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| | | # Yolo-Windows v2 |
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| | | 1. [How to use](#how-to-use) |
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| | | 2. [How to compile](#how-to-compile) |
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| | | 3. [How to train (Pascal VOC Data)](#how-to-train-pascal-voc-data) |
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| | | 4. [How to train (to detect your custom objects)](t#how-to-train-to-detect-your-custom-objects) |
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| | | 5. [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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| | | # Yolo-Windows v2 |
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| | | # "You Only Look Once: Unified, Real-Time Object Detection (version 2)" |
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| | | A yolo windows version (for object detection) |
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| | | ### How to compile: |
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| | | 1. If you have MSVS 2015, CUDA 8.0 and OpenCV 2.4.9 (with paths: `C:\opencv_2.4.9\opencv\build\include` & `C:\opencv_2.4.9\opencv\build\x64\vc14\lib`), then start MSVS, open `build\darknet\darknet.sln`, set **x64** and **Release**, and do the: Build -> Build darknet |
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| | | 1. If you have MSVS 2015, CUDA 8.0 and OpenCV 2.4.9 (with paths: `C:\opencv_2.4.9\opencv\build\include` & `C:\opencv_2.4.9\opencv\build\x64\vc12\lib` or `vc14\lib`), then start MSVS, open `build\darknet\darknet.sln`, set **x64** and **Release**, and do the: Build -> Build darknet |
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| | | 2. If you have other version of CUDA (not 8.0) then open `build\darknet\darknet.vcxproj` by using Notepad, find 2 places with "CUDA 8.0" and change it to your CUDA-version, then do step 1 |
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