Hello
Does the conversion from tensorflow frozen model of TinyYoloV3 to OpenVINO IR require the --reverse-input-channels flag for mo_tf.py? I know it is required for TF ssdv2 model. From my experiments, the Coco trained TinyYoloV3 seems to perform better when using the --reverse-input-channels flag.
Thank you!
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Hi Ra,
It is not required to use the --reverse_input_channels parameter when converting YOLOv3-Tiny. Below is the general conversion command:
python3 mo_t.f.py --input_model /path/to/yolo_v3_tiny.pb --tensorflow_use_custom_operations_config $MO_ROOT/extensions/front/tf/yolo_v3_tiny.json --batch 1
However, in general the color channel order (RG>B or BGR) of the input data should match the channel order of the model training dataset.
For more information about when to reverse input channels, see this documentation.
I hope this information is helpful.
Sincerely,
Sahira
To me it looks like the model performs better with reverse input channels.
My logic is that darknet, just like tf, uses rgb, while OpenVINO uses cv2 order of bgr
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