Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Netron | 25,750 | 4 | 70 | 7 days ago | 610 | December 09, 2023 | 27 | mit | JavaScript | |
Visualizer for neural network, deep learning and machine learning models | ||||||||||
Darknet | 24,851 | 4 months ago | 1,962 | other | C | |||||
Convolutional Neural Networks | ||||||||||
Ncnn | 18,937 | 1 | 14 days ago | 26 | October 27, 2023 | 1,010 | other | C++ | ||
ncnn is a high-performance neural network inference framework optimized for the mobile platform | ||||||||||
Map | 2,685 | a year ago | 99 | apache-2.0 | Python | |||||
mean Average Precision - This code evaluates the performance of your neural net for object recognition. | ||||||||||
Yolov3 Tf2 | 2,501 | 6 months ago | 167 | mit | Jupyter Notebook | |||||
YoloV3 Implemented in Tensorflow 2.0 | ||||||||||
Imgclsmob | 2,399 | 9 | 2 years ago | 67 | September 21, 2021 | 6 | mit | Python | ||
Sandbox for training deep learning networks | ||||||||||
Bmw Yolov4 Training Automation | 630 | 9 months ago | 9 | bsd-3-clause | Python | |||||
This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our BMW-LabelTool-Lite and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. NoCode training with YOLOv4 and YOLOV3 has never been so easy. | ||||||||||
Lightnet | 321 | 5 years ago | 12 | mit | C | |||||
🌓 Bringing pjreddie's DarkNet out of the shadows #yolo | ||||||||||
Bmw Yolov4 Inference Api Gpu | 276 | 2 years ago | bsd-3-clause | Python | ||||||
This is a repository for an nocode object detection inference API using the Yolov3 and Yolov4 Darknet framework. | ||||||||||
Pine | 219 | 3 years ago | 20 | mit | Python | |||||
:evergreen_tree: Aimbot powered by real-time object detection with neural networks, GPU accelerated with Nvidia. Optimized for use with CS:GO. |