tensorflow-yolov4-tiny

Adapted from https://github.com/mystic123/tensorflow-yolo-v3

Refer to how this version(https://github.com/TNTWEN/OpenVINO-YOLOV4) handles split

Tested on Python 3.6, tensorflow 1.14.0, Ubuntu 18.04, l_openvino_toolkit_p_2020.3.194/2020.4.287

Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz fps=30

Todo list:

• Weights converter to pb
• Syns detect yolo

How to work:

1. Download COCO class names file: wget https://raw.githubusercontent.com/pjreddie/darknet/master/data/coco.names
2. Download v4-Tiny weights:
   wget https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4-tiny.weights
3. Run python convert_weights_pb.py
4. Pb converter to IR cp ./yolo_v4_tiny.json /opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf cd /opt/intel/openvino/deployment_tools/model_optimizer python mo.py --input_model yolov4-tiny.pb --transformations_config ./extensions/front/tf/yolo_v4_tiny.json --batch 1
5. Openvino-Object Detection YOLO* Python Demo python sync_detection_yolo.py

####Optional Flags

1. convert_weights_pb.py:
   1. --class_names
      1. Path to the class names file
   2. --weights_file
      1. Path to the desired weights file
   3. --data_format
      1. NCHW (gpu only) or NHWC
   4. --tiny
      1. Use yolov4-tiny
   5. --output_graph
      1. Location to write the output .pb graph to
2. sync_detection_yolo.py:
   1. -m
      1. Path to an .xml file with a trained model.
   2. -labels
      1. Path to the coco.names