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A YOLOv3 object detector to identify people and traffic signs on OpenImageV6 1.6M images

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parthkvv/YOLOv3_Traffic_Sign_Detection

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Dataset Preparation

All the image files will reside in multiple folders. Copy or move all the images from different folders to one single folder.

Create a new folder under rgb/train and rename it as rgb/train/traffic_light_images.

Move the yolov3-tiny-bosch.cfg from the \config folder to the same (traffic_lights) folder. Mae sure there are following files in the traffic_lights folder.

  • train.txt
  • test.txt
  • bosch.data
  • bosch.names
  • yolov3-tiny-bosch.cfg
  • backup folder which stores the weights

Download the yolov3 imagenet darknet53 weights Run the following on terminal for training the model

cd darknet
./darknet detector train traffic_lights/bosch.data traffic_lights/yolov3-tiny-bosch.cfg darknet53.conv.74

Testing

cd darknet
./darknet detector demo traffic_lights/bosch.data traffic_lights/yolov3-tiny-bosch.cfg traffic_lights/backup/<weight_file> <video file>

Actual testing was done on OpenImageV6 images.

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A YOLOv3 object detector to identify people and traffic signs on OpenImageV6 1.6M images

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