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Merge pull request #13 from LdDl/install-darknet
makefile and minor
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‎Makefile

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.ONESHELL:
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.PHONY: download build clean
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# Latest battletested AlexeyAB version of Darknet commit
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LATEST_COMMIT?=d65909fbea471d06e52a2e4a41132380dc2edaa6
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# Temporary folder for building Darknet
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TMP_DIR?=/tmp/
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# Download AlexeyAB version of Darknet
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download:
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rm -rf $(TMP_DIR)install_darknet
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mkdir $(TMP_DIR)install_darknet
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git clone https://github.com/AlexeyAB/darknet.git $(TMP_DIR)install_darknet
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cd $(TMP_DIR)install_darknet
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git checkout $(LATEST_COMMIT)
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cd -
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# Build AlexeyAB version of Darknet for usage with CPU only.
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build:
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cd $(TMP_DIR)install_darknet
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sed -i -e 's/GPU=1/GPU=0/g' Makefile
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sed -i -e 's/CUDNN=1/CUDNN=0/g' Makefile
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sed -i -e 's/LIBSO=0/LIBSO=1/g' Makefile
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$(MAKE) -j $(shell nproc --all)
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$(MAKE) preinstall
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cd -
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# Build AlexeyAB version of Darknet for usage with both CPU and GPU (CUDA by NVIDIA).
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build_gpu:
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cd $(TMP_DIR)install_darknet
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sed -i -e 's/GPU=0/GPU=1/g' Makefile
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sed -i -e 's/CUDNN=0/CUDNN=1/g' Makefile
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sed -i -e 's/LIBSO=0/LIBSO=1/g' Makefile
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$(MAKE) -j $(shell nproc --all)
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$(MAKE) preinstall
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cd -
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# Install system wide.
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sudo_install:
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cd $(TMP_DIR)install_darknet
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sudo cp libdarknet.so /usr/lib/libdarknet.so
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sudo cp include/darknet.h /usr/include/darknet.h
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sudo ldconfig
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cd -
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# Cleanup temporary files for building process
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clean:
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rm -rf $(TMP_DIR)install_darknet
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# Do every step for CPU-based only build.
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install: download build sudo_install clean
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# Do every step for both CPU and GPU-based build.
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install_gpu: download build_gpu sudo_install clean

‎README.md

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[![Go Report Card](https://goreportcard.com/badge/github.com/LdDl/go-darknet)](https://goreportcard.com/report/github.com/LdDl/go-darknet)
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[![GitHub tag](https://img.shields.io/github/tag/LdDl/go-darknet.svg)](https://github.com/LdDl/go-darknet/releases)
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# go-darknet: Go bindings for Darknet (Yolo V4, Yolo V3)
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### go-darknet is a Go package, which uses Cgo to enable Go applications to use YOLO V4/V3 in [Darknet].
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## Requirements
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For proper codebase please use fork of [darknet](https://github.com/AlexeyAB/darknet). Latest commit I've tested [here](https://github.com/AlexeyAB/darknet/commit/d65909fbea471d06e52a2e4a41132380dc2edaa6)
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In order to use go-darknet, `libdarknet.so` should be available in one of
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the following locations:
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You need to install fork of [darknet](https://github.com/AlexeyAB/darknet). Latest commit I've tested is [here](https://github.com/AlexeyAB/darknet/commit/d65909fbea471d06e52a2e4a41132380dc2edaa6)
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* /usr/lib
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* /usr/local/lib
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Use provided [Makefile](Makefile).
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Also, [darknet.h] should be available in one of the following locations:
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* For CPU-based instalattion:
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```shell
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make install
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```
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* For both CPU and GPU-based instalattion:
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```shell
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make install_gpu
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```
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Note: If you want to have GPU-acceleration before running command above install [CUDA](https://developer.nvidia.com/cuda-downloads) and [cuDNN](https://developer.nvidia.com/cudnn) (Latest CUDA version I've tested is [10.2](https://developer.nvidia.com/cuda-10.2-download-archive) and cuDNN is [7.6.5](https://developer.nvidia.com/rdp/cudnn-archive#a-collapse765-102))
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* /usr/include
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* /usr/local/include
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To achieve it, after Darknet compilation (via make) execute following command:
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```shell
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# Copy *.so to /usr/lib + /usr/include (or /usr/local/lib + /usr/local/include)
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sudo cp libdarknet.so /usr/lib/libdarknet.so && sudo cp include/darknet.h /usr/include/darknet.h
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# sudo cp libdarknet.so /usr/local/lib/libdarknet.so && sudo cp include/darknet.h /usr/local/include/darknet.h
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```
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Note: do not forget to set LIBSO=1 in Makefile before executing 'make':
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```Makefile
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LIBSO=1
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```
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## Installation
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```shell
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Building and running program:
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Navigate to [example] folder
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```shell
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cd $GOPATH/github.com/LdDl/go-darknet/example
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```
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Download dataset (sample of image, coco.names, yolov4.cfg (or v3), yolov4.weights(or v3)).
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```shell
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#for yolo v4
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./download_data.sh
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#for yolo v3
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./download_data_v3.sh
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```
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Note: you don't need *coco.data* file anymore, because sh-script above does insert *coco.names* into 'names' field in *yolov4.cfg* file (so AlexeyAB's fork can deal with it properly)
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So last rows in yolov4.cfg file will look like:
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```bash
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......
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[yolo]
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.....
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iou_loss=ciou
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nms_kind=greedynms
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beta_nms=0.6
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names = coco.names # this is path to coco.names file
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```
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Also do not forget change batch and subdivisions sizes from:
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```shell
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batch=64
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subdivisions=8
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```
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to
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```shell
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batch=1
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subdivisions=1
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```
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It will reduce amount of VRAM used for detector test.
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Build and run program
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Yolo V4:
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```shell
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go build main.go && ./main --configFile=yolov4.cfg --weightsFile=yolov4.weights --imageFile=sample.jpg
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```
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Output should be something like this:
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```shell
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traffic light (9): 73.5039% | start point: (238,73) | end point: (251, 106)
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truck (7): 96.6401% | start point: (95,79) | end point: (233, 287)
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truck (7): 96.4774% | start point: (662,158) | end point: (800, 321)
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truck (7): 96.1841% | start point: (0,77) | end point: (86, 333)
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truck (7): 46.8695% | start point: (434,173) | end point: (559, 216)
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car (2): 99.7370% | start point: (512,188) | end point: (741, 329)
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car (2): 99.2533% | start point: (260,191) | end point: (422, 322)
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car (2): 99.0333% | start point: (425,201) | end point: (547, 309)
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car (2): 83.3919% | start point: (386,210) | end point: (437, 287)
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car (2): 75.8621% | start point: (73,199) | end point: (102, 274)
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car (2): 39.1925% | start point: (386,206) | end point: (442, 240)
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bicycle (1): 76.3121% | start point: (189,298) | end point: (253, 402)
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person (0): 97.7213% | start point: (141,129) | end point: (283, 362)
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```
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Yolo V3:
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```
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go build main.go && ./main --configFile=yolov3.cfg --weightsFile=yolov3.weights --imageFile=sample.jpg
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```
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Output should be something like this:
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```shell
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truck (7): 49.5197% | start point: (0,136) | end point: (85, 311)
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car (2): 36.3747% | start point: (95,152) | end point: (186, 283)
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truck (7): 48.4384% | start point: (95,152) | end point: (186, 283)
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truck (7): 45.6590% | start point: (694,178) | end point: (798, 310)
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car (2): 76.8379% | start point: (1,145) | end point: (84, 324)
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truck (7): 25.5731% | start point: (107,89) | end point: (215, 263)
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car (2): 99.8783% | start point: (511,185) | end point: (748, 328)
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car (2): 99.8194% | start point: (261,189) | end point: (427, 322)
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car (2): 99.6408% | start point: (426,197) | end point: (539, 311)
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car (2): 74.5610% | start point: (692,186) | end point: (796, 316)
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car (2): 72.8053% | start point: (388,206) | end point: (437, 276)
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bicycle (1): 72.2932% | start point: (178,270) | end point: (268, 406)
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person (0): 97.3026% | start point: (143,135) | end point: (268, 343)
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```
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* Navigate to [example] folder
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```shell
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cd $GOPATH/github.com/LdDl/go-darknet/example
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```
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* Download dataset (sample of image, coco.names, yolov4.cfg (or v3), yolov4.weights(or v3)).
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```shell
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#for yolo v4
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./download_data.sh
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#for yolo v3
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./download_data_v3.sh
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```
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* Note: you don't need *coco.data* file anymore, because sh-script above does insert *coco.names* into 'names' field in *yolov4.cfg* file (so AlexeyAB's fork can deal with it properly)
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So last rows in yolov4.cfg file will look like:
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```bash
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......
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[yolo]
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.....
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iou_loss=ciou
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nms_kind=greedynms
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beta_nms=0.6
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names = coco.names # this is path to coco.names file
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```
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* Also do not forget change batch and subdivisions sizes from:
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```shell
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batch=64
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subdivisions=8
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```
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to
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```shell
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batch=1
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subdivisions=1
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```
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It will reduce amount of VRAM used for detector test.
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* Build and run program
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Yolo V4:
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```shell
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go build main.go && ./main --configFile=yolov4.cfg --weightsFile=yolov4.weights --imageFile=sample.jpg
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```
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Output should be something like this:
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```shell
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traffic light (9): 73.5039% | start point: (238,73) | end point: (251, 106)
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truck (7): 96.6401% | start point: (95,79) | end point: (233, 287)
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truck (7): 96.4774% | start point: (662,158) | end point: (800, 321)
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truck (7): 96.1841% | start point: (0,77) | end point: (86, 333)
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truck (7): 46.8695% | start point: (434,173) | end point: (559, 216)
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car (2): 99.7370% | start point: (512,188) | end point: (741, 329)
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car (2): 99.2533% | start point: (260,191) | end point: (422, 322)
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car (2): 99.0333% | start point: (425,201) | end point: (547, 309)
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car (2): 83.3919% | start point: (386,210) | end point: (437, 287)
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car (2): 75.8621% | start point: (73,199) | end point: (102, 274)
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car (2): 39.1925% | start point: (386,206) | end point: (442, 240)
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bicycle (1): 76.3121% | start point: (189,298) | end point: (253, 402)
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person (0): 97.7213% | start point: (141,129) | end point: (283, 362)
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```
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Yolo V3:
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```
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go build main.go && ./main --configFile=yolov3.cfg --weightsFile=yolov3.weights --imageFile=sample.jpg
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```
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Output should be something like this:
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```shell
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truck (7): 49.5197% | start point: (0,136) | end point: (85, 311)
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car (2): 36.3747% | start point: (95,152) | end point: (186, 283)
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truck (7): 48.4384% | start point: (95,152) | end point: (186, 283)
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truck (7): 45.6590% | start point: (694,178) | end point: (798, 310)
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car (2): 76.8379% | start point: (1,145) | end point: (84, 324)
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truck (7): 25.5731% | start point: (107,89) | end point: (215, 263)
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car (2): 99.8783% | start point: (511,185) | end point: (748, 328)
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car (2): 99.8194% | start point: (261,189) | end point: (427, 322)
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car (2): 99.6408% | start point: (426,197) | end point: (539, 311)
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car (2): 74.5610% | start point: (692,186) | end point: (796, 316)
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car (2): 72.8053% | start point: (388,206) | end point: (437, 276)
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bicycle (1): 72.2932% | start point: (178,270) | end point: (268, 406)
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person (0): 97.3026% | start point: (143,135) | end point: (268, 343)
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```
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## Documentation
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