Comments (7)
Hello. I think you can print these images out to see whether they have something wrong. Sometimes the values maybe not so important, they can be rescaled when you output them as images.
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okay, thanks a lot @Coldog2333; and I find that on line214, train.py, the check_point should be corrected to check_loss, which is used to replace original check_loss = 1.
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Oh, thank you for your reminder!
(It has been corrected.)
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I remember that I checked all of the codes on my machine before pushing them. Maybe I should check it once again. (If I have time...)
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fine, and your contribution is really useful for my work~
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Glad to hear that. Thank you for your appreciation. :)
If you have any other questions, just feel free to new an issue.
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Hello, I check the codes of this repository today and figure out the reason for the problem you encountered.
This is a bug or something like updated feature of matplotlib.
If you use a matplotlib with version like 2.0.2, the problem will not occur.
reference: matterport/Mask_RCNN#69
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Related Issues (19)
- information about trained models HOT 1
- TypeError: __init__() missing 1 required positional argument: 'task' HOT 3
- SR results not clear HOT 2
- Why SR results is one output image? HOT 4
- 2x model HOT 4
- Issue in SSIM implementation HOT 2
- evaluate.py can only output 1 frame from 7 LR frames? HOT 1
- some error
- Question About Super Resolution HOT 1
- the mask network
- run.py has some detail to modify
- ValueError: Floating point image RGB values must be in the 0..1 range.
- "tiny.zip" download link failed! HOT 2
- About the evaluation results HOT 3
- A question about the performance against the official implementation HOT 1
- run.py forward() takes 2 positional arguments but 3 were given HOT 4
- VHS Denoise Model + Training Set HOT 2
- License?
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