This is a repository for an nocode object detection inference API using the Yolov4 and Yolov3 Opencv.
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Updated
Jun 28, 2022 - Python
This is a repository for an nocode object detection inference API using the Yolov4 and Yolov3 Opencv.
Automatic License Plate Recognition for Traffic Violation Management made with YOLOv4, Darknet, Tensorflow Lite
helmet(hard hat) detection with yolov4
Food calorie estimations Using Deep Learning And Computer Vision
Creating datasets in YOLO format using pretrained YOLO model in Darknet framework which could be used to train the model further
YOLT (You Only Look Twice) - a tool that attempts to improve the accuracy of YOLOv4 in images
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.
Training and fine-tuning YOLOv4 Tiny on custom object detection dataset for Taiwanese traffic
Notes on training and deploying a Darknet YOLO v4 model on Azure.
A tutorial on how to train a YOLOv4 vehicle detector using Darknet and the RoundaboutTraffic dataset on a NVIDIA Jetson Nano.
This repository contains an implementation of YOLOv4 in the context of Detecting People Wearing Mask
People tracking in crowded locations using multiple object Tracking (MOT)
split data into train test split - yolo format (images & txt )split
Convert the YOLOv4 Darknet format txt files to AutoML csv format for Cloud AutoML Vision Object Detection.
Tools for darknet, created by Yu-Hsien Liao (LiaoSteve)
Tools for machine learning. It helps to do "augmentation", "label images" with yolo pre-trainned model, and others...
Vehicle-Identification-from-Traffic-Videos-Surveillance Using-Computer-Vision-and-object-detection-algorithm-yolov4
Ford Otosan Internship Project 2021 || Traffic Sign Detection and Recognition.
Multiple Object Tracking in video Using Deep learning
Image recognition for Javanese script using YOLOv4 Darknet and HD-CNN. This project uses YOLOv4 as the object detector, and each detected object will be classified by HD-CNN.
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