LiweiPE-Object_detection_drinks

This reasearch was develop to detect many soft drinks or snacks taking out from vending machine.

Configuration environment

conda activate tf1.15

• pip install imageio

Dataset

Images annotations have to be changed to xmal format Whole raw dataset can be found at /data/vending Training dataset to detect one object can be found at /data/home/liwei/ImageAI/vending_machine Training dataset to detect more than two objects at the same time can be found at /data/home/liwei/ImageAI/vending_machine_dual

Training

The following example is used to detect different custom objects

from imageai.Detection.Custom import DetectionModelTrainer

trainer = DetectionModelTrainer()
trainer.setModelTypeAsYOLOv3()
trainer.setGpuUsage(train_gpus="0,1,2,3,4,5,6,7")
trainer.setDataDirectory(data_directory="vending_machine")
# trainer.setTrainConfig(object_names_array=["orange_juice"], batch_size=8, num_experiments=10,train_from_pretrained_model="pretrained-yolov3.h5")
trainer.setTrainConfig(object_names_array=["pepsi","water","orange_juice","cucumber_soda","C100_juice","pepsi_330","HongNiu","Wangzi_milk","Wanglaoji","Beibingyang","Asamu_milktea","Harbin_beer","Kangshifu_juice","Maidong_lime","Dongfang_greentea"],
                       batch_size=32, num_experiments=10,train_from_pretrained_model="vending_machine/models_all_25-11/detection_model-ex-010--loss-0007.615.h5")
trainer.trainModel()

Training file for one custom object detection

$ python vending_machine.py

Training file for multiple custom object detection

$ python vending_machine_dual.py

Test

$ python test_video.py

Example for testing video:

from imageai.Detection.Custom import CustomVideoObjectDetection
import os

execution_path = os.getcwd()
video_detector = CustomVideoObjectDetection()
video_detector.setModelTypeAsYOLOv3()
video_detector.setModelPath("vending_machine_dual/models1/detection_model-ex-039--loss-0011.630.h5")
video_detector.setJsonPath("vending_machine_dual/json1/detection_config.json")
video_detector.loadModel()

video_detector.detectObjectsFromVideo(input_file_path="01茅聬隆忙茠掳卯鈥斉犆┞惵ヂ徛ッ溍┞嶁劉卯藛鈩⒚?00氓搂拢卯鈥毬⒚ヂ磁?忙聬麓氓鲁掳莽卢鈧┞嵟捗モ€樎モ€⒙好宦?颅忙麓漏氓搂艩?00氓搂拢卯鈥毬⒚ヂ磁捗┞嶁劉氓鈥︹€γ€?avi",
                                          output_file_path=os.path.join(execution_path, "pepsi_kangshifu%"),
                                          frames_per_second=30,
                                          minimum_percentage_probability=50,
                                          log_progress=True)

Images samples detection

Single object: Orange juice 500ml

Multiple object: Pepsi 500ml, Cucumber soda 500ml, Water 500ml

Video detection: Pepsi 500ml

Citation

@misc {ImageAI, author = "Moses and John Olafenwa", title = "ImageAI, an open source python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities", url = "https://github.com/OlafenwaMoses/ImageAI", month = "mar", year = "2018--" }