Comments (4)
I tested this solution on Wider Face validation dataset for both cases(RGB and BGR) and got next results:
For BGR images(using code from readme file at this repo):
==================== Results ====================
Easy Val AP: 0.5647998370785989
Medium Val AP: 0.5219529625700366
Hard Val AP: 0.2856212575529135
For RGB images(with converting to RGB after image reading):
==================== Results ====================
Easy Val AP: 0.8069582917049369
Medium Val AP: 0.7637617089872778
Hard Val AP: 0.4867522878479363
So, there should be converting to RGB format before processing.
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@nyck33 For the blue output images, you can change the colormap of the image before cv2.imwrite()
by doing image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
and passing it to cv2.imwrite()
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@Andriy963 @acnazarejr Great to know, I just posted on StackExchange about this how pyplot.imread()
was giving better results than the cv2.imread()
However, now my output when I cv2.imwrite()
looks very blue.
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@acnazarejr @Andriy963 @nyck33 @raviam @akofman
Can you please tell me, which script is suitable to get the boundary box details as ".data" format, for my dataset (OULU),
Thanks in advance
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