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The results of yolo v3 detector are different. #602

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DeHysolate opened this issue Apr 9, 2018 · 8 comments
Open

The results of yolo v3 detector are different. #602

DeHysolate opened this issue Apr 9, 2018 · 8 comments

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@DeHysolate
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DeHysolate commented Apr 9, 2018

I used the same cfg, weight and same image, but the results of running pjreddie / darknet in a Linux environment and AlexeyAB / darknet in a Windows environment are different.

I wonder what causes this result.

@DeHysolate DeHysolate changed the title The results of yolo_v3 detector are different. The results of yolo v3 detector are different. Apr 9, 2018
@XP-CHRC
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XP-CHRC commented Apr 9, 2018

In ubuntu16.04, same cfg and weights, the AlexeyAB/darknet is better than the pjreddie/darknet, maybe you can check the function test_detector under the file detector.c, there are some differences.

@DeHysolate
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DeHysolate commented Apr 9, 2018

@XP-CHRC
I compared the original and AlexeyAB's, but found no significant change.
When the original and AlexeyAB's are using the same cfg and weight, does the result differ?

@AlexeyAB
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AlexeyAB commented Apr 9, 2018

@DeHysolate

  • Can you show whole command that you used?
  • Check that you didn't specify -thresh in the command.
  • Did you use default coco-model yolov3.weights or trained by yourself?
  • Can you drag-n-drop this original image (without bound boxes) to next message here? I'll try to detect.

@DeHysolate
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DeHysolate commented Apr 9, 2018

@AlexeyAB

  • Can you show whole command that you used?

detector test coco.data yolov3_train.cfg yolov3_train.weights save.jpg -i 0 -thresh 0.25

  • Check that you didn't specify -thresh in the command.

thresh 0.25

  • Did you use default coco-model yolov3.weights or trained by yourself?

myself based on yolov3.weight

  • Can you drag-n-drop this original image (without bound boxes) to next message here? I'll try to detect.

Now I'm out and I can not capture it.

@AlexeyAB
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AlexeyAB commented Apr 9, 2018

@DeHysolate Can you get different results on original / fork repositories using the default yolov3.weights model?

@DeHysolate
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@AlexeyAB I'll try it tomorrow and upload image because I'm out now. Thanks for your kindness!!

@DeHysolate
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DeHysolate commented Apr 10, 2018

@AlexeyAB
Result of using default weight (coco-model yolov3.weight)
The bounding box results are slightly different.
The probability results are also different. (origianl:100%,99% / fork:100%,97%)

@AlexeyAB
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@DeHysolate
Yes, there is a little difference due to different resize approaches: #232 (comment)

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