As shown in the title, Could you tell me maybe some step is wrong in my process ?
- I have trained a YOLOV3 model for defect detection by keras and convert .h5 to .weights file.(just modify the file name)
- Following the code convert to .pb file.
python3 convert_weights_pb.py --class_names voc_C1.txt --data_format NHWC --weights_file trained_weights_final.weights
3.Following the code convert .pb to IR.
python3 mo_tf.py --input_model /path/to/frozen_darknet_yolov3_model.pb --tensorflow_use_custom_operations_config data.json --batch 1
4.data.json I just modify classes from 80 to 2(number of my classes)
5.Attachments are my trained_weights_final.h5, voc_C1.txt and data.json.
Thanks for your help,hope to get the news soon.
Dear huang, kuang chieh,
you left off "anchors" in your *.json file - which will probably cause Model Optimizer to produce incorrect IR.
"anchors": [10, 13, 16, 30, 33, 23, 30, 61, 62, 45, 59, 119, 116, 90, 156, 198, 373, 326],
Here is the Official Model Optimizer Yolo document you should follow. I see that you are starting with a keras model (*.h5 extension) but you must convert that to a frozen Tensorflow pb first. Model Optimizer doesn't work with Keras directly.
Hope it helps,