After training the yolov3 network, the prediction is normal.but when training the tiny-yolov3,there was no bounding boxes.Everything follows the training steps. I successfully trained tiny-yolov3 for the first time and predicted the result, but this time it won’t work.
hi,Have you solved this problem? I also encountered the same problem, tiny-yolov3 has no prediction result.
hi,Have you solved this problem? I also encountered the same problem, tiny-yolov3 has no prediction result.
Problem solved successfully!
There are some issues in the source code.
anchor_mask = [[6,7,8], [3,4,5], [0,1,2]] if num_layers==3 else [[3,4,5], [1,2,3]]
please change all [1,2,3] to [0,1,2]
anchor_mask = [[6,7,8], [3,4,5], [0,1,2]] if num_layers==3 else [[3,4,5], [0,1,2]]
I remember there should be three mistakes
then retrain the tiny_model
thank you
hi,Have you solved this problem? I also encountered the same problem, tiny-yolov3 has no prediction result.
Problem solved successfully!
There are some issues in the source code.yolo3/model.py
anchor_mask = [[6,7,8], [3,4,5], [0,1,2]] if num_layers==3 else [[3,4,5], [1,2,3]]
please change all [1,2,3] to [0,1,2]
anchor_mask = [[6,7,8], [3,4,5], [0,1,2]] if num_layers==3 else [[3,4,5], [0,1,2]]
I remember there should be three mistakes
then retrain the tiny_model
请问是将cfg里面的mask也改成[[3,4,5], [0,1,2]]然后重新训练吗
I have the same problem, When I find "[[3,4,5], [1,2,3]]", Let me test it. But why? I do not think it is a bug.
The original darknet was updated on August 16, 2018.
https://github.com/pjreddie/darknet/commit/f86901f6177dfc6116360a13cc06ab680e0c86b0#diff-2b0e16f442a744897f1606ff1a0f99d3 ...
However, this repository (qqwweee/keras-yolo3) was last updated on July 31, 2018, so the above changes do not appear to have been applied.
Most helpful comment
Problem solved successfully!
There are some issues in the source code.
yolo3/model.py
anchor_mask = [[6,7,8], [3,4,5], [0,1,2]] if num_layers==3 else [[3,4,5], [1,2,3]]please change all [1,2,3] to [0,1,2]
anchor_mask = [[6,7,8], [3,4,5], [0,1,2]] if num_layers==3 else [[3,4,5], [0,1,2]]I remember there should be three mistakes
then retrain the tiny_model