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| | | # Yolo-v3 and Yolo-v2 for Windows and Linux |
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| | | ### (neural network for object detection) |
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| | | ### (neural network for object detection) - Tensor Cores can be used on [Linux](https://github.com/AlexeyAB/darknet#how-to-compile-on-linux) and [Windows](https://github.com/AlexeyAB/darknet#how-to-compile-on-windows) |
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| | | [](https://circleci.com/gh/AlexeyAB/darknet) |
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| | | 2. To use Yolo as DLL-file in your C++ console application - open in MSVS2015 file `build\darknet\yolo_console_dll.sln`, set **x64** and **Release**, and do the: Build -> Build yolo_console_dll |
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| | | * you can run your console application from Windows Explorer `build\darknet\x64\yolo_console_dll.exe` |
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| | | **use this command**: `yolo_console_dll.exe data/coco.names yolov3.cfg yolov3.weights test.mp4` |
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| | | * or you can run from MSVS2015 (before this - you should copy 2 files `yolo-voc.cfg` and `yolo-voc.weights` to the directory `build\darknet\` ) |
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| | | * after launching your console application and entering the image file name - you will see info for each object: |
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| | | `<obj_id> <left_x> <top_y> <width> <height> <probability>` |
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