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Wovchena avatar Wovchena commented on June 8, 2024

The size specified in accuracy-check.yml is actual model input size for the accuracy so that we able to achieve 42% map. README.md states the shape that you get after the model is converted. That's a common "technique" when shape for inference doesn't match the shape for accuracy.

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Ai-econ avatar Ai-econ commented on June 8, 2024

Thanks a lot for quick response

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eaidova avatar eaidova commented on June 8, 2024

@Ai-econ for achieving accurate results model required preserving aspect ratio of input image, during accruacy validation model input was reshaped according provided preprocessing rules

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Ai-econ avatar Ai-econ commented on June 8, 2024

@eaidova Where i can find preprocessing rules or guidelines so we can follow the same

If i am not wrong, model was trained with higher resolution which results in good accuracy. However if we deploy the model with lower resolution just by converting model input shape will leads to decrease my accuracy and issue in extracting features right ?

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eaidova avatar eaidova commented on June 8, 2024

@Ai-econ they provided in accuracy checker config preprocessing section. Image resized with preserving aspect ratio, where height size will be 368 and width resized according to these rules

def scale_width(dst_width, dst_height, image_width, image_height,):
and then if image height or width not divisible to 8, it will be additionally padded.

To sum up, resolution used for accuracy evaluation will depends from image size and it is bigger then provided by default (in model, default height - 256, while in accuracy - 368).

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