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---
name: Any other question or issue
about: Any other question or issue
title: ''
labels: ''
assignees: ''
---
If something doesnt work for you, then show 2 screenshots:
1. screenshots of your issue
2. screenshots with such information
```
./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
0 conv 32 3 x 3/ 1 608 x 608 x 3 -> 608 x 608 x 32 0.639 BF
```
If you do not get an answer for a long time, try to find the answer among Issues with a Solved label: https://github.com/AlexeyAB/darknet/issues?q=is%3Aopen+is%3Aissue+label%3ASolved

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---
name: Bug report
about: Create a report to help us improve
title: ''
labels: ''
assignees: ''
---
If you want to report a bug - provide:
* description of a bug
* what command do you use?
* do you use Win/Linux/Mac?
* attach screenshot of a bug with previous messages in terminal
* in what cases a bug occurs, and in which not?
* if possible, specify date/commit of Darknet that works without this bug
* 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
```

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---
name: Feature request
about: Suggest an idea for this project
title: ''
labels: Feature-request
assignees: ''
---
For Feature-request:
* describe your feature as detailed as possible
* provide link to the paper and/or source code if it exist
* attach chart/table with comparison that shows improvement

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name: Training issue - no-detections / Nan avg-loss / low accuracy
about: Training issue - no-detections / Nan avg-loss / low accuracy
title: ''
labels: Training issue
assignees: ''
---
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
```