Zy-1996's starred repositories
ocr_digital
Recognition of numbers displayed by digital thermometers using classical computer vision
YOLO-World
[CVPR 2024] Real-Time Open-Vocabulary Object Detection
Fire_Detection
📱🔥 Application streamlit and mongodb to detect flames and smoke in Picture / Video and Webcam using Transfer Learning based on Yolov8x
YOLOv8-Fire-and-Smoke-Detection
This projevct aims to detect fire in forest and other areas
pytorch-cifar100
Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)
openvino_notebooks
📚 Jupyter notebook tutorials for OpenVINO™
Learning-OpenCV-4-Computer-Vision-with-Python-Third-Edition
Learning OpenCV 4 Computer Vision with Python 3 – Third Edition, published by Packt
Towards-Realtime-MOT
Joint Detection and Embedding for fast multi-object tracking
deep-learning-for-image-processing
deep learning for image processing including classification and object-detection etc.
super-gradients
Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
dcase2020_task2_baseline
DCASE2020 Challenge Task 2 baseline system
mmdetection
OpenMMLab Detection Toolbox and Benchmark
PaddleDetection
Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
deep_learning_object_detection
A paper list of object detection using deep learning.
opencv-python-tutorial
📖 OpenCV-Python image processing tutorial for beginners
opencv_tutorials
Opencv4.0 with python (English&中文)， and will keep the update ! 👊
MFNet-pytorch
MFNet-pytorch, image semantic segmentation using RGB-Thermal images
detectron2
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.