From 83a1e4f5b63720d078e72992799c772b26e042cf Mon Sep 17 00:00:00 2001 From: Austin Yang Date: Sat, 24 Feb 2024 18:28:54 -0600 Subject: [PATCH] Initial commit --- Aiming/Aim.py | 174 -- Aiming/DistEst/__init__.py | 3 - Aiming/DistEst/pnp_solver.py | 54 - Aiming/Tracking/EKF_tracker.py | 168 -- Aiming/Tracking/KF_tracker_modified.py | 259 --- Aiming/Tracking/__init__.py | 6 - Aiming/Tracking/basic_tracker.py | 176 -- Aiming/Tracking/consistent_id_gen.py | 33 - Aiming/TrajModel/__init__.py | 6 - Aiming/TrajModel/gravity.py | 50 - Camera/camera_base.py | 26 - Camera/d455.py.deprecated | 31 - Camera/mdvs.py | 140 -- Camera/mvsdk.py | 2403 ------------------------ Camera/read_from_file.py | 73 - Camera/shl_200ws.py.deprecated | 35 - Camera/simple_cv.py | 39 - Communication/communicator.py | 5 +- Detection/CV_mix_DL.py | 650 ------- Detection/YOLO.py.deprecated | 210 --- Utils/__init__.py | 139 -- config.py | 26 - docs/comm_protocol.md | 135 -- examples/filtering_sample.ipynb | 246 --- examples/test_1.jpg | Bin 6641435 -> 0 bytes examples/test_2.jpg | Bin 6471846 -> 0 bytes examples/test_detection.ipynb | 233 --- fc.onnx | Bin 664680 -> 0 bytes recorder.py | 65 - requirements.txt | 3 - vision.py | 127 -- 31 files changed, 4 insertions(+), 5511 deletions(-) delete mode 100644 Aiming/Aim.py delete mode 100644 Aiming/DistEst/__init__.py delete mode 100644 Aiming/DistEst/pnp_solver.py delete mode 100644 Aiming/Tracking/EKF_tracker.py delete mode 100644 Aiming/Tracking/KF_tracker_modified.py delete mode 100644 Aiming/Tracking/__init__.py delete mode 100644 Aiming/Tracking/basic_tracker.py delete mode 100644 Aiming/Tracking/consistent_id_gen.py delete mode 100644 Aiming/TrajModel/__init__.py delete mode 100644 Aiming/TrajModel/gravity.py delete mode 100644 Camera/camera_base.py delete mode 100644 Camera/d455.py.deprecated delete mode 100644 Camera/mdvs.py delete mode 100644 Camera/mvsdk.py delete mode 100644 Camera/read_from_file.py delete mode 100644 Camera/shl_200ws.py.deprecated delete mode 100644 Camera/simple_cv.py delete mode 100644 Detection/CV_mix_DL.py delete mode 100644 Detection/YOLO.py.deprecated delete mode 100644 docs/comm_protocol.md delete mode 100644 examples/filtering_sample.ipynb delete mode 100644 examples/test_1.jpg delete mode 100644 examples/test_2.jpg delete mode 100644 examples/test_detection.ipynb delete mode 100644 fc.onnx delete mode 100644 recorder.py delete mode 100644 vision.py diff --git a/Aiming/Aim.py b/Aiming/Aim.py deleted file mode 100644 index fdc3ee0..0000000 --- a/Aiming/Aim.py +++ /dev/null @@ -1,174 +0,0 @@ -"""Hosts the Aim class, which is the main class for auto-aiming.""" -from .Tracking import basic_tracker -from .DistEst import pnp_estimator -from .TrajModel import * -import numpy as np -import Utils - -from IPython import embed - - -class Aim: - """ - The main class for auto-aiming. - - Its workflow: - 1. takes in a list of predictions from the detection module - 2. apply tracker to fill in missing predictions / append or associate predictions - 3. It selects a single armor to hit - 4. It computes the yaw/pitch difference to the armor - 5. Finally, apply posterior calibration (e.g., range table to hit far targets) - """ - - def __init__(self, config): - """Get the config and initialize the tracker. - - Args: - config (python object): shared config - """ - self.CFG = config - self.tracker = basic_tracker(self.CFG) - self.distance_estimator = pnp_estimator(self.CFG) - - def preprocess(self, pred_list, stm32_state_dict, rgb_img): - """Preprocess predictions to compute armor distances and absolute yaw/pitch. - - Args: - pred_list (list): a list of predictions - stm32_state_dict (dict): a dictionary of stm32 state - - Returns: - list: a list of tuples (armor_type, abs_yaw, abs_pitch, y_distance, z_distance) - """ - gimbal_yaw = stm32_state_dict['cur_yaw'] - gimbal_pitch = stm32_state_dict['cur_pitch'] - - ret_list = [] - - for pred in pred_list: - armor_name, conf, armor_type, bbox, armor = pred - c_x, c_y, w, h = bbox - rel_yaw, rel_pitch = self.get_rotation_angle(c_x, c_y) - abs_yaw = gimbal_yaw + rel_yaw - abs_pitch = gimbal_pitch + rel_pitch - y_distance, z_distance = self.distance_estimator.estimate_distance(armor, rgb_img) - - ret_list.append((armor_type, abs_yaw, abs_pitch, y_distance, z_distance)) - - return ret_list - - def pick_target(self, distance_angle_list, stm32_state_dict): - """Select a priortized target from a list of targets. - - Args: - distance_angle_list (list): list of targets returned from tracker - stm32_state_dict (dict): a dictionary of stm32 state - - Returns: - target: a tuple of (target_pitch, target_yaw, target_y_dist, target_z_dist) - """ - gimbal_pitch = stm32_state_dict['cur_pitch'] - gimbal_yaw = stm32_state_dict['cur_yaw'] - - target_pitch = None - target_yaw = None - target_y_dist = None - target_z_dist = None - min_angle_diff = 9999 - - for y_dist, z_dist, predicted_pitch, predicted_yaw in distance_angle_list: - pitch_diff = Utils.get_radian_diff(predicted_pitch, gimbal_pitch) - yaw_diff = Utils.get_radian_diff(predicted_yaw, gimbal_yaw) - angle_diff = pitch_diff + yaw_diff - if angle_diff < min_angle_diff: - target_pitch = predicted_pitch - target_yaw = predicted_yaw - target_y_dist = y_dist - target_z_dist = z_dist - min_angle_diff = angle_diff - - return target_pitch, target_yaw, target_y_dist, target_z_dist - - def process_one(self, pred_list, enemy_team, rgb_img, stm32_state_dict): - """Process one frame of predictions. - - Args: - pred_list (list): a list of predictions - enemy_team (str): 'blue' or 'red' - rgb_img (np.ndarray): RGB image - stm32_state_dict (dict): a dictionary of stm32 state - - Returns: - dict: a dictionary of results - """ - assert enemy_team in ['blue', 'red'] - - observed_armors = self.preprocess(pred_list, stm32_state_dict, rgb_img) - - distance_angle_list, final_id_list = self.tracker.process_one( - observed_armors, enemy_team, rgb_img) - - # TODO: integrate this into tracking for consistent tracking - target_dist_angle_tuple = self.pick_target(distance_angle_list, stm32_state_dict) - - if target_dist_angle_tuple[0] is None: - return None - - target_pitch, target_yaw, target_y_dist, target_z_dist = target_dist_angle_tuple - - calibrated_pitch, calibrated_yaw = self.posterior_calibration( - target_pitch, target_yaw, target_y_dist, target_z_dist) - - return { - # 'yaw_diff': calibrated_yaw_diff, - # 'pitch_diff': calibrated_pitch_diff, - 'abs_yaw': calibrated_yaw, - 'abs_pitch': calibrated_pitch, - # 'center_x': center_x, - # 'center_y': center_y, - # 'final_bbox_list': final_bbox_list, - # 'final_id_list': final_id_list, - } - - def posterior_calibration(self, raw_pitch, raw_yaw, target_y_dist, target_z_dist): - """Given a set of naively estimated parameters, return calibrated parameters. - - Idea: - Use a range table? - - Args: - yaw_diff (float): yaw difference in radians - pitch_diff (float): pitch difference in radians - distance (float): distance to target in meters - - Returns: - (float, float): calibrated yaw_diff, pitch_diff in radians - """ - target_pitch = raw_pitch - target_yaw = raw_yaw - - # Gravity calibration - pitch_diff = calibrate_pitch_gravity(self.CFG, target_z_dist, target_y_dist) - target_pitch -= pitch_diff - - return (target_pitch, target_yaw) - - def get_rotation_angle(self, bbox_center_x, bbox_center_y): - """Given a bounding box center, return the yaw/pitch difference in radians. - - Args: - bbox_center_x (float): x coordinate of the center of the bounding box - bbox_center_y (float): y coordinate of the center of the bounding box - - Returns: - (float, float): yaw_diff, pitch_diff in radians - """ - yaw_diff = (bbox_center_x - self.CFG.IMG_CENTER_X) * \ - (self.CFG.AUTOAIM_CAMERA.YAW_FOV_HALF / self.CFG.IMG_CENTER_X) - pitch_diff = (bbox_center_y - self.CFG.IMG_CENTER_Y) * \ - (self.CFG.AUTOAIM_CAMERA.PITCH_FOV_HALF / self.CFG.IMG_CENTER_Y) - - yaw_diff = -yaw_diff # counter-clockwise is positive - pitch_diff = pitch_diff # down is positive - - return yaw_diff, pitch_diff diff --git a/Aiming/DistEst/__init__.py b/Aiming/DistEst/__init__.py deleted file mode 100644 index 7251d9d..0000000 --- a/Aiming/DistEst/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -"""Aggregate all distance estimators into one module.""" - -from .pnp_solver import pnp_estimator diff --git a/Aiming/DistEst/pnp_solver.py b/Aiming/DistEst/pnp_solver.py deleted file mode 100644 index 69fade8..0000000 --- a/Aiming/DistEst/pnp_solver.py +++ /dev/null @@ -1,54 +0,0 @@ -"""Simple distance solver using PnP.""" -import numpy as np -import cv2 -import Utils - - -class pnp_estimator: - """Distance estimator using PnP.""" - - def __init__(self, cfg): - """Initialize the PnP solver. - - Args: - cfg (object): python config node object - """ - self.cfg = cfg - self.K = Utils.get_intrinsic_matrix(self.cfg) - - # 3D armor board coordinates centered at armor board center - # The unit is in mm (millimeter) - self.armor_3d_pts = np.array([ - [-65, -125 / 4, 0], # left top - [-65, 125 / 4, 0], - [65, -125 / 4, 0], - [65, 125 / 4, 0] - ]).reshape((4, 3, 1)) - - def estimate_distance(self, armor, img_rgb): - """Estimate the distance to the armor. - - Args: - armor (armor): selected armor object - img_rgb (np.array): RGB image of the frame - - Returns: - (y_dist, z_dist): distance along y-axis (pitch) and z-axis (distance from camera) - """ - obj_2d_pts = np.array([ - armor.left_light.top.astype(int), - armor.left_light.btm.astype(int), - armor.right_light.top.astype(int), - armor.right_light.btm.astype(int), - ]).reshape((4, 2, 1)) - - retval, rvec, tvec = cv2.solvePnP(self.armor_3d_pts.astype(float), - obj_2d_pts.astype(float), - self.K, - distCoeffs=None) - - # rot_mat, _ = cv2.Rodrigues(rvec) - abs_dist = np.sqrt(np.sum(tvec**2)) - - # return -tvec[1], tvec[2] - return 0, abs_dist / 1000.0 diff --git a/Aiming/Tracking/EKF_tracker.py b/Aiming/Tracking/EKF_tracker.py deleted file mode 100644 index 219f0b3..0000000 --- a/Aiming/Tracking/EKF_tracker.py +++ /dev/null @@ -1,168 +0,0 @@ -"""Implemented EKF tracker with filterpy library.""" -import scipy.optimize -import numpy as np -from filterpy.kalman import ExtendedKalmanFilter -from scipy.spatial.distance import mahalanobis as scipy_mahalanobis -from .consistent_id_gen import ConsistentIdGenerator - -import Utils - -# TODO: move this to config -FRAME_BUFFER_SIZE = 10 - - -class KalmanTracker(object): - """A class that represents a Kalman Fitler tracker. - - It is the matrix for KF tracking that will be stored in each armor. - """ - - def __init__(self, init_pitch, init_yaw): - """Initialize EKF from armor.""" - dt = 1 - self.kalman = ExtendedKalmanFilter(dim_x=6, dim_z=2) - # F:transition matrix - self.kalman.F = np.array([[1, 0, dt, 0, 0.5 * (dt**2), 0], - [0, 1, 0, dt, 0, 0.5 * (dt**2)], - [0, 0, 1, 0, dt, 0], - [0, 0, 0, 1, 0, dt], - [0, 0, 0, 0, 1, 0], - [0, 0, 0, 0, 0, 1]], np.float32) - # x:initial state initialize the KF position to center - self.kalman.x = np.array([init_pitch, init_yaw, 0, 0, 0, 0]) - # R:measurement noise matrix - # self.kalman.R *= 10 - self.kalman.R = np.array([[1, 0], [0, 1]], np.float32) * 1 - # Q:process noise matrix - self.kalman.Q = np.eye(6) - # P:initial covariance matrix. Tune this up if initial state is not accurate - self.kalman.P *= 10 - # measurement and prediction - self.measurement = np.array([init_pitch, init_yaw], np.float32) - self.prediction = np.array([init_pitch, init_yaw], np.float32) - - def H_of(self, x): - """Compute the jacobian of the measurement function.""" - # Jocobian of the measurement function H - # The measurement model is linear, so the H matrix is - # actually constant and independent of x - return np.array([[1, 0, 0, 0, 0, 0], - [0, 1, 0, 0, 0, 0]]) - - def hx(self, x): - """Compute the measurement from the state vector x.""" - # Return x and y directly as the measurement - return np.array([x[0], x[1]]) - - def update(self, x, y, certain_flag=True): - """Update the state of this armor with matched armor. - - Args: - x: x state (2d coordinates) - y: y state (2d coordinates) - certain_x (bool): whether the x value is certain (observed) - """ - self.measurement = np.array([x, y], np.float32) - self.kalman.update(self.measurement, self.H_of, self.hx) - self.kalman.predict() - self.prediction = self.kalman.x - - def get_prediction(self): - """Predict the x and y values. - - Returns: - tuple: predicted x and y values - """ - return self.prediction[0], self.prediction[1] - - -class tracked_armor(object): - """A class that represents a tracked armor. - - It stores the history of bounding boxes and ROIs, and can predict the - bounding box of the next frame. - """ - - def __init__(self, armor_type, abs_yaw, abs_pitch, y_distance, z_distance, frame_tick): - """Initialize from prediction. - - Args: - bbox (tuple): (center_x, center_y, w, h) - roi (np.ndarray): ROI of the armor - frame_tick (int): frame tick - armor_id (int): unique ID - """ - self.pitch_buffer = [abs_pitch] - self.yaw_buffer = [abs_yaw] - self.armor_type = armor_type - self.y_distance_buffer = [y_distance] - self.z_distance_buffer = [z_distance] - self.observed_frame_tick = [frame_tick] - self.armor_id = -1 # unique ID - self.KF_matrix = KalmanTracker(abs_pitch, abs_yaw) - - def compute_cost(self, other_armor): - """Compute the cost of matching this armor with another armor. - - Args: - other_armor (tracked_armor): another armor - - Returns: - float: cost - """ - assert isinstance(other_armor, tracked_armor) - if self.armor_type != other_armor.armor_type: - return 99999999 - # TODO: use more sophisticated metrics (e.g., RGB) as cost function - my_yaw = self.yaw_buffer[-1] - my_pitch = self.pitch_buffer[-1] - other_yaw = other_armor.yaw_buffer[-1] - other_pitch = other_armor.pitch_buffer[-1] - return Utils.get_radian_diff(my_yaw, other_yaw) + \ - Utils.get_radian_diff(my_pitch, other_pitch) - - def update(self, other_armor, frame_tick): - """Update the state of this armor with matched armor. - - Args: - other_armor (tracked_armor): another armor - frame_tick (int): frame tick - """ - # Only call if these two armors are matched - assert len(other_armor.pitch_buffer) == 1 - self.pitch_buffer.append(other_armor.pitch_buffer[-1]) - self.yaw_buffer.append(other_armor.yaw_buffer[-1]) - self.y_distance_buffer.append(other_armor.y_distance_buffer[-1]) - self.z_distance_buffer.append(other_armor.z_distance_buffer[-1]) - self.observed_frame_tick.append(frame_tick) - - # Maintain each armor's buffer so that anything older than - # FRAME_BUFFER_SIZE is dropped - self.pitch_buffer = self.pitch_buffer[-FRAME_BUFFER_SIZE:] - self.yaw_buffer = self.yaw_buffer[-FRAME_BUFFER_SIZE:] - self.y_distance_buffer = self.y_distance_buffer[-FRAME_BUFFER_SIZE:] - self.z_distance_buffer = self.z_distance_buffer[-FRAME_BUFFER_SIZE:] - self.observed_frame_tick = self.observed_frame_tick[-FRAME_BUFFER_SIZE:] - - def predict_distance_angle(self, cur_frame_tick): - """Predict the distance and angle of the tracked armor at cur frame tick. - - Args: - cur_frame_tick (int): current frame tick - - Returns: - tuple: (y_distance, z_distance, yaw, pitch) - """ - if cur_frame_tick == self.observed_frame_tick[-1] or len(self.y_distance_buffer) == 1: - cur_pitch = self.pitch_buffer[-1] - cur_yaw = self.yaw_buffer[-1] - self.KF_matrix.update(cur_pitch, cur_yaw) - return self.y_distance_buffer[-1], self.z_distance_buffer[-1], cur_pitch, cur_yaw - else: - # KF tracking - predicted_pitch, predicted_yaw = self.KF_matrix.get_prediction() - self.KF_matrix.update(predicted_pitch, predicted_yaw) - # TODO: use filtering to predict distances as well - latest_y_dist = self.y_distance_buffer[-1] - latest_z_dist = self.z_distance_buffer[-1] - return latest_y_dist, latest_z_dist, predicted_pitch, predicted_yaw diff --git a/Aiming/Tracking/KF_tracker_modified.py b/Aiming/Tracking/KF_tracker_modified.py deleted file mode 100644 index acfc229..0000000 --- a/Aiming/Tracking/KF_tracker_modified.py +++ /dev/null @@ -1,259 +0,0 @@ -"""Defines a basic linear tracker and base classes for future dev.""" -import scipy.optimize -import numpy as np -import cv2 - -from .consistent_id_gen import ConsistentIdGenerator - -# TODO: move this to config -FRAME_BUFFER_SIZE = 10 - -# TODO: this class should be part of abstract base tracker class - - -class KalmanTracker(object): - """A class that represents a Kalman Fitler tracker. - - It is the matrix for KF tracking that will be stored in each armor. - """ - - def __init__(self): - """Initialize from armor.""" - self.kalman = cv2.KalmanFilter(4, 2) - self.kalman.measurementMatrix = np.array([[1, 0, 0, 0], [0, 1, 0, 0]], np.float32) - self.kalman.transitionMatrix = np.array( - [[1, 0, 1, 0], [0, 1, 0, 1], [0, 0, 1, 0], [0, 0, 0, 1]], np.float32) - self.kalman.measurementNoiseCov = np.array([[1, 0], [0, 1]], np.float32) * 1 - self.kalman.processNoiseCov = np.array( - [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]], np.float32) * 1 - self.kalman.controlMatrix = np.array([[0.5, 0], - [0, 0.5], - [1, 0], - [0, 1]], np.float32) - # initialize the KF position to center - initial_state = np.array([320, 180, 0, 0], np.float32) - self.kalman.statePre = initial_state - - self.measurement = np.array((2, 1), np.float32) - self.prediction = np.zeros((2, 1), np.float32) - self.acceleration = np.array((2, 1), np.float32) - - def update(self, x, y): - """Update the value of KF_matrix. - - Args: - x (int): detected x value - y (int): detected y value - """ - acceleration = np.array( - [[(x - self.measurement[0])], [(y - self.measurement[1])]], np.float32) - self.measurement = np.array([[x], [y]], np.float32) - # self.kalman.transitionMatrix[2, 0] = 0.5 * acceleration[0, 0] - # self.kalman.transitionMatrix[3, 1] = 0.5 * acceleration[1, 0] - self.kalman.correct(self.measurement) - self.prediction = self.kalman.predict() - - def get_prediction(self): - """Predict the x and y values. - - Returns: - tuple: predicted x and y values - """ - return int(self.prediction[0]), int(self.prediction[1]) - -# class KalmanTracker(object): # assume constant acceleration -# def __init__(self, dt): -# self.kalman = cv2.KalmanFilter(6, 2) -# self.kalman.measurementMatrix = np.array([[1, 0, 0, 0, 0, 0], -# [0, 1, 0, 0, 0, 0]], np.float32) -# self.kalman.transitionMatrix = np.array([ -# [1, 0, dt, 0, 0.5*dt**2, 0], -# [0, 1, 0, dt, 0, 0.5*dt**2], -# [0, 0, 1, 0, dt, 0], -# [0, 0, 0, 1, 0, dt], -# [0, 0, 0, 0, 1, 0], -# [0, 0, 0, 0, 0, 1]], np.float32) -# self.kalman.processNoiseCov = np.eye(6, dtype=np.float32) * 0.03 - -# # initialize the KF position to center -# initial_state = np.array([320, 180, 0, 0, 0, 0], np.float32) -# self.kalman.statePre = initial_state - -# self.measurement = np.array((2, 1), np.float32) -# self.prediction = np.zeros((2, 1), np.float32) - -# def update(self, x, y): -# self.measurement = np.array([[x], [y]], np.float32) -# self.kalman.correct(self.measurement) -# self.prediction = self.kalman.predict() - -# def get_prediction(self): -# return int(self.prediction[0]), int(self.prediction[1]) - - -class tracked_armor(object): - """A class that represents a tracked armor. - - It stores the history of bounding boxes and ROIs, and can predict the - bounding box of the next frame. - """ - - def __init__(self, bbox, roi, frame_tick, armor_id): - """Initialize from prediction. - - Args: - bbox (tuple): (center_x, center_y, w, h) - roi (np.ndarray): ROI of the armor - frame_tick (int): frame tick - armor_id (int): unique ID - """ - self.bbox_buffer = [bbox] - self.roi_buffer = [roi] - self.observed_frame_tick = [frame_tick] - self.armor_id = armor_id # unique ID - self.KF_matrix = KalmanTracker() - # self.KF_matrix = KalmanTracker(0.05) # dt = 0.05 - - def compute_cost(self, other_armor): - """Compute the cost of matching this armor with another armor. - - Args: - other_armor (tracked_armor): another armor - - Returns: - float: cost - """ - assert isinstance(other_armor, tracked_armor) - # TODO: use more sophisticated metrics (e.g., RGB) as cost function - c_x, c_y, w, h = self.bbox_buffer[-1] - o_c_x, o_c_y, o_w, o_h = other_armor.bbox_buffer[-1] - return np.square(c_x - o_c_x) + np.square(c_y - o_c_y) - - def update(self, other_armor, frame_tick): - """Update the state of this armor with matched armor. - - Args: - other_armor (tracked_armor): another armor - frame_tick (int): frame tick - """ - # Only call if these two armors are matched - self.bbox_buffer.append(other_armor.bbox_buffer[-1]) - self.roi_buffer.append(other_armor.roi_buffer[-1]) - self.observed_frame_tick.append(frame_tick) - - # Maintain each armor's buffer so that anything older than - # FRAME_BUFFER_SIZE is dropped - self.bbox_buffer = self.bbox_buffer[-FRAME_BUFFER_SIZE:] - self.roi_buffer = self.roi_buffer[-FRAME_BUFFER_SIZE:] - - def predict_bbox(self, cur_frame_tick): - """Predict the bounding box of the tracked armor at cur frame tick. - - Args: - cur_frame_tick (int): current frame tick - - TODO - - Use Kalman filter to do prediction - - Support future frame idx for predictions - - Returns: - tuple: (center_x, center_y, w, h) - """ - if cur_frame_tick == self.observed_frame_tick[-1] or len( - self.bbox_buffer) == 1: - # print(self.bbox_buffer[-1]) - c_x, c_y, w, h = self.bbox_buffer[-1] - self.KF_matrix.update(c_x, c_y) - return self.bbox_buffer[-1] - else: - # KF tracking - c_x, c_y, w, h = self.bbox_buffer[-1] - predicted_x, predicted_y = self.KF_matrix.get_prediction() - self.KF_matrix.update(predicted_x, predicted_y) - return (int(predicted_x), int(predicted_y), w, h) - - -class KF_tracker(object): - """ - Basic tracker that can handle only one target. - - It memorizes the state of last two predictions and do linear extrapolation - """ - - SE_THRESHOLD = 3200 # (40, 40) pixels away - - def __init__(self, config): - """Initialize the simple lineartracker. - - Args: - config (python object): shared config - """ - self.CFG = config - self.active_armors = [] - self.id_gen = ConsistentIdGenerator() - self.frame_tick = 0 # TODO: use timestamp may be a better idea - - def process_one(self, pred_list, enemy_team, rgb_img): - """Process one set of detections and rgb images. - - Args: - pred_list (list): list of (name, conf, bbox) tuples - enemy_team (str): enemy team name (blue or red) - rgb_img (np.ndarray): RGB image - - Returns: - (list, list): list of tracked_armors (detections+predictions) and their IDs - """ - new_armors = [] - for name, conf, bbox in pred_list: - c_x, c_y, w, h = bbox - lower_x = int(c_x - w / 2) - upper_x = int(c_x + w / 2) - lower_y = int(c_y - h / 2) - upper_y = int(c_y + h / 2) - roi = rgb_img[lower_y:upper_y, lower_x:upper_x] - new_armors.append(tracked_armor(bbox, roi, self.frame_tick, -1)) - - if len(self.active_armors) > 0: - # Try to associate with current armors - cost_matrix = np.zeros( - (len(new_armors), len(self.active_armors)), dtype=float) - for i in range(len(new_armors)): - for j in range(len(self.active_armors)): - cost_ij = new_armors[i].compute_cost(self.active_armors[j]) - cost_matrix[i, j] = cost_ij - row_ind, col_ind = scipy.optimize.linear_sum_assignment( - cost_matrix) - - for i, j in zip(row_ind, col_ind): - if cost_matrix[i, j] < self.SE_THRESHOLD: - assert new_armors[i] is not None - self.active_armors[j].update( - new_armors[i], self.frame_tick) - new_armors[i] = None - - new_armors = [i for i in new_armors if i is not None] - - for n in new_armors: - n.armor_id = self.id_gen.get_id() - - # Maintain current buffer. If an armor has not been observed by 10 - # frames, it is dropped - self.active_armors = [i for i in self.active_armors - if self.frame_tick - i.observed_frame_tick[-1] < FRAME_BUFFER_SIZE] - - # Unassociated armors are registered as new armors - for a in new_armors: - self.active_armors.append(a) - - # Create a list of bbox and unique IDs to return - ret_bbox_list = [] - ret_id_list = [] - for a in self.active_armors: - # If an armor is observed, directly use the bbox - ret_bbox_list.append(a.predict_bbox(self.frame_tick)) - ret_id_list.append(a.armor_id) - - self.frame_tick += 1 - - return ret_bbox_list, ret_id_list diff --git a/Aiming/Tracking/__init__.py b/Aiming/Tracking/__init__.py deleted file mode 100644 index ae847ab..0000000 --- a/Aiming/Tracking/__init__.py +++ /dev/null @@ -1,6 +0,0 @@ -"""Aggregate all the tracking algorithms into one module.""" - -# Basic tracker: simple linear extrapolation + Hungarian algorithm on -# image plane -from .basic_tracker import basic_tracker -from .KF_tracker_modified import KF_tracker diff --git a/Aiming/Tracking/basic_tracker.py b/Aiming/Tracking/basic_tracker.py deleted file mode 100644 index 867f861..0000000 --- a/Aiming/Tracking/basic_tracker.py +++ /dev/null @@ -1,176 +0,0 @@ -"""Defines a basic linear tracker and base classes for future dev.""" -import scipy.optimize -import numpy as np - -from .consistent_id_gen import ConsistentIdGenerator - -# TODO: this class should be part of abstract base tracker class -from .EKF_tracker import tracked_armor - -# TODO: move this to config -FRAME_BUFFER_SIZE = 10 - -# class tracked_armor(object): -# """A class that represents a tracked armor. - -# It stores the history of bounding boxes and ROIs, and can predict the -# bounding box of the next frame. -# """ - -# def __init__(self, bbox, roi, frame_tick, armor_id): -# """Initialize from prediction. - -# Args: -# bbox (tuple): (center_x, center_y, w, h) -# roi (np.ndarray): ROI of the armor -# frame_tick (int): frame tick -# armor_id (int): unique ID -# """ -# self.bbox_buffer = [bbox] -# self.roi_buffer = [roi] -# self.observed_frame_tick = [frame_tick] -# self.armor_id = armor_id # unique ID - -# def compute_cost(self, other_armor): -# """Compute the cost of matching this armor with another armor. - -# Args: -# other_armor (tracked_armor): another armor - -# Returns: -# float: cost -# """ -# assert isinstance(other_armor, tracked_armor) -# # TODO: use more sophisticated metrics (e.g., RGB) as cost function -# c_x, c_y, w, h = self.bbox_buffer[-1] -# o_c_x, o_c_y, o_w, o_h = other_armor.bbox_buffer[-1] -# return np.square(c_x - o_c_x) + np.square(c_y - o_c_y) - -# def update(self, other_armor, frame_tick): -# """Update the state of this armor with matched armor. - -# Args: -# other_armor (tracked_armor): another armor -# frame_tick (int): frame tick -# """ -# # Only call if these two armors are matched -# self.bbox_buffer.append(other_armor.bbox_buffer[-1]) -# self.roi_buffer.append(other_armor.roi_buffer[-1]) -# self.observed_frame_tick.append(frame_tick) - -# # Maintain each armor's buffer so that anything older than -# # FRAME_BUFFER_SIZE is dropped -# self.bbox_buffer = self.bbox_buffer[-FRAME_BUFFER_SIZE:] -# self.roi_buffer = self.roi_buffer[-FRAME_BUFFER_SIZE:] - -# def predict_bbox(self, cur_frame_tick): -# """Predict the bounding box of the tracked armor at cur frame tick. - -# Args: -# cur_frame_tick (int): current frame tick - -# TODO -# - Use Kalman filter to do prediction -# - Support future frame idx for predictions - -# Returns: -# tuple: (center_x, center_y, w, h) -# """ -# if cur_frame_tick == self.observed_frame_tick[-1] or len( -# self.bbox_buffer) == 1: -# return self.bbox_buffer[-1] -# else: -# # Linear extrapolation -# c_x, c_y, w, h = self.bbox_buffer[-1] -# o_c_x, o_c_y, o_w, o_h = self.bbox_buffer[-2] -# delta_tick = self.observed_frame_tick[-1] - \ -# self.observed_frame_tick[-2] -# new_delta_tick = cur_frame_tick - self.observed_frame_tick[-1] -# delta_x = (c_x - o_c_x) * new_delta_tick / delta_tick -# delta_y = (c_y - o_c_y) * new_delta_tick / delta_tick -# return (int(c_x + delta_x), int(c_y + delta_y), w, h) - - -class basic_tracker(object): - """ - Basic tracker that can handle only one target. - - It memorizes the state of last two predictions and do linear extrapolation - """ - - SE_THRESHOLD = 3200 # (40, 40) pixels away - - def __init__(self, config): - """Initialize the simple lineartracker. - - Args: - config (python object): shared config - """ - self.CFG = config - self.active_armors = [] - self.id_gen = ConsistentIdGenerator() - self.frame_tick = 0 # TODO: use timestamp may be a better idea - - def process_one(self, pred_list, enemy_team, rgb_img): - """Process one set of detections and rgb images. - - Args: - pred_list (list): (armor_type, abs_yaw, abs_pitch, y_distance, z_distance) tuples - enemy_team (str): enemy team name (blue or red) - rgb_img (np.ndarray): RGB image - - Returns: - (list, list): list of tracked_armors (detections+predictions) and their IDs - """ - new_armors = [] - for armor_type, abs_yaw, abs_pitch, y_distance, z_distance in pred_list: - new_armors.append( - tracked_armor( - armor_type, - abs_yaw, - abs_pitch, - y_distance, - z_distance, - self.frame_tick)) - - if len(self.active_armors) > 0: - # Try to associate with current armors - cost_matrix = np.zeros((len(new_armors), len(self.active_armors)), dtype=float) - for i in range(len(new_armors)): - for j in range(len(self.active_armors)): - cost_ij = new_armors[i].compute_cost(self.active_armors[j]) - cost_matrix[i, j] = cost_ij - - row_ind, col_ind = scipy.optimize.linear_sum_assignment(cost_matrix) - - for i, j in zip(row_ind, col_ind): - if cost_matrix[i, j] < self.SE_THRESHOLD: - assert new_armors[i] is not None - self.active_armors[j].update(new_armors[i], self.frame_tick) - new_armors[i] = None - - new_armors = [i for i in new_armors if i is not None] - - for n in new_armors: - n.armor_id = self.id_gen.get_id() - - # Maintain current buffer. If an armor has not been observed by FRAME_BUFFER_SIZE - # frames, it is dropped - self.active_armors = [i for i in self.active_armors - if self.frame_tick - i.observed_frame_tick[-1] < FRAME_BUFFER_SIZE] - - # Unassociated armors are registered as new armors - for a in new_armors: - self.active_armors.append(a) - - # Create a list of bbox and unique IDs to return - ret_distance_angle_list = [] - ret_id_list = [] - for a in self.active_armors: - # If an armor is observed, directly use the bbox - ret_distance_angle_list.append(a.predict_distance_angle(self.frame_tick)) - ret_id_list.append(a.armor_id) - - self.frame_tick += 1 - - return ret_distance_angle_list, ret_id_list diff --git a/Aiming/Tracking/consistent_id_gen.py b/Aiming/Tracking/consistent_id_gen.py deleted file mode 100644 index 806b3ee..0000000 --- a/Aiming/Tracking/consistent_id_gen.py +++ /dev/null @@ -1,33 +0,0 @@ -"""Module for generating consistent id for each object.""" - -import threading - - -class ConsistentIdGenerator: - """Return a consistent id for each object.""" - - def __init__(self, lock=False): - """Initialize the ID generator. - - Args: - lock (bool, optional): Whether this function runs in multi-threading. - Defaults to False for efficiency. - """ - self.lock_flag = lock - if self.lock_flag: - self._lock = threading.Lock() - self._id = 0 - - def get_id(self): - """Get a consistent int id. - - Returns: - int: a unique id - """ - if self.lock_flag: - with self._lock: - self._id += 1 - return self._id - else: - self._id += 1 - return self._id diff --git a/Aiming/TrajModel/__init__.py b/Aiming/TrajModel/__init__.py deleted file mode 100644 index a24a3e6..0000000 --- a/Aiming/TrajModel/__init__.py +++ /dev/null @@ -1,6 +0,0 @@ -"""Aggregate all the trajectory modeling methods into one module. - -For a complete explanation of each module, please refer to the README.md. -""" - -from .gravity import calibrate_pitch_gravity diff --git a/Aiming/TrajModel/gravity.py b/Aiming/TrajModel/gravity.py deleted file mode 100644 index e73bb4b..0000000 --- a/Aiming/TrajModel/gravity.py +++ /dev/null @@ -1,50 +0,0 @@ -"""Calibrate pitch offset to account for gravity.""" -import numpy as np -import numdifftools - - -def calibrate_pitch_gravity(cfg, x1, y1): - """Calibrate pitch offset to account for gravity and air resistance. - - Args: - cfg (python object): config.py config node object - x1 (float): horizontal coordinate in hypothetical landing spot - y1 (float): vertical coordinate in hypothetical landing spot - - Returns: - pitch_offset (float): how much to offset pitch angle - """ - g = cfg.GRAVITY_CONSTANT - v = cfg.INITIAL_BULLET_SPEED - # define the function - # TODO(roger): solving this equation assumes no air resistance - - # You can get where this function comes from by asking GPT4 with the following prompt: - - # Consider a 2D coordinate frame where a cannon is at the origin point (0, 0). - # Given the initial velocity of a cannon ball and its landing location, (x1, y1), - # compute the pitch angle of the cannon. - def f(theta): - return x1 * np.tan(theta) - (g * x1**2) / (2 * v**2 * np.cos(theta)**2) - y1 - - # define the derivative of the function - # def df(theta): - # return derivative(f, theta, dx=1e-6) - df = numdifftools.Derivative(f) - - # initial guess - theta = 0 - - # Newton's method - success_flag = False - for i in range(100): - theta_new = theta - f(theta) / df(theta) - if abs(theta_new - theta) < 1e-6: - success_flag = True - break - theta = theta_new - - if success_flag: - return theta - else: - return 0 diff --git a/Camera/camera_base.py b/Camera/camera_base.py deleted file mode 100644 index fee02a4..0000000 --- a/Camera/camera_base.py +++ /dev/null @@ -1,26 +0,0 @@ -"""Base class for all camera implementations.""" -from abc import abstractmethod - - -class CameraBase: - """Base class for all camera implementations.""" - - def __init__(self, cfg): - """Initialize the camera. - - Args: - cfg (python object): shared config object - """ - self.cfg = cfg - self.width = self.cfg.IMG_WIDTH - self.height = self.cfg.IMG_HEIGHT - self.exposure_time = int(self.cfg.EXPOSURE_TIME) - - @abstractmethod - def get_frame(self): - """Call to get a frame from the camera. - - Returns: - np.ndarray: RGB image frame - """ - raise NotImplementedError diff --git a/Camera/d455.py.deprecated b/Camera/d455.py.deprecated deleted file mode 100644 index a935329..0000000 --- a/Camera/d455.py.deprecated +++ /dev/null @@ -1,31 +0,0 @@ -import numpy as np -import pyrealsense2 as rs -import Utils - -# TODO: make an abstract camera base class -class D455_camera(object): - # Camera parameters from intelrealsense.com/depth-camera/d-455/ - # TODO: for better accuracy, use individual calibrated intrinsics - YAW_FOV_HALF = Utils.deg_to_rad(87) / 2 - PITCH_FOV_HALF = Utils.deg_to_rad(58) / 2 - - def __init__(self, width, height): - self.width = width - self.height = height - - self.pipeline = rs.pipeline() - - self.config = rs.config() - self.config.enable_stream(rs.stream.depth, self.width, self.height, rs.format.z16, 30) - self.config.enable_stream(rs.stream.color, self.width, self.height, rs.format.bgr8, 30) - - self.pipeline.start(self.config) - - def get_frame(self): - RGBD_frame = self.pipeline.wait_for_frames() - - frame = np.array(RGBD_frame.get_color_frame().get_data()) # HW3 - depth = np.array(RGBD_frame.get_depth_frame().get_data()) # uint16 0-65535 - depth[depth == 65535] = 0 # mask ignored label to background - - return (frame, depth) diff --git a/Camera/mdvs.py b/Camera/mdvs.py deleted file mode 100644 index 766e014..0000000 --- a/Camera/mdvs.py +++ /dev/null @@ -1,140 +0,0 @@ -"""Wrap the MDVS SDK to build a camera driver.""" -import cv2 -import numpy as np -import time -import Utils - -from Camera import mvsdk -from Camera.camera_base import CameraBase - - -class mdvs_camera(CameraBase): - """MDVS camera driver. - - Adapted from official MDVS SDK example code, which is located at - https://mindvision.com.cn/uploadfiles/2021/04/20/75287253862433139.zip - - More official MDVS demo programs can be found here - https://mindvision.com.cn/rjxz/list_12.aspx?lcid=139 - """ - - # Computed using the tool at https://mindvision.com.cn/jtxx/list_108.aspx?lcid=21&lcids=1656 - # Config: 6mm lens, MV-SUA133GC - YAW_FOV_HALF = Utils.deg_to_rad(46.245) / 2 - PITCH_FOV_HALF = Utils.deg_to_rad(37.761) / 2 - - def __init__(self, cfg): - """Initialize the MDVS camera. - - Args: - cfg (python object): shared config object - """ - super().__init__(cfg) - - # Enumerate camera devices - DevList = mvsdk.CameraEnumerateDevice() - nDev = len(DevList) - if nDev < 1: - print("No camera was found!") - return - - for i, DevInfo in enumerate(DevList): - print( - "{}: {} {}".format( - i, - DevInfo.GetFriendlyName(), - DevInfo.GetPortType())) - i = 0 if nDev == 1 else int(input("Select camera: ")) - DevInfo = DevList[i] - print(DevInfo) - - # Initialize connection to camera - self.cam = 0 - try: - self.cam = mvsdk.CameraInit(DevInfo, -1, -1) - except mvsdk.CameraException as e: - print("CameraInit Failed({}): {}".format(e.error_code, e.message)) - return - - # Get camera capability (tech specs) - cap = mvsdk.CameraGetCapability(self.cam) - - # Test if the camera is a mono camera or color camera - monoCamera = (cap.sIspCapacity.bMonoSensor != 0) - - # Set camera output format based on mono or color - if monoCamera: - mvsdk.CameraSetIspOutFormat( - self.cam, mvsdk.CAMERA_MEDIA_TYPE_MONO8) - else: - mvsdk.CameraSetIspOutFormat(self.cam, mvsdk.CAMERA_MEDIA_TYPE_BGR8) - - # Set camera trigger mode to continuous grab - mvsdk.CameraSetTriggerMode(self.cam, 0) - - # Set to manual exposure mode and set exposure time to 30ms - mvsdk.CameraSetAeState(self.cam, 0) - mvsdk.CameraSetExposureTime(self.cam, self.exposure_time * 1000) - - # Calls SDK internal thread to start grabbing images - # If in trigger mode, the image grabbing won't start until a trigger - # frame is received - mvsdk.CameraPlay(self.cam) - - # Compute how much buffer is needed to store the image - # Use maximum supported resolution of the camera to compute - FrameBufferSize = cap.sResolutionRange.iWidthMax * \ - cap.sResolutionRange.iHeightMax * (1 if monoCamera else 3) - - # Allocate RGB buffer, used to store the image converted from RAW by ISP - # Remark: RAW data is transferred to PC, and then converted to RGB by software ISP - # If it is a monochrome camera, the format does not need to be converted - # but the ISP still has other processing, so this buffer is still - # needed - self.frame_buffer = mvsdk.CameraAlignMalloc(FrameBufferSize, 16) - - def get_frame(self): - """Call to get a frame from the camera. - - Raises: - Exception: raised when video file is exhausted - - Returns: - np.ndarray: RGB image frame - """ - # Grab one frame from camera - try: - pRawData, FrameHead = mvsdk.CameraGetImageBuffer(self.cam, 200) - mvsdk.CameraImageProcess(self.cam, pRawData, self.frame_buffer, FrameHead) - mvsdk.CameraReleaseImageBuffer(self.cam, pRawData) - - # At this point the frame is stored in pFrameBuffer. - # For color cameras, pFrameBuffer = RGB data, and formono cameras, - # pFrameBuffer = 8-bit grayscale data - frame_data = ( - mvsdk.c_ubyte * - FrameHead.uBytes).from_address( - self.frame_buffer) - - # Convert C array to numpy array - frame = np.frombuffer(frame_data, dtype=np.uint8) - frame = frame.reshape( - (FrameHead.iHeight, - FrameHead.iWidth, - 1 if FrameHead.uiMediaType == mvsdk.CAMERA_MEDIA_TYPE_MONO8 else 3)) - - frame = cv2.resize(frame, (self.width, self.height), interpolation=cv2.INTER_LINEAR) - if self.cfg.ROTATE_180: - frame = cv2.rotate(frame, cv2.ROTATE_180) - return frame - except mvsdk.CameraException as e: - if e.error_code != mvsdk.CAMERA_STATUS_TIME_OUT: - print("CameraGetImageBuffer failed({}): {}".format(e.error_code, e.message)) - - def __del__(self): - """Clean up MDVS driver connection and buffer.""" - # Shut down SDK camera internal thread - mvsdk.CameraUnInit(self.cam) - - # Release frame buffer - mvsdk.CameraAlignFree(self.frame_buffer) diff --git a/Camera/mvsdk.py b/Camera/mvsdk.py deleted file mode 100644 index 6154792..0000000 --- a/Camera/mvsdk.py +++ /dev/null @@ -1,2403 +0,0 @@ -#coding=utf-8 - -"""MDVS camera SDK. - -Adapted from official MDVS SDK example code, which is located at -https://mindvision.com.cn/uploadfiles/2021/04/20/75287253862433139.zip - -More official MDVS demo programs can be found here - https://mindvision.com.cn/rjxz/list_12.aspx?lcid=139 -""" -import platform -from ctypes import * -from threading import local - -# 回调函数类型 -CALLBACK_FUNC_TYPE = None - -# SDK动态库 -_sdk = None - -def _Init(): - global _sdk - global CALLBACK_FUNC_TYPE - - is_win = (platform.system() == "Windows") - is_x86 = (platform.architecture()[0] == '32bit') - - if is_win: - _sdk = windll.MVCAMSDK if is_x86 else windll.MVCAMSDK_X64 - CALLBACK_FUNC_TYPE = WINFUNCTYPE - else: - _sdk = cdll.LoadLibrary("libMVSDK.so") - CALLBACK_FUNC_TYPE = CFUNCTYPE - -_Init() - -#-------------------------------------------类型定义-------------------------------------------------- - -# 状态码定义 -CAMERA_STATUS_SUCCESS = 0 # 操作成功 -CAMERA_STATUS_FAILED = -1 # 操作失败 -CAMERA_STATUS_INTERNAL_ERROR = -2 # 内部错误 -CAMERA_STATUS_UNKNOW = -3 # 未知错误 -CAMERA_STATUS_NOT_SUPPORTED = -4 # 不支持该功能 -CAMERA_STATUS_NOT_INITIALIZED = -5 # 初始化未完成 -CAMERA_STATUS_PARAMETER_INVALID = -6 # 参数无效 -CAMERA_STATUS_PARAMETER_OUT_OF_BOUND = -7 # 参数越界 -CAMERA_STATUS_UNENABLED = -8 # 未使能 -CAMERA_STATUS_USER_CANCEL = -9 # 用户手动取消了,比如roi面板点击取消,返回 -CAMERA_STATUS_PATH_NOT_FOUND = -10 # 注册表中没有找到对应的路径 -CAMERA_STATUS_SIZE_DISMATCH = -11 # 获得图像数据长度和定义的尺寸不匹配 -CAMERA_STATUS_TIME_OUT = -12 # 超时错误 -CAMERA_STATUS_IO_ERROR = -13 # 硬件IO错误 -CAMERA_STATUS_COMM_ERROR = -14 # 通讯错误 -CAMERA_STATUS_BUS_ERROR = -15 # 总线错误 -CAMERA_STATUS_NO_DEVICE_FOUND = -16 # 没有发现设备 -CAMERA_STATUS_NO_LOGIC_DEVICE_FOUND = -17 # 未找到逻辑设备 -CAMERA_STATUS_DEVICE_IS_OPENED = -18 # 设备已经打开 -CAMERA_STATUS_DEVICE_IS_CLOSED = -19 # 设备已经关闭 -CAMERA_STATUS_DEVICE_VEDIO_CLOSED = -20 # 没有打开设备视频,调用录像相关的函数时,如果相机视频没有打开,则回返回该错误。 -CAMERA_STATUS_NO_MEMORY = -21 # 没有足够系统内存 -CAMERA_STATUS_FILE_CREATE_FAILED = -22 # 创建文件失败 -CAMERA_STATUS_FILE_INVALID = -23 # 文件格式无效 -CAMERA_STATUS_WRITE_PROTECTED = -24 # 写保护,不可写 -CAMERA_STATUS_GRAB_FAILED = -25 # 数据采集失败 -CAMERA_STATUS_LOST_DATA = -26 # 数据丢失,不完整 -CAMERA_STATUS_EOF_ERROR = -27 # 未接收到帧结束符 -CAMERA_STATUS_BUSY = -28 # 正忙(上一次操作还在进行中),此次操作不能进行 -CAMERA_STATUS_WAIT = -29 # 需要等待(进行操作的条件不成立),可以再次尝试 -CAMERA_STATUS_IN_PROCESS = -30 # 正在进行,已经被操作过 -CAMERA_STATUS_IIC_ERROR = -31 # IIC传输错误 -CAMERA_STATUS_SPI_ERROR = -32 # SPI传输错误 -CAMERA_STATUS_USB_CONTROL_ERROR = -33 # USB控制传输错误 -CAMERA_STATUS_USB_BULK_ERROR = -34 # USB BULK传输错误 -CAMERA_STATUS_SOCKET_INIT_ERROR = -35 # 网络传输套件初始化失败 -CAMERA_STATUS_GIGE_FILTER_INIT_ERROR = -36 # 网络相机内核过滤驱动初始化失败,请检查是否正确安装了驱动,或者重新安装。 -CAMERA_STATUS_NET_SEND_ERROR = -37 # 网络数据发送错误 -CAMERA_STATUS_DEVICE_LOST = -38 # 与网络相机失去连接,心跳检测超时 -CAMERA_STATUS_DATA_RECV_LESS = -39 # 接收到的字节数比请求的少 -CAMERA_STATUS_FUNCTION_LOAD_FAILED = -40 # 从文件中加载程序失败 -CAMERA_STATUS_CRITICAL_FILE_LOST = -41 # 程序运行所必须的文件丢失。 -CAMERA_STATUS_SENSOR_ID_DISMATCH = -42 # 固件和程序不匹配,原因是下载了错误的固件。 -CAMERA_STATUS_OUT_OF_RANGE = -43 # 参数超出有效范围。 -CAMERA_STATUS_REGISTRY_ERROR = -44 # 安装程序注册错误。请重新安装程序,或者运行安装目录Setup/Installer.exe -CAMERA_STATUS_ACCESS_DENY = -45 # 禁止访问。指定相机已经被其他程序占用时,再申请访问该相机,会返回该状态。(一个相机不能被多个程序同时访问) -#AIA的标准兼容的错误码 -CAMERA_AIA_PACKET_RESEND = 0x0100 #该帧需要重传 -CAMERA_AIA_NOT_IMPLEMENTED = 0x8001 #设备不支持的命令 -CAMERA_AIA_INVALID_PARAMETER = 0x8002 #命令参数非法 -CAMERA_AIA_INVALID_ADDRESS = 0x8003 #不可访问的地址 -CAMERA_AIA_WRITE_PROTECT = 0x8004 #访问的对象不可写 -CAMERA_AIA_BAD_ALIGNMENT = 0x8005 #访问的地址没有按照要求对齐 -CAMERA_AIA_ACCESS_DENIED = 0x8006 #没有访问权限 -CAMERA_AIA_BUSY = 0x8007 #命令正在处理中 -CAMERA_AIA_DEPRECATED = 0x8008 #0x8008-0x0800B 0x800F 该指令已经废弃 -CAMERA_AIA_PACKET_UNAVAILABLE = 0x800C #包无效 -CAMERA_AIA_DATA_OVERRUN = 0x800D #数据溢出,通常是收到的数据比需要的多 -CAMERA_AIA_INVALID_HEADER = 0x800E #数据包头部中某些区域与协议不匹配 -CAMERA_AIA_PACKET_NOT_YET_AVAILABLE = 0x8010 #图像分包数据还未准备好,多用于触发模式,应用程序访问超时 -CAMERA_AIA_PACKET_AND_PREV_REMOVED_FROM_MEMORY = 0x8011 #需要访问的分包已经不存在。多用于重传时数据已经不在缓冲区中 -CAMERA_AIA_PACKET_REMOVED_FROM_MEMORY = 0x8012 #CAMERA_AIA_PACKET_AND_PREV_REMOVED_FROM_MEMORY -CAMERA_AIA_NO_REF_TIME = 0x0813 #没有参考时钟源。多用于时间同步的命令执行时 -CAMERA_AIA_PACKET_TEMPORARILY_UNAVAILABLE = 0x0814 #由于信道带宽问题,当前分包暂时不可用,需稍后进行访问 -CAMERA_AIA_OVERFLOW = 0x0815 #设备端数据溢出,通常是队列已满 -CAMERA_AIA_ACTION_LATE = 0x0816 #命令执行已经超过有效的指定时间 -CAMERA_AIA_ERROR = 0x8FFF #错误 - -# 图像格式定义 -CAMERA_MEDIA_TYPE_MONO = 0x01000000 -CAMERA_MEDIA_TYPE_RGB = 0x02000000 -CAMERA_MEDIA_TYPE_COLOR = 0x02000000 -CAMERA_MEDIA_TYPE_OCCUPY1BIT = 0x00010000 -CAMERA_MEDIA_TYPE_OCCUPY2BIT = 0x00020000 -CAMERA_MEDIA_TYPE_OCCUPY4BIT = 0x00040000 -CAMERA_MEDIA_TYPE_OCCUPY8BIT = 0x00080000 -CAMERA_MEDIA_TYPE_OCCUPY10BIT = 0x000A0000 -CAMERA_MEDIA_TYPE_OCCUPY12BIT = 0x000C0000 -CAMERA_MEDIA_TYPE_OCCUPY16BIT = 0x00100000 -CAMERA_MEDIA_TYPE_OCCUPY24BIT = 0x00180000 -CAMERA_MEDIA_TYPE_OCCUPY32BIT = 0x00200000 -CAMERA_MEDIA_TYPE_OCCUPY36BIT = 0x00240000 -CAMERA_MEDIA_TYPE_OCCUPY48BIT = 0x00300000 -CAMERA_MEDIA_TYPE_EFFECTIVE_PIXEL_SIZE_MASK = 0x00FF0000 -CAMERA_MEDIA_TYPE_EFFECTIVE_PIXEL_SIZE_SHIFT = 16 -CAMERA_MEDIA_TYPE_ID_MASK = 0x0000FFFF -CAMERA_MEDIA_TYPE_COUNT = 0x46 - -#mono -CAMERA_MEDIA_TYPE_MONO1P = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY1BIT | 0x0037) -CAMERA_MEDIA_TYPE_MONO2P = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY2BIT | 0x0038) -CAMERA_MEDIA_TYPE_MONO4P = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY4BIT | 0x0039) -CAMERA_MEDIA_TYPE_MONO8 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY8BIT | 0x0001) -CAMERA_MEDIA_TYPE_MONO8S = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY8BIT | 0x0002) -CAMERA_MEDIA_TYPE_MONO10 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0003) -CAMERA_MEDIA_TYPE_MONO10_PACKED = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x0004) -CAMERA_MEDIA_TYPE_MONO12 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0005) -CAMERA_MEDIA_TYPE_MONO12_PACKED = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x0006) -CAMERA_MEDIA_TYPE_MONO14 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0025) -CAMERA_MEDIA_TYPE_MONO16 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0007) - -# Bayer -CAMERA_MEDIA_TYPE_BAYGR8 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY8BIT | 0x0008) -CAMERA_MEDIA_TYPE_BAYRG8 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY8BIT | 0x0009) -CAMERA_MEDIA_TYPE_BAYGB8 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY8BIT | 0x000A) -CAMERA_MEDIA_TYPE_BAYBG8 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY8BIT | 0x000B) - -CAMERA_MEDIA_TYPE_BAYGR10_MIPI = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY10BIT | 0x0026) -CAMERA_MEDIA_TYPE_BAYRG10_MIPI = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY10BIT | 0x0027) -CAMERA_MEDIA_TYPE_BAYGB10_MIPI = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY10BIT | 0x0028) -CAMERA_MEDIA_TYPE_BAYBG10_MIPI = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY10BIT | 0x0029) - -CAMERA_MEDIA_TYPE_BAYGR10 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x000C) -CAMERA_MEDIA_TYPE_BAYRG10 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x000D) -CAMERA_MEDIA_TYPE_BAYGB10 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x000E) -CAMERA_MEDIA_TYPE_BAYBG10 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x000F) - -CAMERA_MEDIA_TYPE_BAYGR12 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0010) -CAMERA_MEDIA_TYPE_BAYRG12 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0011) -CAMERA_MEDIA_TYPE_BAYGB12 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0012) -CAMERA_MEDIA_TYPE_BAYBG12 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0013) - -CAMERA_MEDIA_TYPE_BAYGR10_PACKED = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x0026) -CAMERA_MEDIA_TYPE_BAYRG10_PACKED = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x0027) -CAMERA_MEDIA_TYPE_BAYGB10_PACKED = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x0028) -CAMERA_MEDIA_TYPE_BAYBG10_PACKED = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x0029) - -CAMERA_MEDIA_TYPE_BAYGR12_PACKED = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x002A) -CAMERA_MEDIA_TYPE_BAYRG12_PACKED = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x002B) -CAMERA_MEDIA_TYPE_BAYGB12_PACKED = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x002C) -CAMERA_MEDIA_TYPE_BAYBG12_PACKED = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x002D) - -CAMERA_MEDIA_TYPE_BAYGR16 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x002E) -CAMERA_MEDIA_TYPE_BAYRG16 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x002F) -CAMERA_MEDIA_TYPE_BAYGB16 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0030) -CAMERA_MEDIA_TYPE_BAYBG16 = (CAMERA_MEDIA_TYPE_MONO | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0031) - -# RGB -CAMERA_MEDIA_TYPE_RGB8 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY24BIT | 0x0014) -CAMERA_MEDIA_TYPE_BGR8 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY24BIT | 0x0015) -CAMERA_MEDIA_TYPE_RGBA8 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY32BIT | 0x0016) -CAMERA_MEDIA_TYPE_BGRA8 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY32BIT | 0x0017) -CAMERA_MEDIA_TYPE_RGB10 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY48BIT | 0x0018) -CAMERA_MEDIA_TYPE_BGR10 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY48BIT | 0x0019) -CAMERA_MEDIA_TYPE_RGB12 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY48BIT | 0x001A) -CAMERA_MEDIA_TYPE_BGR12 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY48BIT | 0x001B) -CAMERA_MEDIA_TYPE_RGB16 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY48BIT | 0x0033) -CAMERA_MEDIA_TYPE_RGB10V1_PACKED = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY32BIT | 0x001C) -CAMERA_MEDIA_TYPE_RGB10P32 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY32BIT | 0x001D) -CAMERA_MEDIA_TYPE_RGB12V1_PACKED = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY36BIT | 0X0034) -CAMERA_MEDIA_TYPE_RGB565P = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0035) -CAMERA_MEDIA_TYPE_BGR565P = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0X0036) - -# YUV and YCbCr -CAMERA_MEDIA_TYPE_YUV411_8_UYYVYY = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x001E) -CAMERA_MEDIA_TYPE_YUV422_8_UYVY = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x001F) -CAMERA_MEDIA_TYPE_YUV422_8 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0032) -CAMERA_MEDIA_TYPE_YUV8_UYV = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY24BIT | 0x0020) -CAMERA_MEDIA_TYPE_YCBCR8_CBYCR = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY24BIT | 0x003A) -#CAMERA_MEDIA_TYPE_YCBCR422_8 : YYYYCbCrCbCr -CAMERA_MEDIA_TYPE_YCBCR422_8 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x003B) -CAMERA_MEDIA_TYPE_YCBCR422_8_CBYCRY = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0043) -CAMERA_MEDIA_TYPE_YCBCR411_8_CBYYCRYY = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x003C) -CAMERA_MEDIA_TYPE_YCBCR601_8_CBYCR = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY24BIT | 0x003D) -CAMERA_MEDIA_TYPE_YCBCR601_422_8 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x003E) -CAMERA_MEDIA_TYPE_YCBCR601_422_8_CBYCRY = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0044) -CAMERA_MEDIA_TYPE_YCBCR601_411_8_CBYYCRYY = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x003F) -CAMERA_MEDIA_TYPE_YCBCR709_8_CBYCR = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY24BIT | 0x0040) -CAMERA_MEDIA_TYPE_YCBCR709_422_8 = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0041) -CAMERA_MEDIA_TYPE_YCBCR709_422_8_CBYCRY = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY16BIT | 0x0045) -CAMERA_MEDIA_TYPE_YCBCR709_411_8_CBYYCRYY = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY12BIT | 0x0042) - -# RGB Planar -CAMERA_MEDIA_TYPE_RGB8_PLANAR = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY24BIT | 0x0021) -CAMERA_MEDIA_TYPE_RGB10_PLANAR = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY48BIT | 0x0022) -CAMERA_MEDIA_TYPE_RGB12_PLANAR = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY48BIT | 0x0023) -CAMERA_MEDIA_TYPE_RGB16_PLANAR = (CAMERA_MEDIA_TYPE_COLOR | CAMERA_MEDIA_TYPE_OCCUPY48BIT | 0x0024) - -# 保存格式 -FILE_JPG = 1 -FILE_BMP = 2 -FILE_RAW = 4 -FILE_PNG = 8 -FILE_BMP_8BIT = 16 -FILE_PNG_8BIT = 32 -FILE_RAW_16BIT = 64 - -# 触发信号 -EXT_TRIG_LEADING_EDGE = 0 -EXT_TRIG_TRAILING_EDGE = 1 -EXT_TRIG_HIGH_LEVEL = 2 -EXT_TRIG_LOW_LEVEL = 3 -EXT_TRIG_DOUBLE_EDGE = 4 - -# IO模式 -IOMODE_TRIG_INPUT = 0 -IOMODE_STROBE_OUTPUT = 1 -IOMODE_GP_INPUT = 2 -IOMODE_GP_OUTPUT = 3 -IOMODE_PWM_OUTPUT = 4 - - -# 相机操作异常信息 -class CameraException(Exception): - """docstring for CameraException""" - def __init__(self, error_code): - super(CameraException, self).__init__() - self.error_code = error_code - self.message = CameraGetErrorString(error_code) - - def __str__(self): - return 'error_code:{} message:{}'.format(self.error_code, self.message) - -class MvStructure(Structure): - def __str__(self): - strs = [] - for field in self._fields_: - name = field[0] - value = getattr(self, name) - if isinstance(value, type(b'')): - value = _string_buffer_to_str(value) - strs.append("{}:{}".format(name, value)) - return '\n'.join(strs) - - def __repr__(self): - return self.__str__() - - def clone(self): - obj = type(self)() - memmove(byref(obj), byref(self), sizeof(self)) - return obj - -# 相机的设备信息,只读信息,请勿修改 -class tSdkCameraDevInfo(MvStructure): - _fields_ = [("acProductSeries", c_char * 32), #产品系列 - ("acProductName", c_char * 32), #产品名称 - ("acFriendlyName", c_char * 32), #产品昵称 - ("acLinkName", c_char * 32), #内核符号连接名,内部使用 - ("acDriverVersion", c_char * 32), #驱动版本 - ("acSensorType", c_char * 32), #sensor类型 - ("acPortType", c_char * 32), #接口类型 - ("acSn", c_char * 32), #产品唯一序列号 - ("uInstance", c_uint)] #该型号相机在该电脑上的实例索引号,用于区分同型号多相机 - - def GetProductSeries(self): - return _string_buffer_to_str(self.acProductSeries) - def GetProductName(self): - return _string_buffer_to_str(self.acProductName) - def GetFriendlyName(self): - return _string_buffer_to_str(self.acFriendlyName) - def GetLinkName(self): - return _string_buffer_to_str(self.acLinkName) - def GetDriverVersion(self): - return _string_buffer_to_str(self.acDriverVersion) - def GetSensorType(self): - return _string_buffer_to_str(self.acSensorType) - def GetPortType(self): - return _string_buffer_to_str(self.acPortType) - def GetSn(self): - return _string_buffer_to_str(self.acSn) - -# 相机的分辨率设定范围 -class tSdkResolutionRange(MvStructure): - _fields_ = [("iHeightMax", c_int), #图像最大高度 - ("iHeightMin", c_int), #图像最小高度 - ("iWidthMax", c_int), #图像最大宽度 - ("iWidthMin", c_int), #图像最小宽度 - ("uSkipModeMask", c_uint), #SKIP模式掩码,为0,表示不支持SKIP 。bit0为1,表示支持SKIP 2x2 bit1为1,表示支持SKIP 3x3.... - ("uBinSumModeMask", c_uint), #BIN(求和)模式掩码,为0,表示不支持BIN 。bit0为1,表示支持BIN 2x2 bit1为1,表示支持BIN 3x3.... - ("uBinAverageModeMask", c_uint),#BIN(求均值)模式掩码,为0,表示不支持BIN 。bit0为1,表示支持BIN 2x2 bit1为1,表示支持BIN 3x3.... - ("uResampleMask", c_uint)] #硬件重采样的掩码 - -#相机的分辨率描述 -class tSdkImageResolution(MvStructure): - _fields_ = [ - ("iIndex", c_int), # 索引号,[0,N]表示预设的分辨率(N 为预设分辨率的最大个数,一般不超过20),OXFF 表示自定义分辨率(ROI) - ("acDescription", c_char * 32), # 该分辨率的描述信息。仅预设分辨率时该信息有效。自定义分辨率可忽略该信息 - ("uBinSumMode", c_uint), # BIN(求和)的模式,范围不能超过tSdkResolutionRange中uBinSumModeMask - ("uBinAverageMode", c_uint), # BIN(求均值)的模式,范围不能超过tSdkResolutionRange中uBinAverageModeMask - ("uSkipMode", c_uint), # 是否SKIP的尺寸,为0表示禁止SKIP模式,范围不能超过tSdkResolutionRange中uSkipModeMask - ("uResampleMask", c_uint), # 硬件重采样的掩码 - ("iHOffsetFOV", c_int), # 采集视场相对于Sensor最大视场左上角的垂直偏移 - ("iVOffsetFOV", c_int), # 采集视场相对于Sensor最大视场左上角的水平偏移 - ("iWidthFOV", c_int), # 采集视场的宽度 - ("iHeightFOV", c_int), # 采集视场的高度 - ("iWidth", c_int), # 相机最终输出的图像的宽度 - ("iHeight", c_int), # 相机最终输出的图像的高度 - ("iWidthZoomHd", c_int), # 硬件缩放的宽度,不需要进行此操作的分辨率,此变量设置为0. - ("iHeightZoomHd", c_int), # 硬件缩放的高度,不需要进行此操作的分辨率,此变量设置为0. - ("iWidthZoomSw", c_int), # 软件缩放的宽度,不需要进行此操作的分辨率,此变量设置为0. - ("iHeightZoomSw", c_int), # 软件缩放的高度,不需要进行此操作的分辨率,此变量设置为0. - ] - - def GetDescription(self): - return _string_buffer_to_str(self.acDescription) - -#相机白平衡模式描述信息 -class tSdkColorTemperatureDes(MvStructure): - _fields_ = [ - ("iIndex", c_int), # 模式索引号 - ("acDescription", c_char * 32), # 描述信息 - ] - - def GetDescription(self): - return _string_buffer_to_str(self.acDescription) - -#相机帧率描述信息 -class tSdkFrameSpeed(MvStructure): - _fields_ = [ - ("iIndex", c_int), # 帧率索引号,一般0对应于低速模式,1对应于普通模式,2对应于高速模式 - ("acDescription", c_char * 32), # 描述信息 - ] - - def GetDescription(self): - return _string_buffer_to_str(self.acDescription) - -#相机曝光功能范围定义 -class tSdkExpose(MvStructure): - _fields_ = [ - ("uiTargetMin", c_uint), #自动曝光亮度目标最小值 - ("uiTargetMax", c_uint), #自动曝光亮度目标最大值 - ("uiAnalogGainMin", c_uint), #模拟增益的最小值,单位为fAnalogGainStep中定义 - ("uiAnalogGainMax", c_uint), #模拟增益的最大值,单位为fAnalogGainStep中定义 - ("fAnalogGainStep", c_float), #模拟增益每增加1,对应的增加的放大倍数。例如,uiAnalogGainMin一般为16,fAnalogGainStep一般为0.125,那么最小放大倍数就是16*0.125 = 2倍 - ("uiExposeTimeMin", c_uint), #手动模式下,曝光时间的最小值,单位:行。根据CameraGetExposureLineTime可以获得一行对应的时间(微秒),从而得到整帧的曝光时间 - ("uiExposeTimeMax", c_uint), #手动模式下,曝光时间的最大值,单位:行 - ] - -#触发模式描述 -class tSdkTrigger(MvStructure): - _fields_ = [ - ("iIndex", c_int), # 模式索引号 - ("acDescription", c_char * 32), # 描述信息 - ] - - def GetDescription(self): - return _string_buffer_to_str(self.acDescription) - -#传输分包大小描述(主要是针对网络相机有效) -class tSdkPackLength(MvStructure): - _fields_ = [ - ("iIndex", c_int), # 模式索引号 - ("acDescription", c_char * 32), # 描述信息 - ("iPackSize", c_uint), - ] - - def GetDescription(self): - return _string_buffer_to_str(self.acDescription) - -#预设的LUT表描述 -class tSdkPresetLut(MvStructure): - _fields_ = [ - ("iIndex", c_int), # 编号 - ("acDescription", c_char * 32), # 描述信息 - ] - - def GetDescription(self): - return _string_buffer_to_str(self.acDescription) - -#AE算法描述 -class tSdkAeAlgorithm(MvStructure): - _fields_ = [ - ("iIndex", c_int), # 编号 - ("acDescription", c_char * 32), # 描述信息 - ] - - def GetDescription(self): - return _string_buffer_to_str(self.acDescription) - -#RAW转RGB算法描述 -class tSdkBayerDecodeAlgorithm(MvStructure): - _fields_ = [ - ("iIndex", c_int), # 编号 - ("acDescription", c_char * 32), # 描述信息 - ] - - def GetDescription(self): - return _string_buffer_to_str(self.acDescription) - -#帧率统计信息 -class tSdkFrameStatistic(MvStructure): - _fields_ = [ - ("iTotal", c_int), #当前采集的总帧数(包括错误帧) - ("iCapture", c_int), #当前采集的有效帧的数量 - ("iLost", c_int), #当前丢帧的数量 - ] - -#相机输出的图像数据格式 -class tSdkMediaType(MvStructure): - _fields_ = [ - ("iIndex", c_int), # 格式种类编号 - ("acDescription", c_char * 32), # 描述信息 - ("iMediaType", c_uint), # 对应的图像格式编码,如CAMERA_MEDIA_TYPE_BAYGR8。 - ] - - def GetDescription(self): - return _string_buffer_to_str(self.acDescription) - -#伽马的设定范围 -class tGammaRange(MvStructure): - _fields_ = [ - ("iMin", c_int), #最小值 - ("iMax", c_int), #最大值 - ] - -#对比度的设定范围 -class tContrastRange(MvStructure): - _fields_ = [ - ("iMin", c_int), #最小值 - ("iMax", c_int), #最大值 - ] - -#RGB三通道数字增益的设定范围 -class tRgbGainRange(MvStructure): - _fields_ = [ - ("iRGainMin", c_int), #红色增益的最小值 - ("iRGainMax", c_int), #红色增益的最大值 - ("iGGainMin", c_int), #绿色增益的最小值 - ("iGGainMax", c_int), #绿色增益的最大值 - ("iBGainMin", c_int), #蓝色增益的最小值 - ("iBGainMax", c_int), #蓝色增益的最大值 - ] - -#饱和度设定的范围 -class tSaturationRange(MvStructure): - _fields_ = [ - ("iMin", c_int), #最小值 - ("iMax", c_int), #最大值 - ] - -#锐化的设定范围 -class tSharpnessRange(MvStructure): - _fields_ = [ - ("iMin", c_int), #最小值 - ("iMax", c_int), #最大值 - ] - -#ISP模块的使能信息 -class tSdkIspCapacity(MvStructure): - _fields_ = [ - ("bMonoSensor", c_int), #表示该型号相机是否为黑白相机,如果是黑白相机,则颜色相关的功能都无法调节 - ("bWbOnce", c_int), #表示该型号相机是否支持手动白平衡功能 - ("bAutoWb", c_int), #表示该型号相机是否支持自动白平衡功能 - ("bAutoExposure", c_int), #表示该型号相机是否支持自动曝光功能 - ("bManualExposure", c_int), #表示该型号相机是否支持手动曝光功能 - ("bAntiFlick", c_int), #表示该型号相机是否支持抗频闪功能 - ("bDeviceIsp", c_int), #表示该型号相机是否支持硬件ISP功能 - ("bForceUseDeviceIsp", c_int), #bDeviceIsp和bForceUseDeviceIsp同时为TRUE时,表示强制只用硬件ISP,不可取消。 - ("bZoomHD", c_int), #相机硬件是否支持图像缩放输出(只能是缩小)。 - ] - -# 定义整合的设备描述信息,这些信息可以用于动态构建UI -class tSdkCameraCapbility(MvStructure): - _fields_ = [ - ("pTriggerDesc", POINTER(tSdkTrigger)), - ("iTriggerDesc", c_int), #触发模式的个数,即pTriggerDesc数组的大小 - ("pImageSizeDesc", POINTER(tSdkImageResolution)), - ("iImageSizeDesc", c_int), #预设分辨率的个数,即pImageSizeDesc数组的大小 - ("pClrTempDesc", POINTER(tSdkColorTemperatureDes)), - ("iClrTempDesc", c_int), #预设色温个数 - ("pMediaTypeDesc", POINTER(tSdkMediaType)), - ("iMediaTypeDesc", c_int), #相机输出图像格式的种类个数,即pMediaTypeDesc数组的大小。 - ("pFrameSpeedDesc", POINTER(tSdkFrameSpeed)), #可调节帧速类型,对应界面上普通 高速 和超级三种速度设置 - ("iFrameSpeedDesc", c_int), #可调节帧速类型的个数,即pFrameSpeedDesc数组的大小。 - ("pPackLenDesc", POINTER(tSdkPackLength)), #传输包长度,一般用于网络设备 - ("iPackLenDesc", c_int), #可供选择的传输分包长度的个数,即pPackLenDesc数组的大小。 - ("iOutputIoCounts", c_int), #可编程输出IO的个数 - ("iInputIoCounts", c_int), #可编程输入IO的个数 - ("pPresetLutDesc", POINTER(tSdkPresetLut)), #相机预设的LUT表 - ("iPresetLut", c_int), #相机预设的LUT表的个数,即pPresetLutDesc数组的大小 - ("iUserDataMaxLen", c_int), #指示该相机中用于保存用户数据区的最大长度。为0表示无。 - ("bParamInDevice", c_int), #指示该设备是否支持从设备中读写参数组。1为支持,0不支持。 - ("pAeAlmSwDesc", POINTER(tSdkAeAlgorithm)),#软件自动曝光算法描述 - ("iAeAlmSwDesc", c_int), #软件自动曝光算法个数 - ("pAeAlmHdDesc", POINTER(tSdkAeAlgorithm)),#硬件自动曝光算法描述,为NULL表示不支持硬件自动曝光 - ("iAeAlmHdDesc", c_int), #硬件自动曝光算法个数,为0表示不支持硬件自动曝光 - ("pBayerDecAlmSwDesc", POINTER(tSdkBayerDecodeAlgorithm)),#软件Bayer转换为RGB数据的算法描述 - ("iBayerDecAlmSwDesc", c_int), #软件Bayer转换为RGB数据的算法个数 - ("pBayerDecAlmHdDesc", POINTER(tSdkBayerDecodeAlgorithm)),#硬件Bayer转换为RGB数据的算法描述,为NULL表示不支持 - ("iBayerDecAlmHdDesc", c_int), #硬件Bayer转换为RGB数据的算法个数,为0表示不支持 - - # 图像参数的调节范围定义,用于动态构建UI - ("sExposeDesc", tSdkExpose), #曝光的范围值 - ("sResolutionRange", tSdkResolutionRange), #分辨率范围描述 - ("sRgbGainRange", tRgbGainRange), #图像数字增益范围描述 - ("sSaturationRange", tSaturationRange), #饱和度范围描述 - ("sGammaRange", tGammaRange), #伽马范围描述 - ("sContrastRange", tContrastRange), #对比度范围描述 - ("sSharpnessRange", tSharpnessRange), #锐化范围描述 - ("sIspCapacity", tSdkIspCapacity), #ISP能力描述 - ] - -#图像帧头信息 -class tSdkFrameHead(MvStructure): - _fields_ = [ - ("uiMediaType", c_uint), # 图像格式,Image Format - ("uBytes", c_uint), # 图像数据字节数,Total bytes - ("iWidth", c_int), # 宽度 Image height - ("iHeight", c_int), # 高度 Image width - ("iWidthZoomSw", c_int), # 软件缩放的宽度,不需要进行软件裁剪的图像,此变量设置为0. - ("iHeightZoomSw", c_int), # 软件缩放的高度,不需要进行软件裁剪的图像,此变量设置为0. - ("bIsTrigger", c_int), # 指示是否为触发帧 is trigger - ("uiTimeStamp", c_uint), # 该帧的采集时间,单位0.1毫秒 - ("uiExpTime", c_uint), # 当前图像的曝光值,单位为微秒us - ("fAnalogGain", c_float), # 当前图像的模拟增益倍数 - ("iGamma", c_int), # 该帧图像的伽马设定值,仅当LUT模式为动态参数生成时有效,其余模式下为-1 - ("iContrast", c_int), # 该帧图像的对比度设定值,仅当LUT模式为动态参数生成时有效,其余模式下为-1 - ("iSaturation", c_int), # 该帧图像的饱和度设定值,对于黑白相机无意义,为0 - ("fRgain", c_float), # 该帧图像处理的红色数字增益倍数,对于黑白相机无意义,为1 - ("fGgain", c_float), # 该帧图像处理的绿色数字增益倍数,对于黑白相机无意义,为1 - ("fBgain", c_float), # 该帧图像处理的蓝色数字增益倍数,对于黑白相机无意义,为1 - ] - -# Grabber统计信息 -class tSdkGrabberStat(MvStructure): - _fields_ = [ - ("Width", c_int), # 帧图像大小 - ("Height", c_int), # 帧图像大小 - ("Disp", c_int), # 显示帧数量 - ("Capture", c_int), # 采集的有效帧的数量 - ("Lost", c_int), # 丢帧的数量 - ("Error", c_int), # 错帧的数量 - ("DispFps", c_float), # 显示帧率 - ("CapFps", c_float), # 捕获帧率 - ] - -# 方法回调辅助类 -class method(object): - def __init__(self, FuncType): - super(method, self).__init__() - self.FuncType = FuncType - self.cache = {} - - def __call__(self, cb): - self.cb = cb - return self - - def __get__(self, obj, objtype): - try: - return self.cache[obj] - except KeyError as e: - def cl(*args): - return self.cb(obj, *args) - r = self.cache[obj] = self.FuncType(cl) - return r - -# 图像捕获的回调函数定义 -CAMERA_SNAP_PROC = CALLBACK_FUNC_TYPE(None, c_int, c_void_p, POINTER(tSdkFrameHead), c_void_p) - -# 相机连接状态回调 -CAMERA_CONNECTION_STATUS_CALLBACK = CALLBACK_FUNC_TYPE(None, c_int, c_uint, c_uint, c_void_p) - -# 异步抓图完成回调 -pfnCameraGrabberSaveImageComplete = CALLBACK_FUNC_TYPE(None, c_void_p, c_void_p, c_int, c_void_p) - -# 帧监听回调 -pfnCameraGrabberFrameListener = CALLBACK_FUNC_TYPE(c_int, c_void_p, c_int, c_void_p, POINTER(tSdkFrameHead), c_void_p) - -# 采集器图像捕获的回调 -pfnCameraGrabberFrameCallback = CALLBACK_FUNC_TYPE(None, c_void_p, c_void_p, POINTER(tSdkFrameHead), c_void_p) - -#-----------------------------------函数接口------------------------------------------ - -# 线程局部存储 -_tls = local() - -# 存储最后一次SDK调用返回的错误码 -def GetLastError(): - try: - return _tls.last_error - except AttributeError as e: - _tls.last_error = 0 - return 0 - -def SetLastError(err_code): - _tls.last_error = err_code - -def _string_buffer_to_str(buf): - s = buf if isinstance(buf, type(b'')) else buf.value - - for codec in ('gbk', 'utf-8'): - try: - s = s.decode(codec) - break - except UnicodeDecodeError as e: - continue - - if isinstance(s, str): - return s - else: - return s.encode('utf-8') - -def _str_to_string_buffer(str): - if type(str) is type(u''): - s = str.encode('gbk') - else: - s = str.decode('utf-8').encode('gbk') - return create_string_buffer(s) - -def CameraSdkInit(iLanguageSel): - err_code = _sdk.CameraSdkInit(iLanguageSel) - SetLastError(err_code) - return err_code - -def CameraEnumerateDevice(MaxCount = 32): - Nums = c_int(MaxCount) - pCameraList = (tSdkCameraDevInfo * Nums.value)() - err_code = _sdk.CameraEnumerateDevice(pCameraList, byref(Nums)) - SetLastError(err_code) - return pCameraList[0:Nums.value] - -def CameraEnumerateDeviceEx(): - return _sdk.CameraEnumerateDeviceEx() - -def CameraIsOpened(pCameraInfo): - pOpened = c_int() - err_code = _sdk.CameraIsOpened(byref(pCameraInfo), byref(pOpened) ) - SetLastError(err_code) - return pOpened.value != 0 - -def CameraInit(pCameraInfo, emParamLoadMode = -1, emTeam = -1): - pCameraHandle = c_int() - err_code = _sdk.CameraInit(byref(pCameraInfo), emParamLoadMode, emTeam, byref(pCameraHandle)) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return pCameraHandle.value - -def CameraInitEx(iDeviceIndex, emParamLoadMode = -1, emTeam = -1): - pCameraHandle = c_int() - err_code = _sdk.CameraInitEx(iDeviceIndex, emParamLoadMode, emTeam, byref(pCameraHandle)) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return pCameraHandle.value - -def CameraInitEx2(CameraName): - pCameraHandle = c_int() - err_code = _sdk.CameraInitEx2(_str_to_string_buffer(CameraName), byref(pCameraHandle)) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return pCameraHandle.value - -def CameraSetCallbackFunction(hCamera, pCallBack, pContext = 0): - err_code = _sdk.CameraSetCallbackFunction(hCamera, pCallBack, c_void_p(pContext), None) - SetLastError(err_code) - return err_code - -def CameraUnInit(hCamera): - err_code = _sdk.CameraUnInit(hCamera) - SetLastError(err_code) - return err_code - -def CameraGetInformation(hCamera): - pbuffer = c_char_p() - err_code = _sdk.CameraGetInformation(hCamera, byref(pbuffer) ) - SetLastError(err_code) - if err_code == 0 and pbuffer.value is not None: - return _string_buffer_to_str(pbuffer) - return '' - -def CameraImageProcess(hCamera, pbyIn, pbyOut, pFrInfo): - err_code = _sdk.CameraImageProcess(hCamera, c_void_p(pbyIn), c_void_p(pbyOut), byref(pFrInfo)) - SetLastError(err_code) - return err_code - -def CameraImageProcessEx(hCamera, pbyIn, pbyOut, pFrInfo, uOutFormat, uReserved): - err_code = _sdk.CameraImageProcessEx(hCamera, c_void_p(pbyIn), c_void_p(pbyOut), byref(pFrInfo), uOutFormat, uReserved) - SetLastError(err_code) - return err_code - -def CameraDisplayInit(hCamera, hWndDisplay): - err_code = _sdk.CameraDisplayInit(hCamera, hWndDisplay) - SetLastError(err_code) - return err_code - -def CameraDisplayRGB24(hCamera, pFrameBuffer, pFrInfo): - err_code = _sdk.CameraDisplayRGB24(hCamera, c_void_p(pFrameBuffer), byref(pFrInfo) ) - SetLastError(err_code) - return err_code - -def CameraSetDisplayMode(hCamera, iMode): - err_code = _sdk.CameraSetDisplayMode(hCamera, iMode) - SetLastError(err_code) - return err_code - -def CameraSetDisplayOffset(hCamera, iOffsetX, iOffsetY): - err_code = _sdk.CameraSetDisplayOffset(hCamera, iOffsetX, iOffsetY) - SetLastError(err_code) - return err_code - -def CameraSetDisplaySize(hCamera, iWidth, iHeight): - err_code = _sdk.CameraSetDisplaySize(hCamera, iWidth, iHeight) - SetLastError(err_code) - return err_code - -def CameraGetImageBuffer(hCamera, wTimes): - pbyBuffer = c_void_p() - pFrameInfo = tSdkFrameHead() - err_code = _sdk.CameraGetImageBuffer(hCamera, byref(pFrameInfo), byref(pbyBuffer), wTimes) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return (pbyBuffer.value, pFrameInfo) - -def CameraGetImageBufferEx(hCamera, wTimes): - _sdk.CameraGetImageBufferEx.restype = c_void_p - piWidth = c_int() - piHeight = c_int() - pFrameBuffer = _sdk.CameraGetImageBufferEx(hCamera, byref(piWidth), byref(piHeight), wTimes) - err_code = CAMERA_STATUS_SUCCESS if pFrameBuffer else CAMERA_STATUS_TIME_OUT - SetLastError(err_code) - if pFrameBuffer: - return (pFrameBuffer, piWidth.value, piHeight.value) - else: - raise CameraException(err_code) - -def CameraSnapToBuffer(hCamera, wTimes): - pbyBuffer = c_void_p() - pFrameInfo = tSdkFrameHead() - err_code = _sdk.CameraSnapToBuffer(hCamera, byref(pFrameInfo), byref(pbyBuffer), wTimes) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return (pbyBuffer.value, pFrameInfo) - -def CameraReleaseImageBuffer(hCamera, pbyBuffer): - err_code = _sdk.CameraReleaseImageBuffer(hCamera, c_void_p(pbyBuffer) ) - SetLastError(err_code) - return err_code - -def CameraPlay(hCamera): - err_code = _sdk.CameraPlay(hCamera) - SetLastError(err_code) - return err_code - -def CameraPause(hCamera): - err_code = _sdk.CameraPause(hCamera) - SetLastError(err_code) - return err_code - -def CameraStop(hCamera): - err_code = _sdk.CameraStop(hCamera) - SetLastError(err_code) - return err_code - -def CameraInitRecord(hCamera, iFormat, pcSavePath, b2GLimit, dwQuality, iFrameRate): - err_code = _sdk.CameraInitRecord(hCamera, iFormat, _str_to_string_buffer(pcSavePath), b2GLimit, dwQuality, iFrameRate) - SetLastError(err_code) - return err_code - -def CameraStopRecord(hCamera): - err_code = _sdk.CameraStopRecord(hCamera) - SetLastError(err_code) - return err_code - -def CameraPushFrame(hCamera, pbyImageBuffer, pFrInfo): - err_code = _sdk.CameraPushFrame(hCamera, c_void_p(pbyImageBuffer), byref(pFrInfo) ) - SetLastError(err_code) - return err_code - -def CameraSaveImage(hCamera, lpszFileName, pbyImageBuffer, pFrInfo, byFileType, byQuality): - err_code = _sdk.CameraSaveImage(hCamera, _str_to_string_buffer(lpszFileName), c_void_p(pbyImageBuffer), byref(pFrInfo), byFileType, byQuality) - SetLastError(err_code) - return err_code - -def CameraSaveImageEx(hCamera, lpszFileName, pbyImageBuffer, uImageFormat, iWidth, iHeight, byFileType, byQuality): - err_code = _sdk.CameraSaveImageEx(hCamera, _str_to_string_buffer(lpszFileName), c_void_p(pbyImageBuffer), uImageFormat, iWidth, iHeight, byFileType, byQuality) - SetLastError(err_code) - return err_code - -def CameraGetImageResolution(hCamera): - psCurVideoSize = tSdkImageResolution() - err_code = _sdk.CameraGetImageResolution(hCamera, byref(psCurVideoSize) ) - SetLastError(err_code) - return psCurVideoSize - -def CameraSetImageResolution(hCamera, pImageResolution): - err_code = _sdk.CameraSetImageResolution(hCamera, byref(pImageResolution) ) - SetLastError(err_code) - return err_code - -def CameraSetImageResolutionEx(hCamera, iIndex, Mode, ModeSize, x, y, width, height, ZoomWidth, ZoomHeight): - err_code = _sdk.CameraSetImageResolutionEx(hCamera, iIndex, Mode, ModeSize, x, y, width, height, ZoomWidth, ZoomHeight) - SetLastError(err_code) - return err_code - -def CameraGetMediaType(hCamera): - piMediaType = c_int() - err_code = _sdk.CameraGetMediaType(hCamera, byref(piMediaType) ) - SetLastError(err_code) - return piMediaType.value - -def CameraSetMediaType(hCamera, iMediaType): - err_code = _sdk.CameraSetMediaType(hCamera, iMediaType) - SetLastError(err_code) - return err_code - -def CameraSetAeState(hCamera, bAeState): - err_code = _sdk.CameraSetAeState(hCamera, bAeState) - SetLastError(err_code) - return err_code - -def CameraGetAeState(hCamera): - pAeState = c_int() - err_code = _sdk.CameraGetAeState(hCamera, byref(pAeState) ) - SetLastError(err_code) - return pAeState.value - -def CameraSetSharpness(hCamera, iSharpness): - err_code = _sdk.CameraSetSharpness(hCamera, iSharpness) - SetLastError(err_code) - return err_code - -def CameraGetSharpness(hCamera): - piSharpness = c_int() - err_code = _sdk.CameraGetSharpness(hCamera, byref(piSharpness) ) - SetLastError(err_code) - return piSharpness.value - -def CameraSetLutMode(hCamera, emLutMode): - err_code = _sdk.CameraSetLutMode(hCamera, emLutMode) - SetLastError(err_code) - return err_code - -def CameraGetLutMode(hCamera): - pemLutMode = c_int() - err_code = _sdk.CameraGetLutMode(hCamera, byref(pemLutMode) ) - SetLastError(err_code) - return pemLutMode.value - -def CameraSelectLutPreset(hCamera, iSel): - err_code = _sdk.CameraSelectLutPreset(hCamera, iSel) - SetLastError(err_code) - return err_code - -def CameraGetLutPresetSel(hCamera): - piSel = c_int() - err_code = _sdk.CameraGetLutPresetSel(hCamera, byref(piSel) ) - SetLastError(err_code) - return piSel.value - -def CameraSetCustomLut(hCamera, iChannel, pLut): - pLutNative = (c_ushort * 4096)(*pLut) - err_code = _sdk.CameraSetCustomLut(hCamera, iChannel, pLutNative) - SetLastError(err_code) - return err_code - -def CameraGetCustomLut(hCamera, iChannel): - pLutNative = (c_ushort * 4096)() - err_code = _sdk.CameraGetCustomLut(hCamera, iChannel, pLutNative) - SetLastError(err_code) - return pLutNative[:] - -def CameraGetCurrentLut(hCamera, iChannel): - pLutNative = (c_ushort * 4096)() - err_code = _sdk.CameraGetCurrentLut(hCamera, iChannel, pLutNative) - SetLastError(err_code) - return pLutNative[:] - -def CameraSetWbMode(hCamera, bAuto): - err_code = _sdk.CameraSetWbMode(hCamera, bAuto) - SetLastError(err_code) - return err_code - -def CameraGetWbMode(hCamera): - pbAuto = c_int() - err_code = _sdk.CameraGetWbMode(hCamera, byref(pbAuto) ) - SetLastError(err_code) - return pbAuto.value - -def CameraSetPresetClrTemp(hCamera, iSel): - err_code = _sdk.CameraSetPresetClrTemp(hCamera, iSel) - SetLastError(err_code) - return err_code - -def CameraGetPresetClrTemp(hCamera): - piSel = c_int() - err_code = _sdk.CameraGetPresetClrTemp(hCamera, byref(piSel) ) - SetLastError(err_code) - return piSel.value - -def CameraSetUserClrTempGain(hCamera, iRgain, iGgain, iBgain): - err_code = _sdk.CameraSetUserClrTempGain(hCamera, iRgain, iGgain, iBgain) - SetLastError(err_code) - return err_code - -def CameraGetUserClrTempGain(hCamera): - piRgain = c_int() - piGgain = c_int() - piBgain = c_int() - err_code = _sdk.CameraGetUserClrTempGain(hCamera, byref(piRgain), byref(piGgain), byref(piBgain) ) - SetLastError(err_code) - return (piRgain.value, piGgain.value, piBgain.value) - -def CameraSetUserClrTempMatrix(hCamera, pMatrix): - pMatrixNative = (c_float * 9)(*pMatrix) - err_code = _sdk.CameraSetUserClrTempMatrix(hCamera, pMatrixNative) - SetLastError(err_code) - return err_code - -def CameraGetUserClrTempMatrix(hCamera): - pMatrixNative = (c_float * 9)() - err_code = _sdk.CameraGetUserClrTempMatrix(hCamera, pMatrixNative) - SetLastError(err_code) - return pMatrixNative[:] - -def CameraSetClrTempMode(hCamera, iMode): - err_code = _sdk.CameraSetClrTempMode(hCamera, iMode) - SetLastError(err_code) - return err_code - -def CameraGetClrTempMode(hCamera): - piMode = c_int() - err_code = _sdk.CameraGetClrTempMode(hCamera, byref(piMode) ) - SetLastError(err_code) - return piMode.value - -def CameraSetOnceWB(hCamera): - err_code = _sdk.CameraSetOnceWB(hCamera) - SetLastError(err_code) - return err_code - -def CameraSetOnceBB(hCamera): - err_code = _sdk.CameraSetOnceBB(hCamera) - SetLastError(err_code) - return err_code - -def CameraSetAeTarget(hCamera, iAeTarget): - err_code = _sdk.CameraSetAeTarget(hCamera, iAeTarget) - SetLastError(err_code) - return err_code - -def CameraGetAeTarget(hCamera): - piAeTarget = c_int() - err_code = _sdk.CameraGetAeTarget(hCamera, byref(piAeTarget) ) - SetLastError(err_code) - return piAeTarget.value - -def CameraSetAeExposureRange(hCamera, fMinExposureTime, fMaxExposureTime): - err_code = _sdk.CameraSetAeExposureRange(hCamera, c_double(fMinExposureTime), c_double(fMaxExposureTime) ) - SetLastError(err_code) - return err_code - -def CameraGetAeExposureRange(hCamera): - fMinExposureTime = c_double() - fMaxExposureTime = c_double() - err_code = _sdk.CameraGetAeExposureRange(hCamera, byref(fMinExposureTime), byref(fMaxExposureTime) ) - SetLastError(err_code) - return (fMinExposureTime.value, fMaxExposureTime.value) - -def CameraSetAeAnalogGainRange(hCamera, iMinAnalogGain, iMaxAnalogGain): - err_code = _sdk.CameraSetAeAnalogGainRange(hCamera, iMinAnalogGain, iMaxAnalogGain) - SetLastError(err_code) - return err_code - -def CameraGetAeAnalogGainRange(hCamera): - iMinAnalogGain = c_int() - iMaxAnalogGain = c_int() - err_code = _sdk.CameraGetAeAnalogGainRange(hCamera, byref(iMinAnalogGain), byref(iMaxAnalogGain) ) - SetLastError(err_code) - return (iMinAnalogGain.value, iMaxAnalogGain.value) - -def CameraSetAeThreshold(hCamera, iThreshold): - err_code = _sdk.CameraSetAeThreshold(hCamera, iThreshold) - SetLastError(err_code) - return err_code - -def CameraGetAeThreshold(hCamera): - iThreshold = c_int() - err_code = _sdk.CameraGetAeThreshold(hCamera, byref(iThreshold)) - SetLastError(err_code) - return iThreshold.value - -def CameraSetExposureTime(hCamera, fExposureTime): - err_code = _sdk.CameraSetExposureTime(hCamera, c_double(fExposureTime) ) - SetLastError(err_code) - return err_code - -def CameraGetExposureLineTime(hCamera): - pfLineTime = c_double() - err_code = _sdk.CameraGetExposureLineTime(hCamera, byref(pfLineTime)) - SetLastError(err_code) - return pfLineTime.value - -def CameraGetExposureTime(hCamera): - pfExposureTime = c_double() - err_code = _sdk.CameraGetExposureTime(hCamera, byref(pfExposureTime)) - SetLastError(err_code) - return pfExposureTime.value - -def CameraGetExposureTimeRange(hCamera): - pfMin = c_double() - pfMax = c_double() - pfStep = c_double() - err_code = _sdk.CameraGetExposureTimeRange(hCamera, byref(pfMin), byref(pfMax), byref(pfStep)) - SetLastError(err_code) - return (pfMin.value, pfMax.value, pfStep.value) - -def CameraSetAnalogGain(hCamera, iAnalogGain): - err_code = _sdk.CameraSetAnalogGain(hCamera, iAnalogGain) - SetLastError(err_code) - return err_code - -def CameraGetAnalogGain(hCamera): - piAnalogGain = c_int() - err_code = _sdk.CameraGetAnalogGain(hCamera, byref(piAnalogGain)) - SetLastError(err_code) - return piAnalogGain.value - -def CameraSetGain(hCamera, iRGain, iGGain, iBGain): - err_code = _sdk.CameraSetGain(hCamera, iRGain, iGGain, iBGain) - SetLastError(err_code) - return err_code - -def CameraGetGain(hCamera): - piRGain = c_int() - piGGain = c_int() - piBGain = c_int() - err_code = _sdk.CameraGetGain(hCamera, byref(piRGain), byref(piGGain), byref(piBGain)) - SetLastError(err_code) - return (piRGain.value, piGGain.value, piBGain.value) - -def CameraSetGamma(hCamera, iGamma): - err_code = _sdk.CameraSetGamma(hCamera, iGamma) - SetLastError(err_code) - return err_code - -def CameraGetGamma(hCamera): - piGamma = c_int() - err_code = _sdk.CameraGetGamma(hCamera, byref(piGamma)) - SetLastError(err_code) - return piGamma.value - -def CameraSetContrast(hCamera, iContrast): - err_code = _sdk.CameraSetContrast(hCamera, iContrast) - SetLastError(err_code) - return err_code - -def CameraGetContrast(hCamera): - piContrast = c_int() - err_code = _sdk.CameraGetContrast(hCamera, byref(piContrast)) - SetLastError(err_code) - return piContrast.value - -def CameraSetSaturation(hCamera, iSaturation): - err_code = _sdk.CameraSetSaturation(hCamera, iSaturation) - SetLastError(err_code) - return err_code - -def CameraGetSaturation(hCamera): - piSaturation = c_int() - err_code = _sdk.CameraGetSaturation(hCamera, byref(piSaturation)) - SetLastError(err_code) - return piSaturation.value - -def CameraSetMonochrome(hCamera, bEnable): - err_code = _sdk.CameraSetMonochrome(hCamera, bEnable) - SetLastError(err_code) - return err_code - -def CameraGetMonochrome(hCamera): - pbEnable = c_int() - err_code = _sdk.CameraGetMonochrome(hCamera, byref(pbEnable)) - SetLastError(err_code) - return pbEnable.value - -def CameraSetInverse(hCamera, bEnable): - err_code = _sdk.CameraSetInverse(hCamera, bEnable) - SetLastError(err_code) - return err_code - -def CameraGetInverse(hCamera): - pbEnable = c_int() - err_code = _sdk.CameraGetInverse(hCamera, byref(pbEnable)) - SetLastError(err_code) - return pbEnable.value - -def CameraSetAntiFlick(hCamera, bEnable): - err_code = _sdk.CameraSetAntiFlick(hCamera, bEnable) - SetLastError(err_code) - return err_code - -def CameraGetAntiFlick(hCamera): - pbEnable = c_int() - err_code = _sdk.CameraGetAntiFlick(hCamera, byref(pbEnable)) - SetLastError(err_code) - return pbEnable.value - -def CameraGetLightFrequency(hCamera): - piFrequencySel = c_int() - err_code = _sdk.CameraGetLightFrequency(hCamera, byref(piFrequencySel)) - SetLastError(err_code) - return piFrequencySel.value - -def CameraSetLightFrequency(hCamera, iFrequencySel): - err_code = _sdk.CameraSetLightFrequency(hCamera, iFrequencySel) - SetLastError(err_code) - return err_code - -def CameraSetFrameSpeed(hCamera, iFrameSpeed): - err_code = _sdk.CameraSetFrameSpeed(hCamera, iFrameSpeed) - SetLastError(err_code) - return err_code - -def CameraGetFrameSpeed(hCamera): - piFrameSpeed = c_int() - err_code = _sdk.CameraGetFrameSpeed(hCamera, byref(piFrameSpeed)) - SetLastError(err_code) - return piFrameSpeed.value - -def CameraSetParameterMode(hCamera, iMode): - err_code = _sdk.CameraSetParameterMode(hCamera, iMode) - SetLastError(err_code) - return err_code - -def CameraGetParameterMode(hCamera): - piTarget = c_int() - err_code = _sdk.CameraGetParameterMode(hCamera, byref(piTarget)) - SetLastError(err_code) - return piTarget.value - -def CameraSetParameterMask(hCamera, uMask): - err_code = _sdk.CameraSetParameterMask(hCamera, uMask) - SetLastError(err_code) - return err_code - -def CameraSaveParameter(hCamera, iTeam): - err_code = _sdk.CameraSaveParameter(hCamera, iTeam) - SetLastError(err_code) - return err_code - -def CameraSaveParameterToFile(hCamera, sFileName): - err_code = _sdk.CameraSaveParameterToFile(hCamera, _str_to_string_buffer(sFileName)) - SetLastError(err_code) - return err_code - -def CameraReadParameterFromFile(hCamera, sFileName): - err_code = _sdk.CameraReadParameterFromFile(hCamera, _str_to_string_buffer(sFileName)) - SetLastError(err_code) - return err_code - -def CameraLoadParameter(hCamera, iTeam): - err_code = _sdk.CameraLoadParameter(hCamera, iTeam) - SetLastError(err_code) - return err_code - -def CameraGetCurrentParameterGroup(hCamera): - piTeam = c_int() - err_code = _sdk.CameraGetCurrentParameterGroup(hCamera, byref(piTeam)) - SetLastError(err_code) - return piTeam.value - -def CameraSetTransPackLen(hCamera, iPackSel): - err_code = _sdk.CameraSetTransPackLen(hCamera, iPackSel) - SetLastError(err_code) - return err_code - -def CameraGetTransPackLen(hCamera): - piPackSel = c_int() - err_code = _sdk.CameraGetTransPackLen(hCamera, byref(piPackSel)) - SetLastError(err_code) - return piPackSel.value - -def CameraIsAeWinVisible(hCamera): - pbIsVisible = c_int() - err_code = _sdk.CameraIsAeWinVisible(hCamera, byref(pbIsVisible)) - SetLastError(err_code) - return pbIsVisible.value - -def CameraSetAeWinVisible(hCamera, bIsVisible): - err_code = _sdk.CameraSetAeWinVisible(hCamera, bIsVisible) - SetLastError(err_code) - return err_code - -def CameraGetAeWindow(hCamera): - piHOff = c_int() - piVOff = c_int() - piWidth = c_int() - piHeight = c_int() - err_code = _sdk.CameraGetAeWindow(hCamera, byref(piHOff), byref(piVOff), byref(piWidth), byref(piHeight)) - SetLastError(err_code) - return (piHOff.value, piVOff.value, piWidth.value, piHeight.value) - -def CameraSetAeWindow(hCamera, iHOff, iVOff, iWidth, iHeight): - err_code = _sdk.CameraSetAeWindow(hCamera, iHOff, iVOff, iWidth, iHeight) - SetLastError(err_code) - return err_code - -def CameraSetMirror(hCamera, iDir, bEnable): - err_code = _sdk.CameraSetMirror(hCamera, iDir, bEnable) - SetLastError(err_code) - return err_code - -def CameraGetMirror(hCamera, iDir): - pbEnable = c_int() - err_code = _sdk.CameraGetMirror(hCamera, iDir, byref(pbEnable)) - SetLastError(err_code) - return pbEnable.value - -def CameraSetRotate(hCamera, iRot): - err_code = _sdk.CameraSetRotate(hCamera, iRot) - SetLastError(err_code) - return err_code - -def CameraGetRotate(hCamera): - iRot = c_int() - err_code = _sdk.CameraGetRotate(hCamera, byref(iRot)) - SetLastError(err_code) - return iRot.value - -def CameraGetWbWindow(hCamera): - PiHOff = c_int() - PiVOff = c_int() - PiWidth = c_int() - PiHeight = c_int() - err_code = _sdk.CameraGetWbWindow(hCamera, byref(PiHOff), byref(PiVOff), byref(PiWidth), byref(PiHeight)) - SetLastError(err_code) - return (PiHOff.value, PiVOff.value, PiWidth.value, PiHeight.value) - -def CameraSetWbWindow(hCamera, iHOff, iVOff, iWidth, iHeight): - err_code = _sdk.CameraSetWbWindow(hCamera, iHOff, iVOff, iWidth, iHeight) - SetLastError(err_code) - return err_code - -def CameraIsWbWinVisible(hCamera): - pbShow = c_int() - err_code = _sdk.CameraIsWbWinVisible(hCamera, byref(pbShow)) - SetLastError(err_code) - return pbShow.value - -def CameraSetWbWinVisible(hCamera, bShow): - err_code = _sdk.CameraSetWbWinVisible(hCamera, bShow) - SetLastError(err_code) - return err_code - -def CameraImageOverlay(hCamera, pRgbBuffer, pFrInfo): - err_code = _sdk.CameraImageOverlay(hCamera, c_void_p(pRgbBuffer), byref(pFrInfo)) - SetLastError(err_code) - return err_code - -def CameraSetCrossLine(hCamera, iLine, x, y, uColor, bVisible): - err_code = _sdk.CameraSetCrossLine(hCamera, iLine, x, y, uColor, bVisible) - SetLastError(err_code) - return err_code - -def CameraGetCrossLine(hCamera, iLine): - px = c_int() - py = c_int() - pcolor = c_uint() - pbVisible = c_int() - err_code = _sdk.CameraGetCrossLine(hCamera, iLine, byref(px), byref(py), byref(pcolor), byref(pbVisible)) - SetLastError(err_code) - return (px.value, py.value, pcolor.value, pbVisible.value) - -def CameraGetCapability(hCamera): - pCameraInfo = tSdkCameraCapbility() - err_code = _sdk.CameraGetCapability(hCamera, byref(pCameraInfo)) - SetLastError(err_code) - return pCameraInfo - -def CameraWriteSN(hCamera, pbySN, iLevel): - err_code = _sdk.CameraWriteSN(hCamera, _str_to_string_buffer(pbySN), iLevel) - SetLastError(err_code) - return err_code - -def CameraReadSN(hCamera, iLevel): - pbySN = create_string_buffer(64) - err_code = _sdk.CameraReadSN(hCamera, pbySN, iLevel) - SetLastError(err_code) - return _string_buffer_to_str(pbySN) - -def CameraSetTriggerDelayTime(hCamera, uDelayTimeUs): - err_code = _sdk.CameraSetTriggerDelayTime(hCamera, uDelayTimeUs) - SetLastError(err_code) - return err_code - -def CameraGetTriggerDelayTime(hCamera): - puDelayTimeUs = c_uint() - err_code = _sdk.CameraGetTriggerDelayTime(hCamera, byref(puDelayTimeUs)) - SetLastError(err_code) - return puDelayTimeUs.value - -def CameraSetTriggerCount(hCamera, iCount): - err_code = _sdk.CameraSetTriggerCount(hCamera, iCount) - SetLastError(err_code) - return err_code - -def CameraGetTriggerCount(hCamera): - piCount = c_int() - err_code = _sdk.CameraGetTriggerCount(hCamera, byref(piCount)) - SetLastError(err_code) - return piCount.value - -def CameraSoftTrigger(hCamera): - err_code = _sdk.CameraSoftTrigger(hCamera) - SetLastError(err_code) - return err_code - -def CameraSetTriggerMode(hCamera, iModeSel): - err_code = _sdk.CameraSetTriggerMode(hCamera, iModeSel) - SetLastError(err_code) - return err_code - -def CameraGetTriggerMode(hCamera): - piModeSel = c_int() - err_code = _sdk.CameraGetTriggerMode(hCamera, byref(piModeSel)) - SetLastError(err_code) - return piModeSel.value - -def CameraSetStrobeMode(hCamera, iMode): - err_code = _sdk.CameraSetStrobeMode(hCamera, iMode) - SetLastError(err_code) - return err_code - -def CameraGetStrobeMode(hCamera): - piMode = c_int() - err_code = _sdk.CameraGetStrobeMode(hCamera, byref(piMode)) - SetLastError(err_code) - return piMode.value - -def CameraSetStrobeDelayTime(hCamera, uDelayTimeUs): - err_code = _sdk.CameraSetStrobeDelayTime(hCamera, uDelayTimeUs) - SetLastError(err_code) - return err_code - -def CameraGetStrobeDelayTime(hCamera): - upDelayTimeUs = c_uint() - err_code = _sdk.CameraGetStrobeDelayTime(hCamera, byref(upDelayTimeUs)) - SetLastError(err_code) - return upDelayTimeUs.value - -def CameraSetStrobePulseWidth(hCamera, uTimeUs): - err_code = _sdk.CameraSetStrobePulseWidth(hCamera, uTimeUs) - SetLastError(err_code) - return err_code - -def CameraGetStrobePulseWidth(hCamera): - upTimeUs = c_uint() - err_code = _sdk.CameraGetStrobePulseWidth(hCamera, byref(upTimeUs)) - SetLastError(err_code) - return upTimeUs.value - -def CameraSetStrobePolarity(hCamera, uPolarity): - err_code = _sdk.CameraSetStrobePolarity(hCamera, uPolarity) - SetLastError(err_code) - return err_code - -def CameraGetStrobePolarity(hCamera): - upPolarity = c_uint() - err_code = _sdk.CameraGetStrobePolarity(hCamera, byref(upPolarity)) - SetLastError(err_code) - return upPolarity.value - -def CameraSetExtTrigSignalType(hCamera, iType): - err_code = _sdk.CameraSetExtTrigSignalType(hCamera, iType) - SetLastError(err_code) - return err_code - -def CameraGetExtTrigSignalType(hCamera): - ipType = c_int() - err_code = _sdk.CameraGetExtTrigSignalType(hCamera, byref(ipType)) - SetLastError(err_code) - return ipType.value - -def CameraSetExtTrigShutterType(hCamera, iType): - err_code = _sdk.CameraSetExtTrigShutterType(hCamera, iType) - SetLastError(err_code) - return err_code - -def CameraGetExtTrigShutterType(hCamera): - ipType = c_int() - err_code = _sdk.CameraGetExtTrigShutterType(hCamera, byref(ipType)) - SetLastError(err_code) - return ipType.value - -def CameraSetExtTrigDelayTime(hCamera, uDelayTimeUs): - err_code = _sdk.CameraSetExtTrigDelayTime(hCamera, uDelayTimeUs) - SetLastError(err_code) - return err_code - -def CameraGetExtTrigDelayTime(hCamera): - upDelayTimeUs = c_uint() - err_code = _sdk.CameraGetExtTrigDelayTime(hCamera, byref(upDelayTimeUs)) - SetLastError(err_code) - return upDelayTimeUs.value - -def CameraSetExtTrigJitterTime(hCamera, uTimeUs): - err_code = _sdk.CameraSetExtTrigJitterTime(hCamera, uTimeUs) - SetLastError(err_code) - return err_code - -def CameraGetExtTrigJitterTime(hCamera): - upTimeUs = c_uint() - err_code = _sdk.CameraGetExtTrigJitterTime(hCamera, byref(upTimeUs)) - SetLastError(err_code) - return upTimeUs.value - -def CameraGetExtTrigCapability(hCamera): - puCapabilityMask = c_uint() - err_code = _sdk.CameraGetExtTrigCapability(hCamera, byref(puCapabilityMask)) - SetLastError(err_code) - return puCapabilityMask.value - -def CameraPauseLevelTrigger(hCamera): - err_code = _sdk.CameraPauseLevelTrigger(hCamera) - SetLastError(err_code) - return err_code - -def CameraGetResolutionForSnap(hCamera): - pImageResolution = tSdkImageResolution() - err_code = _sdk.CameraGetResolutionForSnap(hCamera, byref(pImageResolution)) - SetLastError(err_code) - return pImageResolution - -def CameraSetResolutionForSnap(hCamera, pImageResolution): - err_code = _sdk.CameraSetResolutionForSnap(hCamera, byref(pImageResolution)) - SetLastError(err_code) - return err_code - -def CameraCustomizeResolution(hCamera): - pImageCustom = tSdkImageResolution() - err_code = _sdk.CameraCustomizeResolution(hCamera, byref(pImageCustom)) - SetLastError(err_code) - return pImageCustom - -def CameraCustomizeReferWin(hCamera, iWinType, hParent): - piHOff = c_int() - piVOff = c_int() - piWidth = c_int() - piHeight = c_int() - err_code = _sdk.CameraCustomizeReferWin(hCamera, iWinType, hParent, byref(piHOff), byref(piVOff), byref(piWidth), byref(piHeight)) - SetLastError(err_code) - return (piHOff.value, piVOff.value, piWidth.value, piHeight.value) - -def CameraShowSettingPage(hCamera, bShow): - err_code = _sdk.CameraShowSettingPage(hCamera, bShow) - SetLastError(err_code) - return err_code - -def CameraCreateSettingPage(hCamera, hParent, pWinText, pCallbackFunc = None, pCallbackCtx = 0, uReserved = 0): - err_code = _sdk.CameraCreateSettingPage(hCamera, hParent, _str_to_string_buffer(pWinText), pCallbackFunc, c_void_p(pCallbackCtx), uReserved) - SetLastError(err_code) - return err_code - -def CameraCreateSettingPageEx(hCamera): - err_code = _sdk.CameraCreateSettingPageEx(hCamera) - SetLastError(err_code) - return err_code - -def CameraSetActiveSettingSubPage(hCamera, index): - err_code = _sdk.CameraSetActiveSettingSubPage(hCamera, index) - SetLastError(err_code) - return err_code - -def CameraSetSettingPageParent(hCamera, hParentWnd, Flags): - err_code = _sdk.CameraSetSettingPageParent(hCamera, hParentWnd, Flags) - SetLastError(err_code) - return err_code - -def CameraGetSettingPageHWnd(hCamera): - hWnd = c_void_p() - err_code = _sdk.CameraGetSettingPageHWnd(hCamera, byref(hWnd)) - SetLastError(err_code) - return hWnd.value - -def CameraSpecialControl(hCamera, dwCtrlCode, dwParam, lpData): - err_code = _sdk.CameraSpecialControl(hCamera, dwCtrlCode, dwParam, c_void_p(lpData) ) - SetLastError(err_code) - return err_code - -def CameraGetFrameStatistic(hCamera): - psFrameStatistic = tSdkFrameStatistic() - err_code = _sdk.CameraGetFrameStatistic(hCamera, byref(psFrameStatistic)) - SetLastError(err_code) - return psFrameStatistic - -def CameraSetNoiseFilter(hCamera, bEnable): - err_code = _sdk.CameraSetNoiseFilter(hCamera, bEnable) - SetLastError(err_code) - return err_code - -def CameraGetNoiseFilterState(hCamera): - pEnable = c_int() - err_code = _sdk.CameraGetNoiseFilterState(hCamera, byref(pEnable)) - SetLastError(err_code) - return pEnable.value - -def CameraRstTimeStamp(hCamera): - err_code = _sdk.CameraRstTimeStamp(hCamera) - SetLastError(err_code) - return err_code - -def CameraSaveUserData(hCamera, uStartAddr, pbData): - err_code = _sdk.CameraSaveUserData(hCamera, uStartAddr, pbData, len(pbData)) - SetLastError(err_code) - return err_code - -def CameraLoadUserData(hCamera, uStartAddr, ilen): - pbData = create_string_buffer(ilen) - err_code = _sdk.CameraLoadUserData(hCamera, uStartAddr, pbData, ilen) - SetLastError(err_code) - return pbData[:] - -def CameraGetFriendlyName(hCamera): - pName = create_string_buffer(64) - err_code = _sdk.CameraGetFriendlyName(hCamera, pName) - SetLastError(err_code) - return _string_buffer_to_str(pName) - -def CameraSetFriendlyName(hCamera, pName): - pNameBuf = _str_to_string_buffer(pName) - resize(pNameBuf, 64) - err_code = _sdk.CameraSetFriendlyName(hCamera, pNameBuf) - SetLastError(err_code) - return err_code - -def CameraSdkGetVersionString(): - pVersionString = create_string_buffer(64) - err_code = _sdk.CameraSdkGetVersionString(pVersionString) - SetLastError(err_code) - return _string_buffer_to_str(pVersionString) - -def CameraCheckFwUpdate(hCamera): - pNeedUpdate = c_int() - err_code = _sdk.CameraCheckFwUpdate(hCamera, byref(pNeedUpdate)) - SetLastError(err_code) - return pNeedUpdate.value - -def CameraGetFirmwareVersion(hCamera): - pVersion = create_string_buffer(64) - err_code = _sdk.CameraGetFirmwareVersion(hCamera, pVersion) - SetLastError(err_code) - return _string_buffer_to_str(pVersion) - -def CameraGetEnumInfo(hCamera): - pCameraInfo = tSdkCameraDevInfo() - err_code = _sdk.CameraGetEnumInfo(hCamera, byref(pCameraInfo)) - SetLastError(err_code) - return pCameraInfo - -def CameraGetInerfaceVersion(hCamera): - pVersion = create_string_buffer(64) - err_code = _sdk.CameraGetInerfaceVersion(hCamera, pVersion) - SetLastError(err_code) - return _string_buffer_to_str(pVersion) - -def CameraSetIOState(hCamera, iOutputIOIndex, uState): - err_code = _sdk.CameraSetIOState(hCamera, iOutputIOIndex, uState) - SetLastError(err_code) - return err_code - -def CameraGetIOState(hCamera, iInputIOIndex): - puState = c_int() - err_code = _sdk.CameraGetIOState(hCamera, iInputIOIndex, byref(puState)) - SetLastError(err_code) - return puState.value - -def CameraSetInPutIOMode(hCamera, iInputIOIndex, iMode): - err_code = _sdk.CameraSetInPutIOMode(hCamera, iInputIOIndex, iMode) - SetLastError(err_code) - return err_code - -def CameraSetOutPutIOMode(hCamera, iOutputIOIndex, iMode): - err_code = _sdk.CameraSetOutPutIOMode(hCamera, iOutputIOIndex, iMode) - SetLastError(err_code) - return err_code - -def CameraSetOutPutPWM(hCamera, iOutputIOIndex, iCycle, uDuty): - err_code = _sdk.CameraSetOutPutPWM(hCamera, iOutputIOIndex, iCycle, uDuty) - SetLastError(err_code) - return err_code - -def CameraSetAeAlgorithm(hCamera, iIspProcessor, iAeAlgorithmSel): - err_code = _sdk.CameraSetAeAlgorithm(hCamera, iIspProcessor, iAeAlgorithmSel) - SetLastError(err_code) - return err_code - -def CameraGetAeAlgorithm(hCamera, iIspProcessor): - piAlgorithmSel = c_int() - err_code = _sdk.CameraGetAeAlgorithm(hCamera, iIspProcessor, byref(piAlgorithmSel)) - SetLastError(err_code) - return piAlgorithmSel.value - -def CameraSetBayerDecAlgorithm(hCamera, iIspProcessor, iAlgorithmSel): - err_code = _sdk.CameraSetBayerDecAlgorithm(hCamera, iIspProcessor, iAlgorithmSel) - SetLastError(err_code) - return err_code - -def CameraGetBayerDecAlgorithm(hCamera, iIspProcessor): - piAlgorithmSel = c_int() - err_code = _sdk.CameraGetBayerDecAlgorithm(hCamera, iIspProcessor, byref(piAlgorithmSel)) - SetLastError(err_code) - return piAlgorithmSel.value - -def CameraSetIspProcessor(hCamera, iIspProcessor): - err_code = _sdk.CameraSetIspProcessor(hCamera, iIspProcessor) - SetLastError(err_code) - return err_code - -def CameraGetIspProcessor(hCamera): - piIspProcessor = c_int() - err_code = _sdk.CameraGetIspProcessor(hCamera, byref(piIspProcessor)) - SetLastError(err_code) - return piIspProcessor.value - -def CameraSetBlackLevel(hCamera, iBlackLevel): - err_code = _sdk.CameraSetBlackLevel(hCamera, iBlackLevel) - SetLastError(err_code) - return err_code - -def CameraGetBlackLevel(hCamera): - piBlackLevel = c_int() - err_code = _sdk.CameraGetBlackLevel(hCamera, byref(piBlackLevel)) - SetLastError(err_code) - return piBlackLevel.value - -def CameraSetWhiteLevel(hCamera, iWhiteLevel): - err_code = _sdk.CameraSetWhiteLevel(hCamera, iWhiteLevel) - SetLastError(err_code) - return err_code - -def CameraGetWhiteLevel(hCamera): - piWhiteLevel = c_int() - err_code = _sdk.CameraGetWhiteLevel(hCamera, byref(piWhiteLevel)) - SetLastError(err_code) - return piWhiteLevel.value - -def CameraSetIspOutFormat(hCamera, uFormat): - err_code = _sdk.CameraSetIspOutFormat(hCamera, uFormat) - SetLastError(err_code) - return err_code - -def CameraGetIspOutFormat(hCamera): - puFormat = c_int() - err_code = _sdk.CameraGetIspOutFormat(hCamera, byref(puFormat)) - SetLastError(err_code) - return puFormat.value - -def CameraGetErrorString(iStatusCode): - _sdk.CameraGetErrorString.restype = c_char_p - msg = _sdk.CameraGetErrorString(iStatusCode) - if msg: - return _string_buffer_to_str(msg) - else: - return '' - -def CameraGetImageBufferEx2(hCamera, pImageData, uOutFormat, wTimes): - piWidth = c_int() - piHeight = c_int() - err_code = _sdk.CameraGetImageBufferEx2(hCamera, c_void_p(pImageData), uOutFormat, byref(piWidth), byref(piHeight), wTimes) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return (piWidth.value, piHeight.value) - -def CameraGetImageBufferEx3(hCamera, pImageData, uOutFormat, wTimes): - piWidth = c_int() - piHeight = c_int() - puTimeStamp = c_int() - err_code = _sdk.CameraGetImageBufferEx3(hCamera, c_void_p(pImageData), uOutFormat, byref(piWidth), byref(piHeight), byref(puTimeStamp), wTimes) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return (piWidth.value, piHeight.value, puTimeStamp.value) - -def CameraGetCapabilityEx2(hCamera): - pMaxWidth = c_int() - pMaxHeight = c_int() - pbColorCamera = c_int() - err_code = _sdk.CameraGetCapabilityEx2(hCamera, byref(pMaxWidth), byref(pMaxHeight), byref(pbColorCamera)) - SetLastError(err_code) - return (pMaxWidth.value, pMaxHeight.value, pbColorCamera.value) - -def CameraReConnect(hCamera): - err_code = _sdk.CameraReConnect(hCamera) - SetLastError(err_code) - return err_code - -def CameraConnectTest(hCamera): - err_code = _sdk.CameraConnectTest(hCamera) - SetLastError(err_code) - return err_code - -def CameraSetLedEnable(hCamera, index, enable): - err_code = _sdk.CameraSetLedEnable(hCamera, index, enable) - SetLastError(err_code) - return err_code - -def CameraGetLedEnable(hCamera, index): - enable = c_int() - err_code = _sdk.CameraGetLedEnable(hCamera, index, byref(enable)) - SetLastError(err_code) - return enable.value - -def CameraSetLedOnOff(hCamera, index, onoff): - err_code = _sdk.CameraSetLedOnOff(hCamera, index, onoff) - SetLastError(err_code) - return err_code - -def CameraGetLedOnOff(hCamera, index): - onoff = c_int() - err_code = _sdk.CameraGetLedOnOff(hCamera, index, byref(onoff)) - SetLastError(err_code) - return onoff.value - -def CameraSetLedDuration(hCamera, index, duration): - err_code = _sdk.CameraSetLedDuration(hCamera, index, duration) - SetLastError(err_code) - return err_code - -def CameraGetLedDuration(hCamera, index): - duration = c_uint() - err_code = _sdk.CameraGetLedDuration(hCamera, index, byref(duration)) - SetLastError(err_code) - return duration.value - -def CameraSetLedBrightness(hCamera, index, uBrightness): - err_code = _sdk.CameraSetLedBrightness(hCamera, index, uBrightness) - SetLastError(err_code) - return err_code - -def CameraGetLedBrightness(hCamera, index): - uBrightness = c_uint() - err_code = _sdk.CameraGetLedBrightness(hCamera, index, byref(uBrightness)) - SetLastError(err_code) - return uBrightness.value - -def CameraEnableTransferRoi(hCamera, uEnableMask): - err_code = _sdk.CameraEnableTransferRoi(hCamera, uEnableMask) - SetLastError(err_code) - return err_code - -def CameraSetTransferRoi(hCamera, index, X1, Y1, X2, Y2): - err_code = _sdk.CameraSetTransferRoi(hCamera, index, X1, Y1, X2, Y2) - SetLastError(err_code) - return err_code - -def CameraGetTransferRoi(hCamera, index): - pX1 = c_uint() - pY1 = c_uint() - pX2 = c_uint() - pY2 = c_uint() - err_code = _sdk.CameraGetTransferRoi(hCamera, index, byref(pX1), byref(pY1), byref(pX2), byref(pY2)) - SetLastError(err_code) - return (pX1.value, pY1.value, pX2.value, pY2.value) - -def CameraAlignMalloc(size, align = 16): - _sdk.CameraAlignMalloc.restype = c_void_p - r = _sdk.CameraAlignMalloc(size, align) - return r - -def CameraAlignFree(membuffer): - _sdk.CameraAlignFree(c_void_p(membuffer)) - -def CameraSetAutoConnect(hCamera, bEnable): - err_code = _sdk.CameraSetAutoConnect(hCamera, bEnable) - SetLastError(err_code) - return err_code - -def CameraGetAutoConnect(hCamera): - pbEnable = c_int() - err_code = _sdk.CameraGetAutoConnect(hCamera, byref(pbEnable)) - SetLastError(err_code) - return pbEnable.value - -def CameraGetReConnectCounts(hCamera): - puCounts = c_int() - err_code = _sdk.CameraGetReConnectCounts(hCamera, byref(puCounts)) - SetLastError(err_code) - return puCounts.value - -def CameraSetSingleGrabMode(hCamera, bEnable): - err_code = _sdk.CameraSetSingleGrabMode(hCamera, bEnable) - SetLastError(err_code) - return err_code - -def CameraGetSingleGrabMode(hCamera): - pbEnable = c_int() - err_code = _sdk.CameraGetSingleGrabMode(hCamera, byref(pbEnable)) - SetLastError(err_code) - return pbEnable.value - -def CameraRestartGrab(hCamera): - err_code = _sdk.CameraRestartGrab(hCamera) - SetLastError(err_code) - return err_code - -def CameraEvaluateImageDefinition(hCamera, iAlgorithSel, pbyIn, pFrInfo): - DefinitionValue = c_double() - err_code = _sdk.CameraEvaluateImageDefinition(hCamera, iAlgorithSel, c_void_p(pbyIn), byref(pFrInfo), byref(DefinitionValue)) - SetLastError(err_code) - return DefinitionValue.value - -def CameraDrawText(pRgbBuffer, pFrInfo, pFontFileName, FontWidth, FontHeight, pText, Left, Top, Width, Height, TextColor, uFlags): - err_code = _sdk.CameraDrawText(c_void_p(pRgbBuffer), byref(pFrInfo), _str_to_string_buffer(pFontFileName), FontWidth, FontHeight, _str_to_string_buffer(pText), Left, Top, Width, Height, TextColor, uFlags) - SetLastError(err_code) - return err_code - -def CameraGigeGetIp(pCameraInfo): - CamIp = create_string_buffer(32) - CamMask = create_string_buffer(32) - CamGateWay = create_string_buffer(32) - EtIp = create_string_buffer(32) - EtMask = create_string_buffer(32) - EtGateWay = create_string_buffer(32) - err_code = _sdk.CameraGigeGetIp(byref(pCameraInfo), CamIp, CamMask, CamGateWay, EtIp, EtMask, EtGateWay) - SetLastError(err_code) - return (_string_buffer_to_str(CamIp), _string_buffer_to_str(CamMask), _string_buffer_to_str(CamGateWay), - _string_buffer_to_str(EtIp), _string_buffer_to_str(EtMask), _string_buffer_to_str(EtGateWay) ) - -def CameraGigeSetIp(pCameraInfo, Ip, SubMask, GateWay, bPersistent): - err_code = _sdk.CameraGigeSetIp(byref(pCameraInfo), - _str_to_string_buffer(Ip), _str_to_string_buffer(SubMask), _str_to_string_buffer(GateWay), bPersistent) - SetLastError(err_code) - return err_code - -def CameraGigeGetMac(pCameraInfo): - CamMac = create_string_buffer(32) - EtMac = create_string_buffer(32) - err_code = _sdk.CameraGigeGetMac(byref(pCameraInfo), CamMac, EtMac) - SetLastError(err_code) - return (_string_buffer_to_str(CamMac), _string_buffer_to_str(EtMac) ) - -def CameraEnableFastResponse(hCamera): - err_code = _sdk.CameraEnableFastResponse(hCamera) - SetLastError(err_code) - return err_code - -def CameraSetCorrectDeadPixel(hCamera, bEnable): - err_code = _sdk.CameraSetCorrectDeadPixel(hCamera, bEnable) - SetLastError(err_code) - return err_code - -def CameraGetCorrectDeadPixel(hCamera): - pbEnable = c_int() - err_code = _sdk.CameraGetCorrectDeadPixel(hCamera, byref(pbEnable)) - SetLastError(err_code) - return pbEnable.value - -def CameraFlatFieldingCorrectSetEnable(hCamera, bEnable): - err_code = _sdk.CameraFlatFieldingCorrectSetEnable(hCamera, bEnable) - SetLastError(err_code) - return err_code - -def CameraFlatFieldingCorrectGetEnable(hCamera): - pbEnable = c_int() - err_code = _sdk.CameraFlatFieldingCorrectGetEnable(hCamera, byref(pbEnable)) - SetLastError(err_code) - return pbEnable.value - -def CameraFlatFieldingCorrectSetParameter(hCamera, pDarkFieldingImage, pDarkFieldingFrInfo, pLightFieldingImage, pLightFieldingFrInfo): - err_code = _sdk.CameraFlatFieldingCorrectSetParameter(hCamera, c_void_p(pDarkFieldingImage), byref(pDarkFieldingFrInfo), c_void_p(pLightFieldingImage), byref(pLightFieldingFrInfo)) - SetLastError(err_code) - return err_code - -def CameraFlatFieldingCorrectGetParameterState(hCamera): - pbValid = c_int() - pFilePath = create_string_buffer(1024) - err_code = _sdk.CameraFlatFieldingCorrectGetParameterState(hCamera, byref(pbValid), pFilePath) - SetLastError(err_code) - return (pbValid.value, _string_buffer_to_str(pFilePath) ) - -def CameraFlatFieldingCorrectSaveParameterToFile(hCamera, pszFileName): - err_code = _sdk.CameraFlatFieldingCorrectSaveParameterToFile(hCamera, _str_to_string_buffer(pszFileName)) - SetLastError(err_code) - return err_code - -def CameraFlatFieldingCorrectLoadParameterFromFile(hCamera, pszFileName): - err_code = _sdk.CameraFlatFieldingCorrectLoadParameterFromFile(hCamera, _str_to_string_buffer(pszFileName)) - SetLastError(err_code) - return err_code - -def CameraCommonCall(hCamera, pszCall, uResultBufSize): - pszResult = create_string_buffer(uResultBufSize) if uResultBufSize > 0 else None - err_code = _sdk.CameraCommonCall(hCamera, _str_to_string_buffer(pszCall), pszResult, uResultBufSize) - SetLastError(err_code) - return _string_buffer_to_str(pszResult) if pszResult else '' - -def CameraSetDenoise3DParams(hCamera, bEnable, nCount, Weights): - assert(nCount >= 2 and nCount <= 8) - if Weights: - assert(len(Weights) == nCount) - WeightsNative = (c_float * nCount)(*Weights) - else: - WeightsNative = None - err_code = _sdk.CameraSetDenoise3DParams(hCamera, bEnable, nCount, WeightsNative) - SetLastError(err_code) - return err_code - -def CameraGetDenoise3DParams(hCamera): - bEnable = c_int() - nCount = c_int() - bUseWeight = c_int() - Weights = (c_float * 8)() - err_code = _sdk.CameraGetDenoise3DParams(hCamera, byref(bEnable), byref(nCount), byref(bUseWeight), Weights) - SetLastError(err_code) - bEnable, nCount, bUseWeight = bEnable.value, nCount.value, bUseWeight.value - if bUseWeight: - Weights = Weights[:nCount] - else: - Weights = None - return (bEnable, nCount, bUseWeight, Weights) - -def CameraManualDenoise3D(InFramesHead, InFramesData, nCount, Weights, OutFrameHead, OutFrameData): - assert(nCount > 0) - assert(len(InFramesData) == nCount) - assert(Weights is None or len(Weights) == nCount) - InFramesDataNative = (c_void_p * nCount)(*InFramesData) - WeightsNative = (c_float * nCount)(*Weights) if Weights else None - err_code = _sdk.CameraManualDenoise3D(byref(InFramesHead), InFramesDataNative, nCount, WeightsNative, byref(OutFrameHead), c_void_p(OutFrameData)) - SetLastError(err_code) - return err_code - -def CameraCustomizeDeadPixels(hCamera, hParent): - err_code = _sdk.CameraCustomizeDeadPixels(hCamera, hParent) - SetLastError(err_code) - return err_code - -def CameraReadDeadPixels(hCamera): - pNumPixel = c_int() - err_code = _sdk.CameraReadDeadPixels(hCamera, None, None, byref(pNumPixel)) - SetLastError(err_code) - if pNumPixel.value < 1: - return None - UShortArray = c_ushort * pNumPixel.value - pRows = UShortArray() - pCols = UShortArray() - err_code = _sdk.CameraReadDeadPixels(hCamera, pRows, pCols, byref(pNumPixel)) - SetLastError(err_code) - if err_code == 0: - pNumPixel = pNumPixel.value - else: - pNumPixel = 0 - return (pRows[:pNumPixel], pCols[:pNumPixel]) - -def CameraAddDeadPixels(hCamera, pRows, pCols, NumPixel): - UShortArray = c_ushort * NumPixel - pRowsNative = UShortArray(*pRows) - pColsNative = UShortArray(*pCols) - err_code = _sdk.CameraAddDeadPixels(hCamera, pRowsNative, pColsNative, NumPixel) - SetLastError(err_code) - return err_code - -def CameraRemoveDeadPixels(hCamera, pRows, pCols, NumPixel): - UShortArray = c_ushort * NumPixel - pRowsNative = UShortArray(*pRows) - pColsNative = UShortArray(*pCols) - err_code = _sdk.CameraRemoveDeadPixels(hCamera, pRowsNative, pColsNative, NumPixel) - SetLastError(err_code) - return err_code - -def CameraRemoveAllDeadPixels(hCamera): - err_code = _sdk.CameraRemoveAllDeadPixels(hCamera) - SetLastError(err_code) - return err_code - -def CameraSaveDeadPixels(hCamera): - err_code = _sdk.CameraSaveDeadPixels(hCamera) - SetLastError(err_code) - return err_code - -def CameraSaveDeadPixelsToFile(hCamera, sFileName): - err_code = _sdk.CameraSaveDeadPixelsToFile(hCamera, _str_to_string_buffer(sFileName)) - SetLastError(err_code) - return err_code - -def CameraLoadDeadPixelsFromFile(hCamera, sFileName): - err_code = _sdk.CameraLoadDeadPixelsFromFile(hCamera, _str_to_string_buffer(sFileName)) - SetLastError(err_code) - return err_code - -def CameraGetImageBufferPriority(hCamera, wTimes, Priority): - pFrameInfo = tSdkFrameHead() - pbyBuffer = c_void_p() - err_code = _sdk.CameraGetImageBufferPriority(hCamera, byref(pFrameInfo), byref(pbyBuffer), wTimes, Priority) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return (pbyBuffer.value, pFrameInfo) - -def CameraGetImageBufferPriorityEx(hCamera, wTimes, Priority): - _sdk.CameraGetImageBufferPriorityEx.restype = c_void_p - piWidth = c_int() - piHeight = c_int() - pFrameBuffer = _sdk.CameraGetImageBufferPriorityEx(hCamera, byref(piWidth), byref(piHeight), wTimes, Priority) - err_code = CAMERA_STATUS_SUCCESS if pFrameBuffer else CAMERA_STATUS_TIME_OUT - SetLastError(err_code) - if pFrameBuffer: - return (pFrameBuffer, piWidth.value, piHeight.value) - else: - raise CameraException(err_code) - -def CameraGetImageBufferPriorityEx2(hCamera, pImageData, uOutFormat, wTimes, Priority): - piWidth = c_int() - piHeight = c_int() - err_code = _sdk.CameraGetImageBufferPriorityEx2(hCamera, c_void_p(pImageData), uOutFormat, byref(piWidth), byref(piHeight), wTimes, Priority) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return (piWidth.value, piHeight.value) - -def CameraGetImageBufferPriorityEx3(hCamera, pImageData, uOutFormat, wTimes, Priority): - piWidth = c_int() - piHeight = c_int() - puTimeStamp = c_uint() - err_code = _sdk.CameraGetImageBufferPriorityEx3(hCamera, c_void_p(pImageData), uOutFormat, byref(piWidth), byref(piHeight), byref(puTimeStamp), wTimes, Priority) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return (piWidth.value, piHeight.value, puTimeStamp.value) - -def CameraClearBuffer(hCamera): - err_code = _sdk.CameraClearBuffer(hCamera) - SetLastError(err_code) - return err_code - -def CameraSoftTriggerEx(hCamera, uFlags): - err_code = _sdk.CameraSoftTriggerEx(hCamera, uFlags) - SetLastError(err_code) - return err_code - -def CameraSetHDR(hCamera, value): - err_code = _sdk.CameraSetHDR(hCamera, value) - SetLastError(err_code) - return err_code - -def CameraGetHDR(hCamera): - value = c_int() - err_code = _sdk.CameraGetHDR(hCamera, byref(value)) - SetLastError(err_code) - return value.value - -def CameraGetFrameID(hCamera): - FrameID = c_uint() - err_code = _sdk.CameraGetFrameID(hCamera, byref(FrameID)) - SetLastError(err_code) - return FrameID.value - -def CameraGetFrameTimeStamp(hCamera): - TimeStamp = c_uint64() - TimeStampL = c_uint32.from_buffer(TimeStamp) - TimeStampH = c_uint32.from_buffer(TimeStamp, 4) - err_code = _sdk.CameraGetFrameTimeStamp(hCamera, byref(TimeStampL), byref(TimeStampH)) - SetLastError(err_code) - return TimeStamp.value - -def CameraSetHDRGainMode(hCamera, value): - err_code = _sdk.CameraSetHDRGainMode(hCamera, value) - SetLastError(err_code) - return err_code - -def CameraGetHDRGainMode(hCamera): - value = c_int() - err_code = _sdk.CameraGetHDRGainMode(hCamera, byref(value)) - SetLastError(err_code) - return value.value - -def CameraCreateDIBitmap(hDC, pFrameBuffer, pFrameHead): - outBitmap = c_void_p() - err_code = _sdk.CameraCreateDIBitmap(hDC, c_void_p(pFrameBuffer), byref(pFrameHead), byref(outBitmap)) - SetLastError(err_code) - return outBitmap.value - -def CameraDrawFrameBuffer(pFrameBuffer, pFrameHead, hWnd, Algorithm, Mode): - err_code = _sdk.CameraDrawFrameBuffer(c_void_p(pFrameBuffer), byref(pFrameHead), c_void_p(hWnd), Algorithm, Mode) - SetLastError(err_code) - return err_code - -def CameraFlipFrameBuffer(pFrameBuffer, pFrameHead, Flags): - err_code = _sdk.CameraFlipFrameBuffer(c_void_p(pFrameBuffer), byref(pFrameHead), Flags) - SetLastError(err_code) - return err_code - -def CameraConvertFrameBufferFormat(hCamera, pInFrameBuffer, pOutFrameBuffer, outWidth, outHeight, outMediaType, pFrameHead): - err_code = _sdk.CameraConvertFrameBufferFormat(hCamera, c_void_p(pInFrameBuffer), c_void_p(pOutFrameBuffer), outWidth, outHeight, outMediaType, byref(pFrameHead)) - SetLastError(err_code) - return err_code - -def CameraSetConnectionStatusCallback(hCamera, pCallBack, pContext = 0): - err_code = _sdk.CameraSetConnectionStatusCallback(hCamera, pCallBack, c_void_p(pContext) ) - SetLastError(err_code) - return err_code - -def CameraSetLightingControllerMode(hCamera, index, mode): - err_code = _sdk.CameraSetLightingControllerMode(hCamera, index, mode) - SetLastError(err_code) - return err_code - -def CameraSetLightingControllerState(hCamera, index, state): - err_code = _sdk.CameraSetLightingControllerState(hCamera, index, state) - SetLastError(err_code) - return err_code - -def CameraSetFrameResendCount(hCamera, count): - err_code = _sdk.CameraSetFrameResendCount(hCamera, count) - SetLastError(err_code) - return err_code - -def CameraSetUndistortParams(hCamera, width, height, cameraMatrix, distCoeffs): - assert(len(cameraMatrix) == 4) - assert(len(distCoeffs) == 5) - cameraMatrixNative = (c_double * len(cameraMatrix))(*cameraMatrix) - distCoeffsNative = (c_double * len(distCoeffs))(*distCoeffs) - err_code = _sdk.CameraSetUndistortParams(hCamera, width, height, cameraMatrixNative, distCoeffsNative) - SetLastError(err_code) - return err_code - -def CameraGetUndistortParams(hCamera): - width = c_int() - height = c_int() - cameraMatrix = (c_double * 4)() - distCoeffs = (c_double * 5)() - err_code = _sdk.CameraGetUndistortParams(hCamera, byref(width), byref(height), cameraMatrix, distCoeffs) - SetLastError(err_code) - width, height = width.value, height.value - cameraMatrix = cameraMatrix[:] - distCoeffs = distCoeffs[:] - return (width, height, cameraMatrix, distCoeffs) - -def CameraSetUndistortEnable(hCamera, bEnable): - err_code = _sdk.CameraSetUndistortEnable(hCamera, bEnable) - SetLastError(err_code) - return err_code - -def CameraGetUndistortEnable(hCamera): - value = c_int() - err_code = _sdk.CameraGetUndistortEnable(hCamera, byref(value)) - SetLastError(err_code) - return value.value - -def CameraCustomizeUndistort(hCamera, hParent): - err_code = _sdk.CameraCustomizeUndistort(hCamera, hParent) - SetLastError(err_code) - return err_code - -def CameraGetEyeCount(hCamera): - EyeCount = c_int() - err_code = _sdk.CameraGetEyeCount(hCamera, byref(EyeCount)) - SetLastError(err_code) - return EyeCount.value - -def CameraMultiEyeImageProcess(hCamera, iEyeIndex, pbyIn, pInFrInfo, pbyOut, pOutFrInfo, uOutFormat, uReserved): - err_code = _sdk.CameraMultiEyeImageProcess(hCamera, iEyeIndex, c_void_p(pbyIn), byref(pInFrInfo), c_void_p(pbyOut), byref(pOutFrInfo), uOutFormat, uReserved) - SetLastError(err_code) - return err_code - -# CameraGrabber - -def CameraGrabber_CreateFromDevicePage(): - Grabber = c_void_p() - err_code = _sdk.CameraGrabber_CreateFromDevicePage(byref(Grabber)) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return Grabber.value - -def CameraGrabber_CreateByIndex(Index): - Grabber = c_void_p() - err_code = _sdk.CameraGrabber_CreateByIndex(byref(Grabber), Index) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return Grabber.value - -def CameraGrabber_CreateByName(Name): - Grabber = c_void_p() - err_code = _sdk.CameraGrabber_CreateByName(byref(Grabber), _str_to_string_buffer(Name)) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return Grabber.value - -def CameraGrabber_Create(pDevInfo): - Grabber = c_void_p() - err_code = _sdk.CameraGrabber_Create(byref(Grabber), byref(pDevInfo)) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return Grabber.value - -def CameraGrabber_Destroy(Grabber): - err_code = _sdk.CameraGrabber_Destroy(c_void_p(Grabber)) - SetLastError(err_code) - return err_code - -def CameraGrabber_SetHWnd(Grabber, hWnd): - err_code = _sdk.CameraGrabber_SetHWnd(c_void_p(Grabber), c_void_p(hWnd) ) - SetLastError(err_code) - return err_code - -def CameraGrabber_SetPriority(Grabber, Priority): - err_code = _sdk.CameraGrabber_SetPriority(c_void_p(Grabber), Priority) - SetLastError(err_code) - return err_code - -def CameraGrabber_StartLive(Grabber): - err_code = _sdk.CameraGrabber_StartLive(c_void_p(Grabber)) - SetLastError(err_code) - return err_code - -def CameraGrabber_StopLive(Grabber): - err_code = _sdk.CameraGrabber_StopLive(c_void_p(Grabber)) - SetLastError(err_code) - return err_code - -def CameraGrabber_SaveImage(Grabber, TimeOut): - Image = c_void_p() - err_code = _sdk.CameraGrabber_SaveImage(c_void_p(Grabber), byref(Image), TimeOut) - SetLastError(err_code) - if err_code != 0: - raise CameraException(err_code) - return Image.value - -def CameraGrabber_SaveImageAsync(Grabber): - err_code = _sdk.CameraGrabber_SaveImageAsync(c_void_p(Grabber)) - SetLastError(err_code) - return err_code - -def CameraGrabber_SaveImageAsyncEx(Grabber, UserData): - err_code = _sdk.CameraGrabber_SaveImageAsyncEx(c_void_p(Grabber), c_void_p(UserData)) - SetLastError(err_code) - return err_code - -def CameraGrabber_SetSaveImageCompleteCallback(Grabber, Callback, Context = 0): - err_code = _sdk.CameraGrabber_SetSaveImageCompleteCallback(c_void_p(Grabber), Callback, c_void_p(Context)) - SetLastError(err_code) - return err_code - -def CameraGrabber_SetFrameListener(Grabber, Listener, Context = 0): - err_code = _sdk.CameraGrabber_SetFrameListener(c_void_p(Grabber), Listener, c_void_p(Context)) - SetLastError(err_code) - return err_code - -def CameraGrabber_SetRawCallback(Grabber, Callback, Context = 0): - err_code = _sdk.CameraGrabber_SetRawCallback(c_void_p(Grabber), Callback, c_void_p(Context)) - SetLastError(err_code) - return err_code - -def CameraGrabber_SetRGBCallback(Grabber, Callback, Context = 0): - err_code = _sdk.CameraGrabber_SetRGBCallback(c_void_p(Grabber), Callback, c_void_p(Context)) - SetLastError(err_code) - return err_code - -def CameraGrabber_GetCameraHandle(Grabber): - hCamera = c_int() - err_code = _sdk.CameraGrabber_GetCameraHandle(c_void_p(Grabber), byref(hCamera)) - SetLastError(err_code) - return hCamera.value - -def CameraGrabber_GetStat(Grabber): - stat = tSdkGrabberStat() - err_code = _sdk.CameraGrabber_GetStat(c_void_p(Grabber), byref(stat)) - SetLastError(err_code) - return stat - -def CameraGrabber_GetCameraDevInfo(Grabber): - DevInfo = tSdkCameraDevInfo() - err_code = _sdk.CameraGrabber_GetCameraDevInfo(c_void_p(Grabber), byref(DevInfo)) - SetLastError(err_code) - return DevInfo - -# CameraImage - -def CameraImage_Create(pFrameBuffer, pFrameHead, bCopy): - Image = c_void_p() - err_code = _sdk.CameraImage_Create(byref(Image), c_void_p(pFrameBuffer), byref(pFrameHead), bCopy) - SetLastError(err_code) - return Image.value - -def CameraImage_CreateEmpty(): - Image = c_void_p() - err_code = _sdk.CameraImage_CreateEmpty(byref(Image)) - SetLastError(err_code) - return Image.value - -def CameraImage_Destroy(Image): - err_code = _sdk.CameraImage_Destroy(c_void_p(Image)) - SetLastError(err_code) - return err_code - -def CameraImage_GetData(Image): - DataBuffer = c_void_p() - HeadPtr = c_void_p() - err_code = _sdk.CameraImage_GetData(c_void_p(Image), byref(DataBuffer), byref(HeadPtr)) - SetLastError(err_code) - if err_code == 0: - return (DataBuffer.value, tSdkFrameHead.from_address(HeadPtr.value) ) - else: - return (0, None) - -def CameraImage_GetUserData(Image): - UserData = c_void_p() - err_code = _sdk.CameraImage_GetUserData(c_void_p(Image), byref(UserData)) - SetLastError(err_code) - return UserData.value - -def CameraImage_SetUserData(Image, UserData): - err_code = _sdk.CameraImage_SetUserData(c_void_p(Image), c_void_p(UserData)) - SetLastError(err_code) - return err_code - -def CameraImage_IsEmpty(Image): - IsEmpty = c_int() - err_code = _sdk.CameraImage_IsEmpty(c_void_p(Image), byref(IsEmpty)) - SetLastError(err_code) - return IsEmpty.value - -def CameraImage_Draw(Image, hWnd, Algorithm): - err_code = _sdk.CameraImage_Draw(c_void_p(Image), c_void_p(hWnd), Algorithm) - SetLastError(err_code) - return err_code - -def CameraImage_DrawFit(Image, hWnd, Algorithm): - err_code = _sdk.CameraImage_DrawFit(c_void_p(Image), c_void_p(hWnd), Algorithm) - SetLastError(err_code) - return err_code - -def CameraImage_DrawToDC(Image, hDC, Algorithm, xDst, yDst, cxDst, cyDst): - err_code = _sdk.CameraImage_DrawToDC(c_void_p(Image), c_void_p(hDC), Algorithm, xDst, yDst, cxDst, cyDst) - SetLastError(err_code) - return err_code - -def CameraImage_DrawToDCFit(Image, hDC, Algorithm, xDst, yDst, cxDst, cyDst): - err_code = _sdk.CameraImage_DrawToDCFit(c_void_p(Image), c_void_p(hDC), Algorithm, xDst, yDst, cxDst, cyDst) - SetLastError(err_code) - return err_code - -def CameraImage_BitBlt(Image, hWnd, xDst, yDst, cxDst, cyDst, xSrc, ySrc): - err_code = _sdk.CameraImage_BitBlt(c_void_p(Image), c_void_p(hWnd), xDst, yDst, cxDst, cyDst, xSrc, ySrc) - SetLastError(err_code) - return err_code - -def CameraImage_BitBltToDC(Image, hDC, xDst, yDst, cxDst, cyDst, xSrc, ySrc): - err_code = _sdk.CameraImage_BitBltToDC(c_void_p(Image), c_void_p(hDC), xDst, yDst, cxDst, cyDst, xSrc, ySrc) - SetLastError(err_code) - return err_code - -def CameraImage_SaveAsBmp(Image, FileName): - err_code = _sdk.CameraImage_SaveAsBmp(c_void_p(Image), _str_to_string_buffer(FileName)) - SetLastError(err_code) - return err_code - -def CameraImage_SaveAsJpeg(Image, FileName, Quality): - err_code = _sdk.CameraImage_SaveAsJpeg(c_void_p(Image), _str_to_string_buffer(FileName), Quality) - SetLastError(err_code) - return err_code - -def CameraImage_SaveAsPng(Image, FileName): - err_code = _sdk.CameraImage_SaveAsPng(c_void_p(Image), _str_to_string_buffer(FileName)) - SetLastError(err_code) - return err_code - -def CameraImage_SaveAsRaw(Image, FileName, Format): - err_code = _sdk.CameraImage_SaveAsRaw(c_void_p(Image), _str_to_string_buffer(FileName), Format) - SetLastError(err_code) - return err_code - -def CameraImage_IPicture(Image): - NewPic = c_void_p() - err_code = _sdk.CameraImage_IPicture(c_void_p(Image), byref(NewPic)) - SetLastError(err_code) - return NewPic.value diff --git a/Camera/read_from_file.py b/Camera/read_from_file.py deleted file mode 100644 index f0b3db5..0000000 --- a/Camera/read_from_file.py +++ /dev/null @@ -1,73 +0,0 @@ -"""Hosts the fake camera class that reads from a file for testing.""" -import sys -import time -import numpy as np -import cv2 -import Utils - -from Camera.camera_base import CameraBase - - -class fake_camera(CameraBase): - """ - Fake camera class that mimics the behavior of the real camera. - - It reads from a video file instead. - """ - - # Needs to be calibrated per camera - YAW_FOV_HALF = Utils.deg_to_rad(42) / 2 - PITCH_FOV_HALF = Utils.deg_to_rad(42) / 2 - - def __init__(self, cfg): - """Initialize fake camera. - - Args: - cfg (python object): shared config object - """ - super().__init__(cfg) - - assert len(sys.argv) == 2 # main py file; video file - video_path = sys.argv[1] - assert video_path.endswith('.mp4') - - self.cap = cv2.VideoCapture(video_path) - assert self.cap.isOpened() - - self.alive = True # init to True - - # Timing and frame counter are always in place for devlopment purpose - self.timing = None - self.frame_cnt = 0 - - def get_frame(self): - """Call to get a frame from the camera. - - Raises: - Exception: raised when video file is exhausted - - Returns: - np.ndarray: BGR image frame - """ - if self.timing is None: - self.timing = time.time() - - if not self.cap.isOpened(): - self.alive = False - - ret, frame = self.cap.read() - - if not ret: - self.alive = False - - if not self.alive: - print("Total frames: {}".format(self.frame_cnt)) - print("Total time: {}".format(time.time() - self.timing)) - print("FPS: {}".format(self.frame_cnt / (time.time() - self.timing))) - raise Exception("Video file exhausted") - - frame = cv2.resize(frame, (self.width, self.height)) - - self.frame_cnt += 1 - - return frame diff --git a/Camera/shl_200ws.py.deprecated b/Camera/shl_200ws.py.deprecated deleted file mode 100644 index 0c1ab9d..0000000 --- a/Camera/shl_200ws.py.deprecated +++ /dev/null @@ -1,35 +0,0 @@ -import numpy as np -import cv2 -import time - -cap = cv2.VideoCapture( - 'v4l2src device=/dev/video0 ! image/jpeg,framerate=61612/513,width=640,height=480 ! jpegdec ! videoconvert ! video/x-raw,format=BGR ! appsink max-buffers=1 drop=true', # noqa - cv2.CAP_GSTREAMER) - -if not cap.isOpened(): - print("Cannot open camera") - exit() - -while True: - start_cp = time.time() - # Capture frame-by-frame - ret, frame = cap.read() - # if frame is read correctly ret is True - if not ret: - print("Can't receive frame (stream end?). Exiting ...") - break - print(frame.shape) - # Our operations on the frame come here - # Display the resulting frame - cv2.imshow('frame', frame) - my_key = cv2.waitKey(1) - if my_key == ord('q'): - break - elif my_key == ord('s'): - cv2.imwrite('test.jpg', frame) - print("Total time elapsed: {:.4f}".format(time.time() - start_cp)) - -# When everything done, release the capture - -cap.release() -cv2.destroyAllWindows() diff --git a/Camera/simple_cv.py b/Camera/simple_cv.py deleted file mode 100644 index abe5f04..0000000 --- a/Camera/simple_cv.py +++ /dev/null @@ -1,39 +0,0 @@ -"""Hosts the fake camera class that reads from a file for testing.""" -import sys -import time -import numpy as np -import cv2 -import Utils - -from Camera.camera_base import CameraBase - - -class simple_cv_camera(CameraBase): - """Simple OpenCV camera.""" - - # Needs to be calibrated per camera - YAW_FOV_HALF = Utils.deg_to_rad(42) / 2 - PITCH_FOV_HALF = Utils.deg_to_rad(42) / 2 - - def __init__(self, cfg): - """Initialize a simple camera from defualt camera cam. - - Args: - cfg (python object): shared config object - """ - super().__init__(cfg) - - self.cap = cv2.VideoCapture(0) - assert self.cap.isOpened() - - def get_frame(self): - """Call to get a frame from the camera. - - Returns: - np.ndarray: BGR image frame - """ - ret, frame = self.cap.read() - if not ret: - raise - frame = cv2.resize(frame, (self.width, self.height)) - return frame diff --git a/Communication/communicator.py b/Communication/communicator.py index 250f890..39d8237 100644 --- a/Communication/communicator.py +++ b/Communication/communicator.py @@ -287,7 +287,10 @@ def list_uart_device_paths(): # list of possible prefixes UART_PREFIX_LIST = ('tty.usbmodem', 'usb-STMicroelectronics_STM32_STLink_') dev_basename = '/dev/serial/by-id' - dev_list = os.listdir(dev_basename) + try: + dev_list = os.listdir(dev_basename) + except FileNotFoundError: + dev_list = [] dev_paths = [] # ret val for dev_name in dev_list: diff --git a/Detection/CV_mix_DL.py b/Detection/CV_mix_DL.py deleted file mode 100644 index a39078b..0000000 --- a/Detection/CV_mix_DL.py +++ /dev/null @@ -1,650 +0,0 @@ -"""Host routines for computational / learning-based detections.""" -import numpy as np -import cv2 -import os -import time -import Utils -# Internal ENUM -RED = 0 -BLUE = 1 - - -class cv_mix_dl_detector: - """A routine that combines CV and DL to detect armors. - - It uses CV to propose potential armors, and then uses DL to filter out false positives. - """ - - def __init__(self, config, detect_color, model_path='fc.onnx'): - """Initialize the detector. - - Args: - config (python object): shared config.py - detect_color (int): RED or BLUE (enum) - model_path (str, optional): path to the DL model. Defaults to 'fc.onnx'. - """ - self.CFG = config - self.armor_proposer = cv_armor_proposer(self.CFG, detect_color) - self.digit_classifier = dl_digit_classifier(self.CFG, model_path) - self.change_color(detect_color) - - def detect(self, rgb_img): - """Detect armors in the given image. - - Args: - rgb_img (np.ndarray): RGB image - - Returns: - list: list of detected armors - """ - return self(rgb_img) - - def __call__(self, rgb_img): - """Detect armors in the given image. - - Args: - rgb_img (np.ndarray): RGB image - - Returns: - list: list of detected armors - """ - rgb_img = Utils.auto_align_brightness(rgb_img) - # defaults to BGR format - rgb_img = cv2.cvtColor(rgb_img, cv2.COLOR_BGR2RGB) - # propose potential armors - armor_list = self.armor_proposer(rgb_img) - for armor in armor_list: - armor.extract_number(rgb_img) - - # filter out false positives - armor_list = self.digit_classifier(armor_list) - - # Pad into formats - ret_list = [] - # name, conf, bbox - # center_x, center_y, width, height = bbox - for armor in armor_list: - center_x, center_y = armor.center - height = (armor.left_light.length + armor.right_light.length) / 2 - width = cv2.norm(armor.left_light.center - armor.right_light.center) - bbox = (center_x, center_y, width, height) - name = f'armor_{self.detect_color_str}' - ret_list.append((name, float(armor.confidence), str(armor.number[0]), bbox, armor)) - return ret_list - - def change_color(self, new_color): - """Change the color of the detector. - - Args: - new_color (int): RED or BLUE (enum) - """ - if new_color in [0, 1]: - assert new_color in [0, 1] - self.detect_color = new_color - self.armor_proposer.detect_color = new_color - if new_color: - self.detect_color_str = 'blue' - else: - self.detect_color_str = 'red' - elif new_color in ['red', 'blue']: - self.detect_color_str = new_color - if new_color == 'red': - color_num = 0 - else: - color_num = 1 - self.detect_color = color_num - self.armor_proposer.detect_color = color_num - else: - raise NotImplementedError - - -class light_class: - """ - A class that represents a light bar on the armor board. - - Most importantly, given a rotated rect from OpenCV, it can calculate the - center, top, bottom, length, width, and tilt angle of the light bar. - - For instance, OpenCV could say a rotated rect is 180 degrees tilted, but - in fact, it is 0 degrees tilted. This class can correct the tilt angle. - - Attributes: - center (np.ndarray): center of the light bar - top (np.ndarray): top point of the light bar - btm (np.ndarray): bottom point of the light bar - length (float): length of the light bar - width (float): width of the light bar - tilt_angle (float): tilt angle of the light bar - """ - - def __init__(self, rotated_rect): - """Initialize the light bar. - - Args: - rotated_rect (tuple): (center, (width, height), angle) - """ - ((self.center_x, self.center_y), (_, _), _) = rotated_rect - # sort according to y - pts = sorted(cv2.boxPoints(rotated_rect), key=lambda x: x[1]) - self.top = (pts[0] + pts[1]) / 2 - self.btm = (pts[2] + pts[3]) / 2 - - self.length = cv2.norm(self.top - self.btm) - self.width = cv2.norm(pts[0] - pts[1]) - - self.tilt_angle = np.arctan2( - np.abs( - self.top[0] - - self.btm[0]), - np.abs( - self.top[1] - - self.btm[1])) - self.tilt_angle = self.tilt_angle / np.pi * 180 - - self.center = np.array([self.center_x, self.center_y]) - - self.color = None - - -class armor_class: - """ - A class that represents an armor board. - - Attributes: - left_light (light_class): left light bar - right_light (light_class): right light bar - center (np.ndarray): center of the armor board - color (int): color of the armor board - confidence (float): confidence of the armor board - armor_type (str): 'large' or 'small' - """ - - def __init__(self, light1, light2, color): - """Initialize the armor board. - - Args: - light1 (light_class): left light bar - light2 (light_class): right light bar - color (int): color of the armor board - """ - assert light1.color == light2.color - assert light1.color == color - self.color = color - self.confidence = 0.0 - - if light1.center_x < light2.center_x: - self.left_light = light1 - self.right_light = light2 - else: - self.left_light = light2 - self.right_light = light1 - - self.center = (self.left_light.center + self.right_light.center) / 2 - self.armor_type = None # 'large', 'small' - - def extract_number(self, rgb_img): - """Extract number from the armor board using perspective transform. - - The perspective transform matrix is computed by using top and bottom - points of the left and right light bars as source vertices, and - manually set target vertices. - - Args: - rgb_img (np.ndarray): RGB image - """ - light_length = 12 - warp_height = 28 - small_armor_width = 32 - large_armor_width = 54 - - roi_size = (20, 28) - - lights_vertices = np.array([ - self.left_light.btm, self.left_light.top, - self.right_light.top, self.right_light.btm - ]).astype(np.float32) - - top_light_y = (warp_height - light_length) / 2 - 1 - bottom_light_y = top_light_y + light_length - - if self.armor_type == 'small': - warp_width = small_armor_width - else: - warp_width = large_armor_width - - target_vertices = np.array([ - [0, bottom_light_y], [0, top_light_y], - [warp_width - 1, top_light_y], [warp_width - 1, bottom_light_y] - ]).astype(np.float32) # default to float64 for some reason... - - rotation_matrix = cv2.getPerspectiveTransform( - lights_vertices, target_vertices) - - self.number_image = cv2.warpPerspective( - rgb_img, rotation_matrix, (warp_width, warp_height)) - - start_x = int((warp_width - roi_size[0]) / 2) - self.number_image = self.number_image[:roi_size[1], - start_x:start_x + roi_size[0]] - - # Binarize - self.number_image = cv2.cvtColor(self.number_image, cv2.COLOR_RGB2GRAY) - thres, self.number_image = cv2.threshold( - self.number_image, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) - - -class cv_armor_proposer: - """Armor proposer using OpenCV.""" - - # Hyperparameters - MIN_LIGHTNESS = 160 - LUMINANCE_THRES = 90 - - LIGHT_MIN_RATIO = 0.1 - LIGHT_MAX_RATIO = 0.55 - LIGHT_MAX_ANGLE = 40.0 - - LIGHT_AREA_THRES = 50 - - ARMOR_MIN_LIGHT_RATIO = 0.6 - ARMOR_MIN_SMALL_CENTER_DISTANCE = 1.3 - ARMOR_MAX_SMALL_CENTER_DISTANCE = 4 - ARMOR_MIN_LARGE_CENTER_DISTANCE = 4 - ARMOR_MAX_LARGE_CENTER_DISTANCE = 6 - - assert ARMOR_MAX_SMALL_CENTER_DISTANCE <= ARMOR_MIN_LARGE_CENTER_DISTANCE - - armor_max_angle = 35.0 - - def __init__(self, config, detect_color): - """Initialize the armor proposer. - - Args: - config (python object): shared config.py - detect_color (int): color to detect (0: red, 1: blue ENUM) - """ - self.CFG = config - self.detect_color = detect_color - - def __call__(self, rgb_img): - """Run the armor proposer for a single image. - - Args: - rgb_img (np.ndarray): RGB image - - Returns: - list of armor_class: list of detected armors - """ - binary_img = self.preprocess(rgb_img) - if self.CFG.DEBUG_DISPLAY: - # visualize binary image - cv2.imshow('binary', binary_img) - cv2.waitKey(1) - - light_list = self.find_lights(rgb_img, binary_img) - if self.CFG.DEBUG_DISPLAY: - viz_img = rgb_img.copy() - # visualize lights - for light in light_list: - cv2.rectangle( - viz_img, (int( - light.top[0]), int( - light.top[1])), (int( - light.btm[0]), int( - light.btm[1])), (0, 255, 0), 2) - cv2.imshow('lights', viz_img) - cv2.waitKey(1) - - armor_list = self.match_lights(light_list) - if self.CFG.DEBUG_DISPLAY: - viz_img = rgb_img.copy() - # visualize armors - for armor in armor_list: - cv2.rectangle( - viz_img, (int( - armor.left_light.top[0]), int( - armor.left_light.top[1])), (int( - armor.right_light.btm[0]), int( - armor.right_light.btm[1])), (0, 255, 0), 2) - cv2.imshow('armors', viz_img) - cv2.waitKey(1) - - return armor_list - - def preprocess(self, rgb_img): - """Preprocess for binarized image. - - Args: - rgb_img (np.ndarray): RGB image - - Returns: - np.ndarray: binarized image - """ - gray_img = cv2.cvtColor(rgb_img, cv2.COLOR_RGB2GRAY) - - thres, binary_img = cv2.threshold( - gray_img, self.MIN_LIGHTNESS, 255, cv2.THRESH_BINARY) - - return binary_img - - def filter_contours_rects(self, contours, rects, rgb_img): - """Filter out contours that are too small and not of interested color. - - Args: - contours (list of np.ndarray): contours - rects (list of np.ndarray): bounding rectangles - rgb_img (np.ndarray): RGB image - - Returns: - list of np.ndarray: filtered contours - list of np.ndarray: filtered bounding rectangles - """ - filtered_contours = [] - filtered_rects = [] - assert len(contours) == len(rects) - for i in range(len(rects)): - x, y, w, h = rects[i] - # Area test - if w * h < self.LIGHT_AREA_THRES: - continue - - # Color test - if not Utils.color_test(rgb_img, rects[i], self.detect_color): - continue - - filtered_rects.append(rects[i]) - filtered_contours.append(contours[i]) - - return filtered_contours, filtered_rects - - def find_lights(self, rgb_img, binary_img): - """Find potential light bars in the image. - - It follows open-sourced implementation to detect light bar from - binarzied images. However, in practice we find that is not robust - enough. So we augment it with color difference contours too. - - Two contours are often overlapped and we apply NMS to remove - overlapped ones. We trust binary contours more than color difference. - - The NMS is also different from the one in object detection. Namely, - in detection we usually do - - IoU = intersection / union - - So that a small object in front of a big object will not be removed. - - However, in our case, using this leads to inefficiency because two light bars - can not be contained in each other. So we use - - IoU = intersection / area of smaller one - - instead. - - Args: - rgb_img (np.ndarray): RGB image - binary_img (np.ndarray): binarized image - - Returns: - list of light_class: list of detected lights - """ - bin_contours, _ = cv2.findContours( - binary_img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - # Use difference of color to handle white light - if self.detect_color == RED: - color_diff = rgb_img[:, :, 0].astype(int) - rgb_img[:, :, 2] - color_diff[color_diff < 0] = 0 - color_diff = color_diff.astype(np.uint8) - _, color_bin = cv2.threshold( - color_diff, self.LUMINANCE_THRES, 255, cv2.THRESH_BINARY) - color_contours, _ = cv2.findContours( - color_bin, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - else: - color_diff = rgb_img[:, :, 2].astype(int) - rgb_img[:, :, 0] - color_diff[color_diff < 0] = 0 - color_diff = color_diff.astype(np.uint8) - _, color_bin = cv2.threshold( - color_diff, self.LUMINANCE_THRES, 255, cv2.THRESH_BINARY) - color_contours, _ = cv2.findContours( - color_bin, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - - if self.CFG.DEBUG_DISPLAY: - cv2.imshow('color', color_bin) - cv2.waitKey(1) - - # Preprocess contours for early filtering - bin_contours = [ - contour for contour in bin_contours if contour.shape[0] >= 5] - color_contours = [ - contour for contour in color_contours if contour.shape[0] >= 5] - - bin_rects = [cv2.boundingRect(contour) for contour in bin_contours] - col_rects = [cv2.boundingRect(contour) for contour in color_contours] - - # Basic filtering for contours and rects - bin_contours, bin_rects = self.filter_contours_rects( - bin_contours, bin_rects, rgb_img) - color_contours, col_rects = self.filter_contours_rects( - color_contours, col_rects, rgb_img) - - # Apply NMS to contours from binary image and color difference image - # COLOR contours are generally less reliable - final_contours = [] - for col_rect, col_contour in zip(col_rects, color_contours): - append_flag = True - for bin_rect in bin_rects: - # Compute rectangle overlap - x_overlap = max(0, - min(bin_rect[0] + bin_rect[2], - col_rect[0] + col_rect[2]) - max(bin_rect[0], - col_rect[0])) - y_overlap = max(0, - min(bin_rect[1] + bin_rect[3], - col_rect[1] + col_rect[3]) - max(bin_rect[1], - col_rect[1])) - overlap = x_overlap * y_overlap - min_area = min(bin_rect[2] * bin_rect[3], - col_rect[2] * col_rect[3]) - normalized_overlap = overlap / min_area - NMS_THRES = 0.5 - if normalized_overlap > NMS_THRES: - # If overlap is too large, discard color contour - append_flag = False - break - if append_flag: - final_contours.append(col_contour) - final_contours.extend(bin_contours) - - light_list = [] - for contour in final_contours: - light = cv2.minAreaRect(contour) - light = light_class(light) - - if not self.is_light(light): - continue - - light.color = self.detect_color - light_list.append(light) - return light_list - - def is_light(self, light): - """Apply filtering to determine if a light bar is valid. - - Criteria: - 1. Aspect ratio can not be too large or too small (light bars are slim verticals) - 2. Tilt angle (light bars are vertical) - - Args: - light (light_class): light bar to be filtered - - Returns: - bool: True if the light bar is valid - """ - ratio = light.width / light.length - ratio_ok = self.LIGHT_MIN_RATIO < ratio and ratio < self.LIGHT_MAX_RATIO - - angle_ok = light.tilt_angle < self.LIGHT_MAX_ANGLE - - return ratio_ok and angle_ok - - def match_lights(self, light_list): - """Match pairs of lights into armors. - - Args: - light_list (list of light_class): list of detected lights - - Returns: - list of armor_class: list of detected armors - """ - armor_list = [] - - for i in range(len(light_list)): - for j in range(i + 1, len(light_list)): - light1 = light_list[i] - light2 = light_list[j] - - assert light1.color == self.detect_color - assert light2.color == self.detect_color - - if self.contain_light(light1, light2, light_list): - continue - - armor = armor_class(light1, light2, self.detect_color) - - if self.is_armor(armor): - armor_list.append(armor) - - return armor_list - - def contain_light(self, light1, light2, light_list): - """Test if a pair of light is contained in another light bar. - - Empirically, this is a good way to filter out false positives. - - Args: - light1 (light_class): light bar 1 - light2 (light_class): light bar 2 - light_list (list of light_class): list of all detected lights - - Returns: - bool: True if light1 and light2 are contained in another light bar - """ - pts = np.array([ - light1.top, light1.btm, light2.top, light2.btm - ]) - rect = cv2.boundingRect(pts) - - for test_light in light_list: - if test_light == light1 or test_light == light2: - continue - - if Utils.rect_contains( - rect, test_light.top) or Utils.rect_contains( - rect, test_light.btm) or Utils.rect_contains( - rect, test_light.center): - return True - - return False - - def is_armor(self, armor): - """Apply filtering to determine if an armor is valid. - - Criteria: - 1. The length of two light bars can not be too different - 2. The ratio of distance between two light bars and their length - 3. The angle of armor boards two light bars would form - - Args: - armor (armor_class): armor to be filtered - - Returns: - bool: True if the armor meets all the criteria - """ - light1 = armor.left_light - light2 = armor.right_light - if light1.length < light2.length: - light_length_ratio = light1.length / light2.length - else: - light_length_ratio = light2.length / light1.length - - light_ratio_ok = light_length_ratio > self.ARMOR_MIN_LIGHT_RATIO - - avg_light_length = (light1.length + light2.length) / 2 - center_dist = cv2.norm( - light1.center - light2.center) / avg_light_length - - center_dist_ok = ( - (self.ARMOR_MIN_SMALL_CENTER_DISTANCE < center_dist) and ( - center_dist < self.ARMOR_MAX_SMALL_CENTER_DISTANCE)) or ( - (self.ARMOR_MIN_LARGE_CENTER_DISTANCE < center_dist) and ( - center_dist < self.ARMOR_MAX_LARGE_CENTER_DISTANCE)) - - # test light center connection angle - diff = light1.center - light2.center - angle = abs(np.arctan(diff[1] / diff[0])) / np.pi * 180 - angle_ok = angle < self.armor_max_angle - - if center_dist > self.ARMOR_MIN_LARGE_CENTER_DISTANCE: - armor.armor_type = 'large' - else: - armor.armor_type = 'small' - - return light_ratio_ok and center_dist_ok and angle_ok - - -class dl_digit_classifier: - """Classify digits in armor number using deep learning model.""" - - LABEL_NAMES_LIST = np.array(['B', '1', '2', '3', '4', '5', 'G', 'O', 'N']) - CLASSIFIER_THRESHOLD = 0.9 - - def __init__(self, config, model_path): - """Initialize the classifier. - - Args: - config (python object): shared config.py - model_path (str): path to the model file - """ - self.CFG = config - self.net = cv2.dnn.readNetFromONNX(model_path) - - @staticmethod - def normalize(image): - """Normalize image to [0, 1].""" - return image.astype(np.float32) / 255.0 - - def __call__(self, armor_list): - """Classify a batch of armor numbers. - - Args: - armor_list (list of armor_class): list of armors to be classified - - Returns: - list of str: list of classified armor numbers - """ - ret_list = [] - for armor in armor_list: - input_image = self.normalize(armor.number_image) - blob = cv2.dnn.blobFromImage( - input_image, scalefactor=1., size=(28, 20)) # BCHW - self.net.setInput(blob) - outputs = self.net.forward() - max_probs = outputs.max(axis=1) - softmax_probs = np.exp(outputs - max_probs) - my_sum = np.sum(softmax_probs, axis=1) - softmax_probs = softmax_probs / my_sum - - # Test - max_class = softmax_probs.argmax(axis=1) - max_class_names = self.LABEL_NAMES_LIST[max_class] - - if softmax_probs[0, max_class] < self.CLASSIFIER_THRESHOLD or max_class_names == 'N': - continue - - # TODO: use digit predictions to improve accuracy? - # Right now using that logic causes a lot of false negatives... - armor.confidence = softmax_probs[0, max_class] - armor.number = max_class_names - ret_list.append(armor) - - return ret_list diff --git a/Detection/YOLO.py.deprecated b/Detection/YOLO.py.deprecated deleted file mode 100644 index 386fcce..0000000 --- a/Detection/YOLO.py.deprecated +++ /dev/null @@ -1,210 +0,0 @@ -from ctypes import * -import numpy as np -import random - -from config import DARKNET_LIB_PATH - -# Note: darknet is patched per issue https://github.com/pjreddie/darknet/issues/289 -# ============= copied from pjreddie's darknet repo - - -def sample(probs): - s = sum(probs) - probs = [a / s for a in probs] - r = random.uniform(0, 1) - for i in range(len(probs)): - r = r - probs[i] - if r <= 0: - return i - return len(probs) - 1 - - -def c_array(ctype, values): - arr = (ctype * len(values))() - arr[:] = values - return arr - - -class BOX(Structure): - _fields_ = [("x", c_float), - ("y", c_float), - ("w", c_float), - ("h", c_float)] - -# Follow up-to-date definition here -# https://github.com/AlexeyAB/darknet/blob/ccb392ddf2ab49f66989e6318a2e379c9238068c/darknet.py#L56 - - -class DETECTION(Structure): - _fields_ = [("bbox", BOX), - ("classes", c_int), - ("prob", POINTER(c_float)), - ("mask", POINTER(c_float)), - ("objectness", c_float), - ("sort_class", c_int), - ("uc", POINTER(c_float)), - ("points", c_int), - ("embeddings", POINTER(c_float)), - ("embedding_size", c_int), - ("sim", c_float), - ("track_id", c_int)] - - -class IMAGE(Structure): - _fields_ = [("w", c_int), - ("h", c_int), - ("c", c_int), - ("data", POINTER(c_float))] - - -class METADATA(Structure): - _fields_ = [("classes", c_int), - ("names", POINTER(c_char_p))] - - -lib = CDLL(DARKNET_LIB_PATH, RTLD_GLOBAL) -lib.network_width.argtypes = [c_void_p] -lib.network_width.restype = c_int -lib.network_height.argtypes = [c_void_p] -lib.network_height.restype = c_int - -predict = lib.network_predict -predict.argtypes = [c_void_p, POINTER(c_float)] -predict.restype = POINTER(c_float) - -set_gpu = lib.cuda_set_device -set_gpu.argtypes = [c_int] - -make_image = lib.make_image -make_image.argtypes = [c_int, c_int, c_int] -make_image.restype = IMAGE - -get_network_boxes = lib.get_network_boxes -get_network_boxes.argtypes = [ - c_void_p, - c_int, - c_int, - c_float, - c_float, - POINTER(c_int), - c_int, - POINTER(c_int)] -get_network_boxes.restype = POINTER(DETECTION) - -make_network_boxes = lib.make_network_boxes -make_network_boxes.argtypes = [c_void_p] -make_network_boxes.restype = POINTER(DETECTION) - -free_detections = lib.free_detections -free_detections.argtypes = [POINTER(DETECTION), c_int] - -free_ptrs = lib.free_ptrs -free_ptrs.argtypes = [POINTER(c_void_p), c_int] - -network_predict = lib.network_predict -network_predict.argtypes = [c_void_p, POINTER(c_float)] - -reset_rnn = lib.reset_rnn -reset_rnn.argtypes = [c_void_p] - -load_net = lib.load_network -load_net.argtypes = [c_char_p, c_char_p, c_int] -load_net.restype = c_void_p - -do_nms_obj = lib.do_nms_obj -do_nms_obj.argtypes = [POINTER(DETECTION), c_int, c_int, c_float] - -do_nms_sort = lib.do_nms_sort -do_nms_sort.argtypes = [POINTER(DETECTION), c_int, c_int, c_float] - -free_image = lib.free_image -free_image.argtypes = [IMAGE] - -letterbox_image = lib.letterbox_image -letterbox_image.argtypes = [IMAGE, c_int, c_int] -letterbox_image.restype = IMAGE - -load_meta = lib.get_metadata -lib.get_metadata.argtypes = [c_char_p] -lib.get_metadata.restype = METADATA - -load_image = lib.load_image_color -load_image.argtypes = [c_char_p, c_int, c_int] -load_image.restype = IMAGE - -rgbgr_image = lib.rgbgr_image -rgbgr_image.argtypes = [IMAGE] - -predict_image = lib.network_predict_image -predict_image.argtypes = [c_void_p, IMAGE] -predict_image.restype = POINTER(c_float) - -ndarray_image = lib.ndarray_to_image -ndarray_image.argtypes = [POINTER(c_ubyte), POINTER(c_long), POINTER(c_long)] -ndarray_image.restype = IMAGE - - -def nparray_to_image(img): - data = img.ctypes.data_as(POINTER(c_ubyte)) - image = ndarray_image(data, img.ctypes.shape, img.ctypes.strides) - - return image - -# ============= copied from pjreddie's darknet repo - - -class Yolo: - def __init__( - self, - cfg_path, - weight_path, - meta_path, - thresh=.5, - hier_thresh=.5, - nms=.45): - ''' - Args: - cfg_path: path to darknet model definition files - weight_path: path to darkent model weight - meta_path: path to detection meta path - (note: see https://github.com/pjreddie/darknet/blob/master/python/darknet.py for - example meta definition) - thresh: confidence threshold for unet - hier_thresh: confidence threshold for unet - nms: overlap threshold for nms - ''' - print(type(cfg_path), type(weight_path)) - self.net = load_net(cfg_path.encode(), weight_path.encode(), 0) - self.meta = load_meta(meta_path.encode()) - self.thresh = thresh - self.hier_thresh = hier_thresh - self.nms = nms - - def detect(self, image): - ''' - Args: - image: path to image to predict - Return: - An array of tuple (class name, prob, (x, y, w, h)) - ''' - # im = load_image(image, 0, 0) - im = nparray_to_image(image) - num = c_int(0) - pnum = pointer(num) - predict_image(self.net, im) - dets = get_network_boxes(self.net, im.w, im.h, - self.thresh, self.hier_thresh, None, 0, pnum) - num = pnum[0] - do_nms_obj(dets, num, self.meta.classes, self.nms) - - res = [] - for j in range(num): - for i in range(self.meta.classes): - if dets[j].prob[i] > 0: - b = dets[j].bbox - res.append( - (self.meta.names[i], dets[j].prob[i], (b.x, b.y, b.w, b.h))) - res = sorted(res, key=lambda x: -x[1]) - free_image(im) - free_detections(dets, num) - return res diff --git a/Utils/__init__.py b/Utils/__init__.py index 2a20bc7..e69de29 100644 --- a/Utils/__init__.py +++ b/Utils/__init__.py @@ -1,139 +0,0 @@ -"""Host commonly used utils functions.""" -import numpy as np -import cv2 - - -def deg_to_rad(deg): - """Convert degree to radian.""" - return deg * ((2 * np.pi) / 360) - - -def rad_to_deg(rad): - """Convert radian to degree.""" - return rad * (360. / (2 * np.pi)) - - -def auto_align_brightness(img, target_v=50): - """Standardize brightness of image. - - Args: - img (np.ndarray): BGR image - target_v (int, optional): target brightness. Defaults to 50. - - Returns: - np.ndarray: BGR image with standardized brightness - """ - hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) - h, s, v = cv2.split(hsv) - - cur_v = np.mean(v) - v_diff = int(cur_v - target_v) - - if v_diff > 0: - value = v_diff - # needs lower brightness - v[v < value] = 0 - v[v >= value] -= value - final_hsv = cv2.merge((h, s, v)) - img = cv2.cvtColor(final_hsv, cv2.COLOR_HSV2BGR) - return img - else: - # brighten - value = -v_diff - # needs lower brightness - v[v > (255 - value)] = 255 - v[v <= (255 - value)] += value - final_hsv = cv2.merge((h, s, v)) - img = cv2.cvtColor(final_hsv, cv2.COLOR_HSV2BGR) - return img - - -def color_test(rgb_img, rect, color): - """Test if the color of the roi is the same as the given color. - - Args: - rgb_img (np.ndarray): RGB image - rect (tuple): (x, y, w, h) - color (int): RED or BLUE (enum) - - Returns: - bool: True if the color of the roi is the same as the given color - """ - # Internal ENUM - RED = 0 - BLUE = 1 - - rgb_roi = rgb_img[rect[1]:rect[1] + rect[3], rect[0]:rect[0] + rect[2]] - sum_r = np.sum(rgb_roi[:, :, 0]) - sum_b = np.sum(rgb_roi[:, :, 2]) - if color == RED: - return sum_r >= sum_b - else: - return sum_b >= sum_r - - -def rect_contains(rect, pt): - """Determine if a pt is inside a rect. - - Args: - rect (tuple): (x, y, w, h) - pt (tuple): (x, y) - - Returns: - bool: True if the pt is inside the rect - """ - return rect[0] < pt[0] < rect[0] + \ - rect[2] and rect[1] < pt[1] < rect[1] + rect[3] - - -def get_intrinsic_matrix(cfg): - """Get the camera intrinsic matrix. - - Args: - cfg (object): config.py node object - - Returns: - K: camera intrinsic matrix 3x3 - """ - if hasattr(cfg, 'K'): - return cfg.K - elif hasattr(cfg.AUTOAIM_CAMERA, 'K'): - return cfg.AUTOAIM_CAMERA.K - else: - # Infer from image size - K = np.eye(3) - - H = cfg.IMG_HEIGHT - W = cfg.IMG_WIDTH - fl = min(H, W) * 2 - cx = W / 2 - cy = H / 2 - - K[0, 0] = fl - K[1, 1] = fl - K[0, 2] = cx - K[1, 2] = cy - - return K - - -def get_radian_diff(angle1, angle2): - """Compute the abs difference between two angles in radians. - - Parameters: - angle1 (float): First angle in radians. - angle2 (float): Second angle in radians. - - Returns: - float: The difference between the angles in radians, ranging from 0 to pi. - """ - # Normalize angles to be between 0 and 2*pi - angle1 = angle1 % (2 * np.pi) - angle2 = angle2 % (2 * np.pi) - - # Compute the difference along the lesser arc - diff = abs(angle1 - angle2) - if diff > np.pi: - diff = 2 * np.pi - diff - - return diff diff --git a/config.py b/config.py index eb510ff..dd877f7 100644 --- a/config.py +++ b/config.py @@ -1,29 +1,3 @@ -"""Config file that is shared across the whole project.""" - -# ========== Camera ========== -from Camera.read_from_file import fake_camera -from Camera.simple_cv import simple_cv_camera -# Define camera -# from Camera.d455 import D455_camera -# from Camera.mdvs import mdvs_camera -AUTOAIM_CAMERA = fake_camera - -# This param needs to be tuned per arena / camera setup -EXPOSURE_TIME = 5 - -# Compute some constants and define camera to use -IMG_HEIGHT = 512 -IMG_WIDTH = 640 - -IMG_CENTER_X = IMG_WIDTH // 2 -IMG_CENTER_Y = IMG_HEIGHT // 2 - -ROTATE_180 = True # Camera is mounted upside down - -# ========== Trajectory Modeling ========== -GRAVITY_CONSTANT = 9.81 # acceleration due to gravity -INITIAL_BULLET_SPEED = 15.0 # empirically measured - # ========== Communication ========== PACK_START = b'ST' PACK_END = b'ED' diff --git a/docs/comm_protocol.md b/docs/comm_protocol.md deleted file mode 100644 index f728622..0000000 --- a/docs/comm_protocol.md +++ /dev/null @@ -1,135 +0,0 @@ -# iRM Communication Protocol - -This documents the communication protocol design for exchanging information between -onboard Nvidia Jetson computers and the STM32 control board. - -For implementation on the STM32 side, please refer to the example [here](https://github.com/illini-robomaster/iRM_Embedded_2023/tree/main/examples/minipc). - -For implementation on the Jetson side, please refer to the main communicator [here](../Communication/communicator.py). - -# Protocol between Jetson and STM32 - -Note that the communication should always be single-sided (Otherwise we are reinventing TCP). A response should never **directly** depend on any data in previous packets. Example: send back `rel_pitch += 1` is an undefined behavior. - -## Packet Struct - -| Name | Content | Size | Offset | -|--------------|------------------------------------|---------------|----------------| -| HEADER | fixed 2 ASCII char ('ST') | 2 bytes | 0 | -| SEQ_NUM | uint16_t counter | 2 bytes | 2 | -| DATA_LEN | uint8_t length of the data section | 1 byte | 4 | -| CMD_ID | uint8_t identifier | 1 byte | 5 | -| DATA | struct with fixed length | n bytes | 6 | -| CRC_CHECKSUM | uint8_t checksum | 1 byte | PACKET_LEN - 3 | -| TAIL | fixed 2 ASCII char ('ED') | 2 bytes | PACKET_LEN - 2 | -| TOTAL | / | 10 - 21 bytes | / | - -## Detailed explanations - -Note: the memory layout of STM32 is **little-endian**. Hence when integers that require -decoding are sent, they need to be encoded in little endianness. However, for strings -(e.g., the HEADER ASCII and PACK_END ASCII), they do not need to be reversed since array -layouts are not affected by endianness. - -### HEADER - -2 ASCII chars This is the start of the packet denoted by ASCII characters 'ST'. - - -### SEQ_NUM - -uint16_t counter. This is a counter that is incremented by 1 every time a packet is sent. Restart from 0 when overflow. - -### DATA_LEN - -uint8_t length. The length of the data section (see below). Note this is not the length of the entire packet! Left here for future extension. Currently for all CMD_ID, the length of data is fixed and known. So this value is set to 0. - -### CMD_ID - -uint8_t identifier. - -| Name | ID | Data Length | Description | -|----------------|------|-------------|----------------------------------| -| GIMBAL_CMD_ID | 0x00 | 10 | Movement of the gimbal | -| COLOR_CMD_ID | 0x01 | 1 | My color, red is 0 and blue is 1 | -| CHASSIS_CMD_ID | 0x02 | 12 | Movement of the chassis | - -Packet length = Data length + 9 bytes _(Head length + Tail length + Checksum length)_ - -### DATA - -The followings are current data structs: - ---- - -#### gimbal_data_t - -| Name | Content | Size | Offset | -|-----------|-------------------------|---------|-----------------| -| rel_yaw | float32, relative yaw | 4 bytes | DATA_OFFSET + 0 | -| rel_pitch | float32, relative pitch | 4 bytes | DATA_OFFSET + 4 | -| mode | uint8_t, autoaim mode | 1 byte | DATA_OFFSET + 8 | -| debug_int | uint8_t, debug int | 1 byte | DATA_OFFSET + 9 | - -**mode**: Different modes for autoaim. Current options are 'ST' (0) and 'MY' (1), which stands for "Search Target" and "Move Yoke". - -- **ST == 0**: The "Search Target" mode means either 1) the AutoAim algorithm is not engaged - or 2) the AutoAim algorithm is engaged but the target is not found. In the former case, the - STM32 board should simply ignore input from the Jetson board. In the latter case, the STM32 - should hold pitch to the horizontal position, and rotate yaw to search for the target. -- **MY == 1**: The "Move Yoke" mode means the AutoAim algorithm is engaged and the target is found. - In this case, the relative pitch/yaw angles are sent to the STM32 board, and the gimbal - should move relatively to the current position. (**NOTE**: filtering to compensate for - latency and smoothness needs to be implemented on the STM32 side due to real-time access - to gimbal data.) - -**debug_int**: A int for debug for user. - ---- - -#### color_data_t - -| Name | Content | Size | Offset | -|----------|----------------------------|--------|-----------------| -| my_color | uint8_t, color of our team | 1 byte | DATA_OFFSET + 0 | - -**my_color**: RED is 0; BLUE is one - ---- - -#### chassis_data_t - -| Name | Content | Size | Offset | -|------|-----------------------------------------------|---------|-----------------| -| vx | float32, velocity to the front of the chassis | 4 bytes | DATA_OFFSET + 0 | -| vy | float32, velocity to the left of the chassis | 4 bytes | DATA_OFFSET + 4 | -| vw | float32, counterclockwise angular velocity | 4 bytes | DATA_OFFSET + 8 | - ---- - -### CRC_CHECKSUM - -uint8_t checksum. This is the CRC checksum of the packet. The CRC standard used -is the MAXIM_DOW standard. The CRC checksum is calculated on the packet contents BEFORE the -PACK_END (i.e., CRC is computed for the first (PACKET_LEN - 3) bytes up to end to REL_PITCH). - -### PACK_END - -2 ASCII chars. This is the end of the packet denoted by ASCII characters 'ED'. - -## Checklist: when adding a new packet type: - -### For Vision repo: -- In `communicator.py`, add data section packing to `create_packet_data()` -- In `communicator.py`, update `update_current_state()` and `parse_data()` -- In `communicator.py`, change `self.stm32_state_dict{}` in `__init__()` -- In `config.py`, add CMD_ID and update `CMD_TO_LEN[]` -- (Optional) If new whole packet length (header + tail + data > STJ_MAX_PACKET_LENGTH or < STJ_MIN_PACKET_LENGTH), in `communicator.py`, update `STJ_MAX_PACKET_LENGTH` and `STJ_MIN_PACKET_LENGTH`. - -### For Embedded repo: -- In `minipc_protocol.h`, add new data struct definition -- In `minipc_protocol.h`, change struct `status_data_t` -- In `minipc_protocol.h`, updaete `enum CMD_ID` and `CMD_TO_LEN[]` -- In `minipc_protocol.cc`, add data section packing to `Pack()` (you will need to add a helper function) -- In `minipc_protocol.cc`, add data section parsing to `ParseData()` -- (Optional) If new whole packet length (header + tail + data > MAX_PACKET_LENGTH or < MIN_PACKET_LENGTH), in `minipc_protocol.h`, update `MAX_PACKET_LENGTH` and `MIN_PACKET_LENGTH`. diff --git a/examples/filtering_sample.ipynb b/examples/filtering_sample.ipynb deleted file mode 100644 index bbd0e33..0000000 --- a/examples/filtering_sample.ipynb +++ /dev/null @@ -1,246 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "bba7d274", - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import numpy as np\n", - "import scipy.interpolate\n", - "import matplotlib.pyplot as plt" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "333c60c4", - "metadata": {}, - "outputs": [], - "source": [ - "np.random.seed(42)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "c48c7b0e", - "metadata": {}, - "outputs": [], - "source": [ - "# Generate simulation data\n", - "\n", - "# Gimbal control freq (in Hz)\n", - "gimbal_freq = 1000\n", - "\n", - "# Actual freq on jetson (in Hz)\n", - "jetson_freq = 50\n", - "\n", - "gimbal_t = np.linspace(0, 1, gimbal_freq)\n", - "jetson_t = np.linspace(0, 1, jetson_freq)\n", - "\n", - "gt_gimbal_signal = np.sin(2 * np.pi * gimbal_t)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "6aebfa4d", - "metadata": {}, - "outputs": [], - "source": [ - "jetson_noise_std = 0.1\n", - "\n", - "jetson_idx = np.round(np.linspace(0, gimbal_freq - 1, jetson_freq)).astype(int)\n", - "jetson_signal = gt_gimbal_signal[jetson_idx]\n", - "\n", - "jetson_signal = jetson_signal + np.random.normal(scale=jetson_noise_std, size=jetson_signal.shape)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "9436a6d7", - "metadata": {}, - "outputs": [], - "source": [ - "inter_func = scipy.interpolate.interp1d(jetson_t, jetson_signal, kind='previous')\n", - "extrapolated_signal = inter_func(gimbal_t)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "0ce72da8", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(9, 6))\n", - "plt.xlabel(\"Time (seconds)\")\n", - "plt.ylabel(\"Yaw angle (rads)\")\n", - "plt.step(gimbal_t, gt_gimbal_signal, label=\"Reference val\", where='post')\n", - "plt.step(jetson_t, jetson_signal, label=\"Jetson val\", where='post')\n", - "# plt.step(gimbal_t, extrapolate_jetson_signal, label=\"Extrapolated Jetson val\")\n", - "plt.legend()" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "9a012d3a", - "metadata": {}, - "outputs": [], - "source": [ - "# Recursive variables\n", - "xhat = 0 # posterior\n", - "xhatminus = 0 # a priori\n", - "\n", - "P = 0 # posterior variance estimation\n", - "Pminus = 0 # a priori variance estimation\n", - "K = np.array([0, 0]) # Kalman gain\n", - "\n", - "# Constant modeling variables\n", - "Q = 1 # noise variance\n", - "\n", - "H = 1\n", - "\n", - "A = 1 # state transition\n", - "B = 0 # control transition\n", - "\n", - "R = 20 # state variance\n", - "\n", - "xhat_list = []\n", - "\n", - "jetson_signal_ptr = 0\n", - "\n", - "last_signal = 0\n", - "last_last_signal = 0\n", - "\n", - "last_t = 0.1\n", - "last_last_t = -1\n", - "\n", - "for i in range(gimbal_freq):\n", - " if jetson_signal_ptr < len(jetson_t) and gimbal_t[i] >= jetson_t[jetson_signal_ptr]:\n", - " last_last_signal = last_signal\n", - " last_signal = jetson_signal[jetson_signal_ptr]\n", - " last_last_t = last_t\n", - " last_t = jetson_t[jetson_signal_ptr]\n", - " jetson_signal_ptr += 1\n", - " # state transition: A @ xhat + B @ u + N\n", - " xhatminus = A * xhat + B\n", - " Pminus = A*P*A + Q\n", - " K = Pminus * H / (H * Pminus * H + R)\n", - " \n", - " # Update with pseudo posteriori observation\n", - " xhat = xhatminus + K * (extrapolated_signal[i] - H * xhatminus)\n", - " xhat_list.append(xhat)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "aacef2ec", - "metadata": {}, - "outputs": [], - "source": [ - "xhat_arr = np.array(xhat_list)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "fcfdf560", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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"nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.15" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/examples/test_1.jpg b/examples/test_1.jpg deleted file mode 100644 index 46d9d88a5159f6dc9366c26e8698f3bfa3ec5aff..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 6641435 zcmc$_cT`hfw>BD7L_|P(6HzHj7wJX#Sr7ps(mM!<5Mqc3Na%|676AbTA<{dM5;}yA zf`AZes7WZ&6TlE5gq!!A_q^x({=4J;b9Y8YR`yt9?)j{>_FQw$XRg!fQ=CzjE)4Vn z05CEFNC5zV3xM+soPe|R76bhQU=Rc_{#P3Suw)SWPur2<*1!9l0RYZ${crzh5a8Uu z`_p9tI_TfW|Nj5qzf2zh04DmKbGPr@QAlR^?>57kvw*Mvb6?^1?XL{~EAi`@|B=Yv z@%8Ngv{`-?od0(py0HJc&NH0-_nq_qr``-~|Eo6x@BgJY!~aNQxO(P4PkG|=Z+ZWh z-lx;2vw#Qy!~fsc={#NMi>Dm`jtc-7;Okk28-Oz$3}-nQPJ0;g=&%|8Tfu)r0MG~a z9OHSW3(OZ;E(6XmoIQKy+*wA(bMz@<2>I8bpW|TUysmKXJeP?x(+zL#JMWTnFNof+ z?&L8YC5kD!ybfo+$jiqsASf%2o%)I=9!lL4m(z2S`I#hi_V^ecicTaC$ z|MwpQW0>)Y$*JiXEDldtURhoHy}m)(+due2KBW9TqOXGgjQ4*d`ake+(D9r(ckb*t 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