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valid mAP much higher than the original darknet using the same weights trained by this repo #3478
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@yanxurui Hi, The latest version of this repo supports 2 approaches of resizing: #232 (comment)
While pjreddie/darknet and ultralytics/yolov3 supports only letter_box. |
@AlexeyAB |
@yanxurui Also if you use this repository, then download the latest version. Only in the last commit was added |
Great. I still don't understand one thing. |
Another question. |
I don't understand it too :) I got higher mAP on original weights-file (that is trained with letter_box) by using resizing than by using letter_box during detection.
Have you downloaded the latest version of Darknet? |
No. I am not using the latest version But I do see this option in my detector.c. |
For checking mAP - yes. For detection - several monthes ago. |
Great. |
Hi @AlexeyAB
I have trained this repo on a custom dataset.
I want to compute mAP on the validation set.
I run this command:
./darknet detector valid cfg/bdd.data cfg/yolov3-bdd.cfg backup/yolov3-bdd_30000.weights
Then compute the mAP using cocoapi on the result json file.
The mAP is around 16%.
I run the same command using the original darknet repo with config and weights being replaced with the same files.
The mAP is around 10%.
I also use ultralytics/yolov3 to calculate mAP which is around 10%.
So, why do the weights trained by this repo perform worse when using the original repo to do validation?
Thank you very much.
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