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.

100-Days-Of-ML-Code中文版

📡 Simple and ready-to-use tutorials for TensorFlow

深度学习入门教程, 优秀文章, Deep Learning Tutorial

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

Build your neural network easy and fast, 莫烦Python中文教学

tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials

Reference models and tools for Cloud TPUs.

unet for image segmentation

Single Shot MultiBox Detector in TensorFlow

A simplified implemention of Faster R-CNN that replicate performance from origin paper

exercise for nndl

The repository is about 100+ python programming exercise problem discussed, explained, and solved in different ways

Deep Learning 101 with PaddlePaddle （『飞桨』深度学习框架入门教程）

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

3D U-Net model for volumetric semantic segmentation written in pytorch

利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码

Code for the Lovász-Softmax loss (CVPR 2018)

Replication of simple CV Projects including attention, classification, detection, keypoint detection, etc.

Code for "Deep Snake for Real-Time Instance Segmentation" CVPR 2020 oral

Resources of semantic segmantation based on Deep Learning model

Gaussian Process Optimization using GPy

Some interesting TensorFlow tutorials for beginners.

This repo is the codebase for our team to participate in DOTA related competitions, including rotation and horizontal detection.

Image Segmentation and Object Detection in Pytorch

Hierarchical Attention Networks for Document Classification in PyTorch

pytorch version of spatial transformer networks

Statistics and Visualization of acceptance rate, main keyword of CVPR 2019 accepted papers for the main Computer Vision conference (CVPR)

STEAL - Learning Semantic Boundaries from Noisy Annotations (CVPR 2019)

Deep networks for Earth Observation