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jack zhang's Projects

mri_field_contributions icon mri_field_contributions

MATLAB code to perform the estimation and demodulation of field map contributions in magnetic resonance water–fat imaging

mrsignalsseqs icon mrsignalsseqs

Stanford University Rad229 Class Code: MRI Signals and Sequences

niftynet icon niftynet

An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

open-groundingdino icon open-groundingdino

This is the third party implementation of the paper Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

opencv icon opencv

Open Source Computer Vision Library

paddleocr-json icon paddleocr-json

OCR离线图片文字识别命令行windows程序,以JSON字符串形式输出结果,方便别的程序调用。提供各种语言API。由 PaddleOCR C++ 编译。

phycv icon phycv

PhyCV: The First Physics-inspired Computer Vision Library

py_img_seg_eval icon py_img_seg_eval

Evaluation metrics for image segmentation inspired by paper Fully Convolutional Networks for Semantic Segmentation

pytorch-unet icon pytorch-unet

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

sa-autoaug icon sa-autoaug

Scale-aware Automatic Augmentation for Object Detection (CVPR 2021)

sahi icon sahi

Platform agnostic sliced/tiled inference + interactive ui + error analysis plots

segloss icon segloss

A collection of loss functions for medical image segmentation

sssegmentation icon sssegmentation

SSSegmentation: An Open Source Strongly Supervised Semantic Segmentation Toolbox Based on PyTorch.

surface-defect-detection icon surface-defect-detection

📈 Constantly summarizing open source dataset and critical papers in the field of surface defect research which are of great importance.

torchcv icon torchcv

TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision

torchkbnufft icon torchkbnufft

A robust, easy-to-deploy non-uniform Fast Fourier Transform in PyTorch.

transformer-ssl icon transformer-ssl

This is an official implementation for "Self-Supervised Learning with Swin Transformers".

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