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Merge pull request #635 from JdeRobot/issue-633
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Added CARLA examples for GUI and non-GUI pipelines
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sergiopaniego authored Sep 20, 2023
2 parents a80c972 + be166a9 commit 0a18e0a
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1 change: 1 addition & 0 deletions .gitignore
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*.max

*.h5
*.pth

### Python ###
# Byte-compiled / optimized / DLL files
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54 changes: 47 additions & 7 deletions README.md
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[![Publish cuda 11 Docker image](https://github.com/JdeRobot/BehaviorMetrics/actions/workflows/generate_docker_cuda_11.yml/badge.svg)](https://github.com/JdeRobot/BehaviorMetrics/actions/workflows/generate_docker_cuda_11.yml)
# Behavior Metrics

This project presents different approaches to the follow-the-line exercise but using artificial intelligence to complete the circuits. The solutions presented are:
- Using classification networks.
- Using regression networks.
- Using reinforcement learning.
- Solution for real robots.
This software tool provides evaluation capabilities for autonomous driving solutions using simulation.
We provide a series of quantitative metrics for the evaluation of autonomous driving solutions with support for two simulators, [CARLA](https://carla.org/) (main supported simulator) and [gazebo](https://gazebosim.org/home) (partial support).
Currently supported tasks include:

For more information about the project you can consult the [website of Behavior Metrics](https://jderobot.github.io/BehaviorMetrics/).
* Follow-lane
* Driving in traffic
* Navigation

Each task comes with its own custom evaluation metrics that can help compare autonomous driving solutions.
The main component of the ego vehicle is the brain, which receives sensor data, manipulates it, and generates robot control commands based on it.
The inner part of the brain can be controlled by an end-to-end model, written in Tensorflow or PyTorch, a reinforcement learning policy, or even an explicitly programmed policy.

The software provides two main pipelines, a graphical user interface (GUI) and a headless mode (scripted).
The first one is intended for testing one brain+model at a time and debugging it visually while the headless mode is intended for running lots of experiments at the same time for comparison of a batch of brain+models in different scenarios.

<img src="./assets/behavior_metrics_full_architecture.png" alt="architecture"/>

### Installation

For more information about the project and how to install it, you can consult the [website of Behavior Metrics](https://jderobot.github.io/BehaviorMetrics/).

### Examples

We provide examples for the follow-lane task using CARLA:

* For an example of a robot brain using a Tensorflow model for control with GUI pipeline, run:

```
python3 driver_carla.py -c configs/CARLA/default_carla_tensorflow.yml -g
```

* For an example of a robot brain using a PyTorch model for control with GUI pipeline, run:

```
python3 driver_carla.py -c configs/CARLA/default_carla_torch.yml -g
```

* For an example of an explicitly programmed robot brain with GUI pipeline, run:

```
python3 driver_carla.py -c configs/CARLA/default_carla.yml -g
```

* For an example of the headless pipeline, run:

```
python3 driver_carla.py -c configs/CARLA/default_carla_multiple.yml -s
```

### Contributing to the project

If you want to contribute, please first check out [CONTRIBUTING.md](CONTRIBUTING.md) section.

<img src="https://jderobot.github.io/assets/images/projects/neural_behavior/autonomous.jpeg" alt="config" style="zoom:20%;" />
<img src="./assets/behavior_metrics_full_architecture.png" alt="architecture"/>
4 changes: 3 additions & 1 deletion behavior_metrics/brains/CARLA/brain_carla_slow_and_turn.py
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Expand Up @@ -65,7 +65,9 @@ def execute(self):
image_2 = self.camera_2.getImage().data
image_3 = self.camera_3.getImage().data

self.motors.sendThrottle(1)
self.motors.sendThrottle(0.5)
self.motors.sendSteer(0.05)

self.update_frame('frame_0', image)
self.update_frame('frame_1', image_1)
self.update_frame('frame_2', image_2)
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from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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from PIL import Image
from brains.f1.torch_utils.pilotnet import PilotNet
from brains.CARLA.pytorch.utils.pilotnet import PilotNet
from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH
from os import path
from albumentations import (
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import math
import carla

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'
FLOAT = torch.FloatTensor

class Brain:
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from PIL import Image
from brains.f1.torch_utils.pilotnet import PilotNet
from brains.CARLA.pytorch.utils.pilotnet import PilotNet
from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH
from os import path
from albumentations import (
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import math
import carla

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'
FLOAT = torch.FloatTensor

class Brain:
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from PIL import Image
from brains.f1.torch_utils.pilotnet import PilotNet
from brains.CARLA.pytorch.utils.pilotnet import PilotNet
from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH
from os import path
from albumentations import (
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import math
import carla

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'
FLOAT = torch.FloatTensor

class Brain:
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from PIL import Image
from brains.f1.torch_utils.pilotnet import PilotNet
from brains.CARLA.pytorch.utils.pilotnet import PilotNet
from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH
from os import path
from albumentations import (
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import math
import carla

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'
FLOAT = torch.FloatTensor

class Brain:
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from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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self.update_pose(self.pose.getPose3d())

image_shape=(66, 200)
#image_shape=(50, 150)
img_base = cv2.resize(bird_eye_view_1, image_shape)

AUGMENTATIONS_TEST = Compose([
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from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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Expand Up @@ -15,7 +15,7 @@
from utils.logger import logger
from traceback import print_exc

PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/'
PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/'

from tensorflow.python.framework.errors_impl import NotFoundError
from tensorflow.python.framework.errors_impl import UnimplementedError
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8 changes: 6 additions & 2 deletions behavior_metrics/brains/brains_handler.py
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Expand Up @@ -34,9 +34,13 @@ def __init__(self, sensors, actuators, brain_path, controller, model=None, confi
def load_brain(self, path, model=None):

path_split = path.split("/")
robot_type = path_split[-2]
robot_type = path_split[1]
module_name = path_split[-1][:-3] # removing .py extension
import_name = 'brains.' + robot_type + '.' + module_name
if len(path_split) == 4:
framework = path_split[2]
import_name = 'brains.' + robot_type + '.' + framework + '.' + module_name
else:
import_name = 'brains.' + robot_type + '.' + module_name

if robot_type == 'CARLA':
module = importlib.import_module(import_name)
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import tensorflow as tf
from gym.envs.registration import register
from brains.f1.rl_utils.inference import InferencerWrapper
from brains.gazebo.f1.rl_utils.inference import InferencerWrapper
import yaml
import gym
import numpy as np
Expand All @@ -11,7 +11,7 @@
if 'F1Env-v0' not in gym.envs.registry.env_specs:
gym.envs.register(
id='F1Env-v0',
entry_point='brains.f1.rl_utils.models:F1Env',
entry_point='brains.gazebo.f1.rl_utils.models:F1Env',
# More arguments here
)
else:
Expand Down Expand Up @@ -154,7 +154,7 @@ def __init__(self, sensors, actuators, handler, config=None):
'algorithm': 'dqn',
'environment': 'simple',
'agent': 'f1',
'filename': 'brains/f1/config/config_inference_followline_dqn_f1_gazebo.yaml'
'filename': 'brains/gazebo/f1/config/config_inference_followline_dqn_f1_gazebo.yaml'
}

f = open(args['filename'], "r")
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