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| | | 3. [How to train (Pascal VOC Data)](#how-to-train-pascal-voc-data) |
| | | 4. [How to train (to detect your custom objects)](#how-to-train-to-detect-your-custom-objects) |
| | | 5. [When should I stop training](#when-should-i-stop-training) |
| | | 6. [How to mark bounded boxes of objects and create annotation files](#how-to-mark-bounded-boxes-of-objects-and-create-annotation-files) |
| | | 6. [How to improve object detection](#how-to-improve-object-detection) |
| | | 7. [How to mark bounded boxes of objects and create annotation files](#how-to-mark-bounded-boxes-of-objects-and-create-annotation-files) |
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| | | |  |  https://arxiv.org/abs/1612.08242 | |
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| | | ## How to improve object detection: |
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| | | 1. Before training: |
| | | * set flag `random=1` in your `.cfg`-file - it will increase precision by training Yolo for different resolutions: [link](https://github.com/AlexeyAB/darknet/blob/47409529d0eb935fa7bafbe2b3484431117269f5/cfg/yolo-voc.cfg#L244) |
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| | | 2. After training - for detection: |
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| | | * Increase network-resolution by set in your `.cfg`-file (`height=608` and `width=608`) or (`height=832` and `width=832`) or (any value multiple of 32): [link](https://github.com/AlexeyAB/darknet/blob/47409529d0eb935fa7bafbe2b3484431117269f5/cfg/yolo-voc.cfg#L4) |
| | | * you do not need to train the network again, just use `.weights`-file already trained for 416x416 resolution |
| | | * if error `Out of memory` occurs then in `.cfg`-file you should increase `subdivisions=16`, 32 or 64: [link](https://github.com/AlexeyAB/darknet/blob/47409529d0eb935fa7bafbe2b3484431117269f5/cfg/yolo-voc.cfg#L3) |
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| | | ## How to mark bounded boxes of objects and create annotation files: |
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| | | Here you can find repository with GUI-software for marking bounded boxes of objects and generating annotation files for Yolo v2: https://github.com/AlexeyAB/Yolo_mark |