ncnn is a high-performance neural network inference framework optimized for the mobile platform

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

YOLO ROS: Real-Time Object Detection for ROS

Self-hosted, local only NVR and AI Computer Vision software. With features such as object detection, motion detection, face recognition and more, it gives you the power to keep an eye on your home, office or any other place you want to monitor.

implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)

GUI for marking bounded boxes of objects in images for training neural network Yolo v3 and v2

NVIDIA DeepStream SDK 7.1 / 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1 implementation for YOLO models

License Plate Detection and Recognition in Unconstrained Scenarios

MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB:fire::fire::fire:

An open source tool to quantify the world

YOLOv2 in PyTorch

fire-smoke-detect-yolov4-yolov5 and fire-smoke-detection-dataset 火灾检测，烟雾检测

TensorRT8.Support Yolov5n,s,m,l,x .darknet -> tensorrt. Yolov4 Yolov3 use raw darknet *.weights and *.cfg fils. If the wrapper is useful to you,please Star it.

YOLO9000: Better, Faster, Stronger - Real-Time Object Detection. 9000 classes!

🚇暗网中文网监控爬虫(DEEPMIX)

Convert JSON annotations into YOLO format.

Label images and video for Computer Vision applications