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Yolov7 ⭐ 12,154

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

Tensorflow 2.x Yolov3 ⭐ 521

YOLOv3 implementation in TensorFlow 2.3.1

Pytorchnethub ⭐ 519

项目注释+论文复现+算法竞赛+Pytorch实践

Yolov4 Cloud Tutorial ⭐ 115

This repository walks you through how to Build and Run YOLOv4 Object Detections with Darknet in the Cloud with Google Colab.

Xtreme Vision ⭐ 76

A High Level Python Library to empower students, developers to build applications and systems enabled with computer vision capabilities.

Yolo v4 using TensorFlow 2.x

Maskdetect Yolov4 Pytorch ⭐ 40

基于PyTorch&YOLOv4实现的口罩佩戴检测 ⭐ 自建口罩数据集分享

Comet.box ⭐ 21

Collection of Object Detection and Segmentation Pipelines🛸🚀

Deep Learning With Googlecolab ⭐ 14

Deep Learning Applications (Darknet - YOLOv3, YOLOv4 | DeOldify - Image Colorization, Video Colorization | Face-Recognition) with Google Colaboratory - on the free Tesla K80/Tesla T4/Tesla P100 GPU - using Keras, Tensorflow and PyTorch.

Chess_recognition ⭐ 12

This project uses computer vision techniques to detect objects on a chessboard. The data are converted into an 8x8 numpy matrix which is passed to the minimax algorithm to suggest a move.

Darkeras Yolov4 ⭐ 10

Darkeras: Execute YOLOv3/YOLOv4 Object Detection on Keras with Darknet Pre-trained Weights. A tool for converting weight files trained on Darknet software to Keras framework.

Fruit Detection In Orchards ⭐ 8

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

Object_detection_classification_ _ford_otosan_intern_p2 ⭐ 7

Development of Deep Learning algorithms for Drivable Area Segmentation, Lane Segmentation, Traffic Sign Detection and Classification with data collected and labeled by Ford Otosan.

Comparativestudy ⭐ 6

Code for paper: "Road object detection: a comparative study of deep learning-based algorithms" https://link.springer.com/article/10.1007/s11042-0

Airborne Object Detection And Tracking ⭐ 6

Funix Capstone Project with Airborne Object Detection and Tracking

Darkneuron ⭐ 5

This Library will deal with the implementation of Automatic Deep Learning which can reduce the time and Complexity for non-technical users and Specialists in this field to train their own networks with significant accuracies and can perform Image Classification, Object Detection and hybridization of Models.

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