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Update issue templates

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---
name: 'Bug report or Training issue '
about: Create a report to help us improve
title: ''
labels: ''
assignees: ''
---
Read the recommendations below if you want to make a Bug report, ask a Training question or request a Feature.
1. 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
```
----
2. If you have an issue with training - no-detections / Nan avg-loss / low accuracy:
* 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
```
----
3. 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