All Projects → stephanecharette → DarkMark

stephanecharette / DarkMark

Licence: other
Marking up images for use with Darknet.

Programming Languages

C++
36643 projects - #6 most used programming language
c
50402 projects - #5 most used programming language
Objective-C++
1391 projects
java
68154 projects - #9 most used programming language
objective c
16641 projects - #2 most used programming language
CMake
9771 projects

Projects that are alternatives of or similar to DarkMark

darknet-vis
Visualize YOLO feature map in prediction for easily checking your model performance
Stars: ✭ 68 (+9.68%)
Mutual labels:  yolo, darknet
JSON2YOLO
Convert JSON annotations into YOLO format.
Stars: ✭ 222 (+258.06%)
Mutual labels:  yolo, darknet
DroNet
DroNet: Efficient convolutional neural network detector for Real-Time UAV applications
Stars: ✭ 54 (-12.9%)
Mutual labels:  yolo, darknet
live-cctv
To detect any reasonable change in a live cctv to avoid large storage of data. Once, we notice a change, our goal would be track that object or person causing it. We would be using Computer vision concepts. Our major focus will be on Deep Learning and will try to add as many features in the process.
Stars: ✭ 23 (-62.9%)
Mutual labels:  yolo, darknet
lightDenseYOLO
A real-time object detection app based on lightDenseYOLO Our lightDenseYOLO is the combination of two components: lightDenseNet as the CNN feature extractor and YOLO v2 as the detection module
Stars: ✭ 20 (-67.74%)
Mutual labels:  yolo, darknet
Alturos.ImageAnnotation
A collaborative tool for labeling image data for yolo
Stars: ✭ 47 (-24.19%)
Mutual labels:  image-annotation, yolo
darknet.js
A NodeJS wrapper of pjreddie's darknet / yolo.
Stars: ✭ 61 (-1.61%)
Mutual labels:  yolo, darknet
DarkPlate
License plate parsing using Darknet and YOLO
Stars: ✭ 36 (-41.94%)
Mutual labels:  yolo, darknet
VideoRecognition-realtime-autotrainer-alerts
State of the art object detection in real-time using YOLOV3 algorithm. Augmented with a process that allows easy training of the classifier as a plug & play solution . Provides alert if an item in an alert list is detected.
Stars: ✭ 36 (-41.94%)
Mutual labels:  yolo, darknet
ffcnn
ffcnn is a cnn neural network inference framework, written in 600 lines C language.
Stars: ✭ 50 (-19.35%)
Mutual labels:  yolo, darknet
OpenCV-Flask
🐛 🐛 Opencv视频流传输到网页浏览器并做目标检测 🐛 🐛
Stars: ✭ 35 (-43.55%)
Mutual labels:  yolo, darknet
object-tracking
Multiple Object Tracking System in Keras + (Detection Network - YOLO)
Stars: ✭ 89 (+43.55%)
Mutual labels:  yolo, darknet
darknet
php ffi darknet
Stars: ✭ 21 (-66.13%)
Mutual labels:  yolo, darknet
darknet2caffe
Conversion of yolo from DarkNet to Caffe
Stars: ✭ 25 (-59.68%)
Mutual labels:  yolo, darknet
vehicle-rear
Vehicle-Rear: A New Dataset to Explore Feature Fusion For Vehicle Identification Using Convolutional Neural Networks
Stars: ✭ 99 (+59.68%)
Mutual labels:  yolo, darknet
pnn
pnn is Darknet compatible neural nets inference engine implemented in Rust.
Stars: ✭ 17 (-72.58%)
Mutual labels:  yolo, darknet
darknet-nnpack
Darknet with NNPACK
Stars: ✭ 302 (+387.1%)
Mutual labels:  yolo, darknet
yolor
implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
Stars: ✭ 1,867 (+2911.29%)
Mutual labels:  yolo, darknet
Tracking-with-darkflow
Real-time people Multitracker using YOLO v2 and deep_sort with tensorflow
Stars: ✭ 522 (+741.94%)
Mutual labels:  yolo, darknet
go-darknet
Go bindings for Darknet (YOLO v4 / v3)
Stars: ✭ 56 (-9.68%)
Mutual labels:  yolo, darknet

What is DarkMark?

DarkMark and DarkHelp demo

DarkMark is a C++ GUI tool used to annotate images for use in neural networks. It was written specifically to be used with the Darknet neural network framework, and has several features tailored for use with Darknet and YOLO.

DarkMark editor window with annotated image of a dog

When you first launch DarkMark, you can specify a Darknet-style neural network to load with the selected project. DarkMark uses that neural network to assist you in marking up more images.

DarkMark launcher

Several different review capabilities exist to quickly review all the annotations and highlight some common errors.

DarkMark review window

Once ready, DarkMark can also be used to generate all of the Darknet and YOLO (or other) configuration files to train a new neural network. This includes the modifications needed to the .cfg file, as well as the .data, training and validation .txt files. DarkMark will also create some shell scripts to start the training and copy the necessary files between computers.

Darknet configuration

License

DarkMark is open source and published using the GNU GPL v3 license. See license.txt for details.

How to Build DarkMark

Extremely simple easy-to-follow tutorial on how to build Darknet, DarkHelp, and DarkMark:

DarkMark build tutorial

DarkMark requires DarkHelp to build. (And DarkHelp requires Darknet.) So before you start building DarkMark, make sure you follow the build instructions for DarkHelp.

Once Darknet and DarkHelp have been built and installed, run the following commands to build DarkMark on Ubuntu:

sudo apt-get install build-essential cmake libopencv-dev libx11-dev libfreetype6-dev libxrandr-dev libxinerama-dev libxcursor-dev libmagic-dev
cd ~/src
git clone https://github.com/stephanecharette/DarkMark.git
cd DarkMark
mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release ..
make
make package
sudo dpkg -i darkmark*.deb

Doxygen Output

The official DarkMark documentation and web site is at https://www.ccoderun.ca/darkmark/.

Some links to specific useful pages:

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].