GitHub - Rope-Robotics/darknet: YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )

The dataset can be found on the cloud which you need to add the images and .txt files into the folder path data/obj.
Cloud - mnt/cloudShareRobotLog/robot_software/machine_learned/inspection/obj
- The weights and conv is also on cloud or on sharepoint.
On sharepoint you can find the documentation (How to use it) under RD/01 Software/29 Mathie (Darknet Machine Learning)
- Remember to make the file and then use cfg and data when using on Ubuntu.
- For Windows use the build folder.
The distance machine learning done from Ukraine can be found on Largefiles/Bladedistance_SW

Name		Name	Last commit message	Last commit date
Latest commit History 2,046 Commits
.circleci		.circleci
.github		.github
3rdparty		3rdparty
build/darknet		build/darknet
cfg		cfg
cmake		cmake
data		data
include		include
results		results
scripts		scripts
src		src
.gitignore		.gitignore
.travis.yml		.travis.yml
CMakeLists.txt		CMakeLists.txt
DarknetConfig.cmake.in		DarknetConfig.cmake.in
LICENSE		LICENSE
Makefile		Makefile
README.md		README.md
build.ps1		build.ps1
build.sh		build.sh
darknet.py		darknet.py
darknet_images.py		darknet_images.py
darknet_video.py		darknet_video.py
image_yolov3.sh		image_yolov3.sh
image_yolov4.sh		image_yolov4.sh
json_mjpeg_streams.sh		json_mjpeg_streams.sh
net_cam_v3.sh		net_cam_v3.sh
net_cam_v4.sh		net_cam_v4.sh
package.xml		package.xml
video_yolov3.sh		video_yolov3.sh
video_yolov4.sh		video_yolov4.sh

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