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JUN's Projects

pytorch-polygon-rnn icon pytorch-polygon-rnn

Pytorch implementation of Polygon-RNN(http://www.cs.toronto.edu/polyrnn/poly_cvpr17/)

pytorch-project-template icon pytorch-project-template

A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinforcement Learning.

rcd icon rcd

RCD: Relation Map Driven Cognitive Diagnosis for Intelligent Education Systems

rectlabel-support icon rectlabel-support

RectLabel - An image annotation tool to label images for bounding box object detection and segmentation.

segloss icon segloss

A collection of loss functions for medical image segmentation

serving icon serving

A flexible, high-performance serving system for machine learning models(『飞桨』服务器端部署库)

single_shot_al icon single_shot_al

The code of ''Single Shot Active Learning using Pseudo Annotators"

streamlit icon streamlit

Streamlit — The fastest way to build custom ML tools

swagger-codegen icon swagger-codegen

swagger-codegen contains a template-driven engine to generate documentation, API clients and server stubs in different languages by parsing your OpenAPI / Swagger definition.

tinygrad icon tinygrad

You like pytorch? You like micrograd? You love tinygrad! ❤️

torchcv icon torchcv

A PyTorch-Based Framework for Deep Learning in Computer Vision

transfiner icon transfiner

Mask Transfiner for High-Quality Instance Segmentation, CVPR 2022

transformers icon transformers

🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.

uda icon uda

Unsupervised Data Augmentation (UDA)

umi-ocr icon umi-ocr

OCR离线批量图片文字识别软件,带界面。可排除视频图片中的水印、游戏图片中的UI等干扰,提取干净的文本。基于 PaddleOCR 。

vaal icon vaal

Variational Adversarial Active Learning (ICCV 2019)

vector-map-generation-from-aerial-imagery-using-deep-learning-geospatial-unet icon vector-map-generation-from-aerial-imagery-using-deep-learning-geospatial-unet

We propose a simple yet efficient technique to leverage semantic segmentation model to extract and separate individual buildings in densely compacted areas using medium resolution satellite/UAV orthoimages. We adopted standard UNET architecture, additionally added batch normalization layer after every convolution, to label every pixel in the image.

viewal icon viewal

Implementation for the paper "ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation"

viraal icon viraal

PyTorch implementation of VirAAL: Virtual Adversarial Active Learning (https://arxiv.org/abs/2005.07287)

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