yolov4-tiny

PyTorch ,ONNX and TensorRT implementation of YOLOv4

Scaled-YOLOv4: Scaling Cross Stage Partial Network

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.

A Wide Range of Custom Functions for YOLOv4, YOLOv4-tiny, YOLOv3, and YOLOv3-tiny Implemented in TensorFlow, TFLite, and TensorRT.

This is a code repository for pytorch c++ (or libtorch) tutorial.

This is implementation of YOLOv4,YOLOv4-relu,YOLOv4-tiny,YOLOv4-tiny-3l,Scaled-YOLOv4 and INT8 Quantization in OpenVINO2021.3

This repository deploys YOLOv4 as an optimized TensorRT engine to Triton Inference Server

Got 100fps on TX2. Got 500fps on GeForce GTX 1660 Ti. If the project is useful to you, please Star it.

More Than YOLO（v3, v4, v3-tiny, v4-tiny）

CF 火线娱乐辅助

YOLOv4 object detector using TensorRT engine

A state of the art of new lightweight YOLO model implemented by TensorFlow 2.

C++ trainable detection library based on libtorch (or pytorch c++). Yolov4 tiny provided now.

A modern object detector inside fragment shaders

YoloV4 on a bare Raspberry Pi 4 with ncnn framework

Browser and Android application where users can quickly create climbing routes and share with community

Address book for computer vision models.

tensorrt7, support yolov3 yolov3-tiny yolov4 yolov4-tiny and so on ,if you train at darknet(AB) platform, it can support

使用darknet训练yolov4-tiny网络模型以进行人脸口罩的目标检测任务，模型由yolo格式转换为ncnn格式并部署于android

yolov4 object detection using opencv python, its simplest way to run inference on yolo

Vehicle counter using python opencv and dlib

Fruit Detection and Counting Model research for Yield mapping and Robotic harvesting

This project is for recognizing motorbike license plate in Vietnam. Includes detecting LP and recognizing characters on it. I'll write report later 😅

Trafic participants recognition, localization and classification on real time video.

Localizador de patentes con YOLO v4

This sample is an example of running an AI container on the Jetson platform utilizing GPU acceleration.

The proposed Attention ALL-CNN Twin Head YOLO (AA -YOLO) outperforms the original YOLOv4-tiny on the COCO dataset by 3.3% and reduces the model parameters by 7.26%. Source code is at https://github.com/e96031413/AA-YOLO

Here resides an end-to-end sample of using an NVIDIA Jetson platform as an Azure IoT Edge device with Live Video Analytics Edge and Azure Blob Storage. An open-source ML model is utilized to detect objects in an RSTP stream simulator. A Python web app is included for reviewing AI detections from Blob Storage.