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annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

blip-pytorch

这是一个blip-pytorch简化的代码，适用于了解Attention与Transformer的结构。

caption-anything

Caption-Anything is a versatile tool combining image segmentation, visual captioning, and ChatGPT, generating tailored captions with diverse controls for user preferences.

case-western-reserve-university-bearing-data-crawler

A crawler of Case Western Reserve University bearing data

cbm_codes_open

This repository contains data and codes that implement common machine learning algorithms for machinery condition monitoring task.

cesiumjs-tutorial

CesiumJS中文基础教程 http://cesiumcn.org/ | http://cesium.coinidea.com/

clip

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

clip-pytorch

这是一个clip-pytorch的模型，可以训练自己的数据集。

corrosion_cs_classification

corrosion condition state classification for bridge inspections

crack-detection

cs543_project_image-based-localization-of-bridge-defects-with-ar-visualization

Visual inspection of bridges is customarily used to identify and evaluate faults. However, current procedures followed by human inspectors demand long inspection times to examine large and difficult to access bridges. To address these limitations, we investigate a computer vision‐based approach that employs SIFT keypoint matching on collected images of defects against a pre-existing reconstructed 3D point cloud of the bridge. We also investigate methods of reducing computation time with ML-based and conventional CV methods of segmentation to eliminate redundant keypoints. Our project successfully localizes the defect images and achieves a savings in runtime from filtering keypoints.

deeplabv3-plus-pytorch

这是一个deeplabv3-plus-pytorch的源码，可以用于训练自己的模型。

deeplabv3finetuning

Tutorial on fine tuning DeepLabv3 segmentation network for your own segmentation task in PyTorch.

deeplabv3plus-pytorch

DeepLabv3 and DeepLabv3+ with pretrained weights for Pascal VOC & Cityscapes

deeplearning-muli-notes

Notes about courses Dive into Deep Learning by Mu Li

detr

End-to-End Object Detection with Transformers

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

diffusers

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

drone-tracking-datasets

Multi-view drone tracking datasets

easycv

An all-in-one toolkit for computer vision

ent516_digi-bridge_visualisation

Self-designed coursework for Digi-Bridge visualisation as the TA in the module ENT516

fashion-mnist

A MNIST-like fashion product database. Benchmark :point_right:

flask-socketio

Socket.IO integration for Flask applications.

flasktutorial

Flask Tutorial

gaoy74.github.io_backup

gcn_study

GCN 入门学习教程

grounded-segment-anything

Marrying Grounding DINO with Segment Anything - Detect and Segment Anything with Text Inputs

iforest

iForest anomaly detection codes (Matlab Version)

image_segmentation

texture and color based Image Segmentation using K-Means Clustering

inpaint-anything

Inpaint anything using Segment Anything and inpainting models.