PyTorch ,ONNX and TensorRT implementation of YOLOv4

Scaled-YOLOv4: Scaling Cross Stage Partial Network

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

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

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

YOLOv4 object detector using TensorRT engine

A state of the art of new lightweight YOLO model implemented by TensorFlow 2. This project is the official code for the paper "CSL-YOLO: A Cross-Stage Lightweight Object Detector with Low FLOPs"in IEEE ISCAS 2022.

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

Bu video bir proje tanıtım videosudur. Projede python programlama dilinde makine öğrenmesi (machine learning) ve görüntü işleme (computer vision OpenCV) kullanılarak orman yangınlarında eş zamanlı olarak duman ve ateş tespiti yapılmıştır.

Vehicle counter using python opencv and dlib

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

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.

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

A Web App of Object Detection using YOLOv4 and Streamlit

Because of the COVID-19 pandemic of 2020, more and more people are concerned with protecting themselves using masks, thus the need of software capable of monitoring whether the people are wearing masks or not. That is why I created a Python application using OpenCV (with CUDA support) based on the YOLOv4 algorithm, more precisely the tiny option…

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

Development of an underwater simulator which will be used for oysters detection for the project. Simulator can generate random underwater landscape, randomize oysters location and oysters count and much more. Using a range scanner installed on BlueROV for navigation.

toy scripts for training YOLO to detect vehicles for counting purposes