darknet

Visualizer for neural network, deep learning, and machine learning models

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.

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

YOLO ROS: Real-Time Object Detection for ROS

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

License Plate Detection and Recognition in Unconstrained Scenarios

YOLOv2 in PyTorch

An open source tool to quantify the world

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

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.

🚇暗网中文网监控爬虫(DEEPMIX)

A caffe implementation of MobileNet-YOLO detection network

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

Label images and video for Computer Vision applications

NVIDIA DeepStream SDK 6.1.1 / 6.1 / 6.0.1 / 6.0 configuration for YOLO models