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Very low loss but no detection on images #7307
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I have the same issue... |
I have changed the Network Size to 768x768 and the division to 64. And now I now get following output for mAP for around 3k Batches:
And I also got some good detections for manual testing some of my images. I think darknet was not able to see the objects which I wanted to be detected. I will run the training to finish and share my results here. |
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@versavel I do have annotations in the .txt Files of the Testing Images. I use all of my training images as Validation Images. |
read FAQ: https://github.com/AlexeyAB/darknet/wiki/FAQ---frequently-asked-questions
I have read the FAQ and
what command do you use?
detector train .\yolo.data .\yolov3_license_plate.cfg .\yolov3_license_plate_last.weights
what dataset do you use?
I use a custom dataset with german license plates. Examples can be found in the attachment.
what Loss and mAP did you get?
I do get a Loss of around 0.0034 and a mAP of (TP = 0, FP = 0) after 5k of Iterations
show chart.png with Loss and mAP
It is in the attachment
check your dataset - run training with flag
-show_imgs
i.e../darknet detector train ... -show_imgs
and look at theaug_...jpg
images, do you see correct truth bounded boxes?I do see the correct bounding boxes
rename your cfg-file to txt-file and drag-n-drop (attach) to your message here
it is
show content of generated files
bad.list
andbad_label.list
if they existThere are no files.
Aug-Files:
aug-images.zip
Config-File:
yolov3_license_plate.txt
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