1.4 KiB
name | about | title | labels | assignees |
---|---|---|---|---|
Training issue - no-detections / Nan avg-loss / low accuracy | Training issue - no-detections / Nan avg-loss / low accuracy | Training issue |
If you have an issue with training - no-detections / Nan avg-loss / low accuracy:
* read FAQ: https://github.com/AlexeyAB/darknet/wiki/FAQ---frequently-asked-questions
* what command do you use?
* what dataset do you use?
* what Loss and mAP did you get?
* show chart.png with Loss and mAP
* check your dataset - run training with flag -show_imgs
i.e. ./darknet detector train ... -show_imgs
and look at the aug_...jpg
images, do you see correct truth bounded boxes?
* rename your cfg-file to txt-file and drag-n-drop (attach) to your message here
* show content of generated files bad.list
and bad_label.list
if they exist
* Read How to train (to detect your custom objects)
and How to improve object detection
in the Readme: https://github.com/AlexeyAB/darknet/blob/master/README.md
* show such screenshot with info
./darknet detector test cfg/coco.data cfg/yolov4.cfg yolov4.weights data/dog.jpg
CUDA-version: 10000 (10000), cuDNN: 7.4.2, CUDNN_HALF=1, GPU count: 1
CUDNN_HALF=1
OpenCV version: 4.2.0
0 : compute_capability = 750, cudnn_half = 1, GPU: GeForce RTX 2070
net.optimized_memory = 0
mini_batch = 1, batch = 8, time_steps = 1, train = 0
layer filters size/strd(dil) input output