EpicWatermelon

TensorFlow-Examples

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

detectron2

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

CLIP

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

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

Book3_Elements-of-Mathematics

Book_3_《数学要素》 | 鸢尾花书：从加减乘除到机器学习；上架；欢迎继续纠错，纠错多的同学还会有赠书！

mmcv

OpenMMLab Computer Vision Foundation

nvitop

An interactive NVIDIA-GPU process viewer and beyond, the one-stop solution for GPU process management.

SwinIR

SwinIR: Image Restoration Using Swin Transformer (official repository)

shapely

Manipulation and analysis of geometric objects

KAIR

Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

geatpy

Evolutionary algorithm toolbox and framework with high performance for Python

Swin-Transformer-Object-Detection

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.

denoiser

Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.

noise2noise

Noise2Noise: Learning Image Restoration without Clean Data - Official TensorFlow implementation of the ICML 2018 paper

MulimgViewer

MulimgViewer is a multi-image viewer that can open multiple images in one interface, which is convenient for image comparison and image stitching.

CLIPasso

lemniscate.pytorch

Unsupervised Feature Learning via Non-parametric Instance Discrimination

SCUNet

Practical Blind Denoising via Swin-Conv-UNet and Data Synthesis (Machine Intelligence Research 2023)

spikeinterface

A Python-based module for creating flexible and robust spike sorting pipelines.

Pretrained-IPT

jpeg-sandbox

Interactively edit individual DCT blocks in any JPEG image in the browser.

DnCNN-tensorflow

:octocat::octocat:A tensorflow implement of the paper "Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising"

deepinterpolation

stats320

STATS320: Statistical Methods for Neural Data Analysis

ecephys_spike_sorting

Modules for processing extracellular electrophysiology data from Neuropixels probes

ProjectWeek

Website for NA-MIC Project Weeks

Net-SURE

Training deep learning based denoisers without ground truth data - Official Tensorflow implementation of the NeurIPS 2018 paper

LIBNet

Neural network for Lithium-ion battery in nanoCT images. For now, only the segmentation module is included.

Extended_SURE

NeurIPS 2019 Accepted - Extending Stein's Unbiased Risk Estimator to Train Deep Denoisers with Correlated Pairs of Noisy Images

g9py