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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
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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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