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.

Learn how to design, develop, deploy and iterate on production-grade ML applications.

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

The fastai deep learning library

《统计学习方法》的代码实现

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

📡 Simple and ready-to-use tutorials for TensorFlow

wtfpython的中文翻译/持续🚧.../ 能力有限，欢迎帮我改进翻译

PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)

PRML algorithms implemented in Python

OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image genera…

unet for image segmentation

line drawing colorization using chainer

Unofficial implementation of the ImageNet, CIFAR 10 and SVHN Augmentation Policies learned by AutoAugment using pillow

Code for the Lovász-Softmax loss (CVPR 2018)

Data Augmentation For Object Detection

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

Feature exploration for supervised learning

Using deep learning to generate music in MIDI format.

开发 bilibili 网站爬虫，大数据分析研究

various cv tools, such as label tools, data augmentation, label conversion, etc.

An implementation of "mixup: Beyond Empirical Risk Minimization"

Kaggle airbus ship detection challenge 21st solution

AIND Term 2 -- Lesson on Convolutional Neural Networks

Cutout / Random Erasing implementation, especially for ImageDataGenerator in Keras

U-Net图像分割练习题两则

Lyrics and piano music generation in Pytorch

This project contains code for paper Ksenia Konyushkova, Raphael Sznitman, Pascal Fua 'Learning Active Learning from Data', NIPS 2017

[IGARSS 2025 Oral] A Simple Aerial Detection Baseline of Multimodal Language Models.

A practical example of image classifier with Keras 2.x and TensorFlow backend, using the Kaggle Cats vs. Dogs dataset. By taking advantage of Keras' image data augmentation capabilities (and also r…