Ganzooo's repositories

LRSRN

simple_real_time_super_resolution

soil_segmentation

soil_segmentation

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camera_lens_glare

camera_lens_glare_reduction

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SegLoss

A collection of loss functions for medical image segmentation

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kaggle_uw_madison_image_segmentation

https://www.kaggle.com/competitions/uw-madison-gi-tract-image-segmentation

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aimet

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

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awesome-public-datasets

A topic-centric list of HQ open datasets.

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Awesome-Super-Resolution

Collect super-resolution related papers, data, repositories

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Best-README-Template

An awesome README template to jumpstart your projects!

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copy-paste-aug

Copy-paste augmentation for segmentation and detection tasks

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free-programming-books

:books: Freely available programming books

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hlb-CIFAR10

Train to 94% on CIFAR-10 in ~6.84 seconds on a single A100, the current world speed record. Or ~95.78% in ~114 seconds (or less!)

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Learning-Deep-Learning

Paper reading notes on Deep Learning and Machine Learning

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learnopencv

Learn OpenCV : C++ and Python Examples

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MAI-2021-Workshop

MAI 2021 Workshop_Sample

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Neural-Network-Architecture-Diagrams

Diagrams for visualizing neural network architecture (Created with diagrams.net)

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NTIRE23-RTSR

NTIRE 2023 Challenge on Real-Time Super-Resolution

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pixel_error_recovery

Pixel error recovery method

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PyProf

A GPU performance profiling tool for PyTorch models

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pytorch_ema

Tiny PyTorch library for maintaining a moving average of a collection of parameters.

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segmentation_models.pytorch

Segmentation models with pretrained backbones. PyTorch.

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semantic-segmentation

Nvidia Semantic Segmentation monorepo

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stable-diffusion

A latent text-to-image diffusion model

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temporal-shift-module

[ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding

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tidl-yolov5-custom-model-demo

A walkthrough and personal notes on running YOLOv5 models with TIDL.

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TinyNeuralNetwork

TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.

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Torch-Pruning

[CVPR-2023] Towards Any Structural Pruning; LLMs / Diffusion / YOLOv8 / CNNs / Transformers

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transformer-blocks

Multi-Head Attention, Transformer, Perceiver, Linear Attention.

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