- Many ideas I used and focused on https://iChess.io Chess and Chess960 Gameplay! Not yet fully Integrated! :D.
- UCI engine to use build as fallows: mkdir build && cd build && cmake -DDARKNET_ENG_CHESS=1 .. && make && cp darknet /your/engine/path
- in the engine path you have to put chess.cfg and chess.weights in the Linux or macOS may use RAMDisk.
- Linux: sudo mount -t tmpfs -o rw,size=4096M tmpfs /your/disk.ram/
- macOS: diskutil erasevolume HFS+ "/your/disk.ram"
hdiutil attach -nomount ram://8388608
Using RAM disk in general is good to safe your HDD or SDD with often transactions :D.
- json (https://github.com/nlohmann/json)
- libchess (https://github.com/sowson/libchess)
Step by step in command prompt guide: https://iblog.isowa.io/2018/05/26/darknet-training
Step by step experimental guide: https://iblog.isowa.io/2021/11/20/darknet-on-opencl-on-windows-11-x64
git apply patches/clblast.patch
DarkNet-vNext Link If you are looking for engine that has all the same functions, but it is FASTER!
This engine runs on OpenCV v4! But, OpenCV v3 is also fine!
YOLO4 elements are supported, remember in CFG file to use [yolo4] instead of [yolo] to make it work!
https://iblog.isowa.io/2020/07/02/the-multi-gpu-set-idea
https://iblog.isowa.io/2020/06/22/gpu-opencl-fine-tuning-problem-solution
https://iblog.isowa.io/2020/05/31/ph-d-hanna-hackintosh-is-ready
https://iblog.isowa.io/2020/04/29/darknet-in-opencl-on-beagleboard-ai
https://iblog.isowa.io/2020/03/03/is-opencl-beats-cuda
https://iblog.isowa.io/2020/03/02/hania-pc-well-it-needs-macos
https://iblog.isowa.io/2020/02/08/pc-for-phd-studies
https://iblog.isowa.io/2020/01/04/gpu-opencl-fine-tuning-problem
https://iblog.isowa.io/2019/12/29/darknet-cuda-vs-opencl-and-cpu-vs-nvidia-vs-amd
https://iblog.isowa.io/2019/11/05/gpu-computing-on-opencl
https://iblog.isowa.io/2019/08/18/the-fastest-darknet-in-opencl-on-the-planet
https://iblog.isowa.io/2019/02/02/darknet-in-opencl-on-asus-thinker-board-s
https://iblog.isowa.io/2018/08/01/darknet-in-opencl
https://iblog.isowa.io/2018/05/26/darknet-training
Thanks!