How to get the accuracy of test or valid in classification? Not Top1 or Topk. Such as "- map"

[zhen-yan]

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

[Dickoabc123]

Hello @zhen-yan did you manage to solve this? I too would like to know the training and validation losses for each Epoch along with the mAP for each Epoch. @AlexeyAB do you know how we can achieve this? This is very important for analysing the performance of the models.