#Yolov4
Showing 24 of 24 repositories tagged #yolov4, ranked by stars
🔥🔥🔥 专注于YOLO11，YOLOv8、TYOLOv12、YOLOv10、RT-DETR、YOLOv7、YOLOv5改进模型，Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀
YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
Scaled-YOLOv4: Scaling Cross Stage Partial Network
🍅 Deploy ncnn on mobile phones. Support Android and iOS. 移动端ncnn部署，支持Android与iOS。
:basketball::robot::basketball: AI web app and API to analyze basketball shots and shooting pose.
High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
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.
A shared library of on-demand DeepStream Pipeline Services for Python and C/C++
PyTorch implementations of recent Computer Vision tricks (ReXNet, RepVGG, Unet3p, YOLOv4, CIoU loss, AdaBelief, PolyLoss, MobileOne). Other additions: AdEMAMix
This repository provides you with an easy-to-use labeling tool for State-of-the-art Deep Learning training purposes. It supports Auto-Labeling.
⚾🤖⚾ Automatic baseball pitching overlay in realtime
Packaged version of ultralytics/yolov5 + many extra features
This is a repository for an nocode object detection inference API using the Yolov3 and Yolov4 Darknet framework.
This is a repository for an nocode object detection inference API using the Yolov4 and Yolov3 Opencv.
a Pytorch easy re-implement of "YOLOX: Exceeding YOLO Series in 2021"
Import and export Darknet™ models within MATLAB deep learning networks.
System integrated with YOLOv4 and Deep SORT for real-time crowd monitoring, then perform crowd analysis. The system is able to monitor for abnormal crowd activity, social distance violation and restricted entry. The other part of the system can then process crowd movement data into optical flow, heatmap and energy graph.
Official Implementation of "Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras"
Go bindings for Darknet (YOLO v4 / v7-tiny / v3)
Use the YOLO v4 and v5 (ONNX) models for object detection in C# using ML.Net
A High Level Python Library to empower students, developers to build applications and systems enabled with computer vision capabilities.
Deep Learning and Computer Vision Applications using Streamlit
Considering the big change that the world is facing, as well as our lives due to the COVID-19, we provide to people and companies a complete open-source tool to analyze the social distancing for streets, parks, offices, and even crowded places like malls, train stations, and others.
ODAM - Object detection and Monitoring