Pinned Repositories
APA2Seg-Net
Anatomy-guided Multimodal Registration by Learning Segmentation without Ground Truth: Application to Intraprocedural CBCT/MR Liver Segmentation and Registration (Medical Image Analysis, 2021)
APG
Mapping Agricultural Plastic Greenhouses Using Google Earth Images and Deep Learning
Blog
d2l-pytorch
This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.
darknet
YOLOv4v / Scaled-YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )
DeepLabV3-
the DeepLabV3+ by keras
detr
End-to-End Object Detection with Transformers
hed
code for Holistically-Nested Edge Detection
jquery_lazyload
Vanilla JavaScript plugin for lazyloading images
Swin-Transformer-Semantic-Segmentation
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
xusanpangzi's Repositories
xusanpangzi/APG
Mapping Agricultural Plastic Greenhouses Using Google Earth Images and Deep Learning
xusanpangzi/DeepLabV3-
the DeepLabV3+ by keras
xusanpangzi/detr
End-to-End Object Detection with Transformers
xusanpangzi/Swin-Transformer-Semantic-Segmentation
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
xusanpangzi/APA2Seg-Net
Anatomy-guided Multimodal Registration by Learning Segmentation without Ground Truth: Application to Intraprocedural CBCT/MR Liver Segmentation and Registration (Medical Image Analysis, 2021)
xusanpangzi/darknet
YOLOv4v / Scaled-YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )
xusanpangzi/Detectron
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
xusanpangzi/EfficientNet-PyTorch
A PyTorch implementation of EfficientNet and EfficientNetV2 (coming soon!)
xusanpangzi/efficientnetv2.pytorch
PyTorch implementation of EfficientNetV2
xusanpangzi/hmmlearn
Hidden Markov Models in Python, with scikit-learn like API
xusanpangzi/ml-visuals
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
xusanpangzi/nvtop
NVIDIA GPUs htop like monitoring tool
xusanpangzi/pix2pix
Image-to-image translation with conditional adversarial nets
xusanpangzi/py
xusanpangzi/pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
xusanpangzi/pytorch-image-models
PyTorch image models, scripts, pretrained weights -- (SE)ResNet/ResNeXT, DPN, EfficientNet, MixNet, MobileNet-V3/V2, MNASNet, Single-Path NAS, FBNet, and more
xusanpangzi/PyTorch-YOLOv3
Minimal PyTorch implementation of YOLOv3
xusanpangzi/pytorch-YOLOv4
PyTorch ,ONNX and TensorRT implementation of YOLOv4
xusanpangzi/SERT
复现Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
xusanpangzi/SETR
[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
xusanpangzi/Swin-Transformer
a general-purpose Transformer based vision backbone
xusanpangzi/TransUNet
This repository includes the official project of TransUNet, presented in our paper: TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.
xusanpangzi/vision
Datasets, Transforms and Models specific to Computer Vision
xusanpangzi/vision_transformer
xusanpangzi/vit-pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
xusanpangzi/WatNet
A deep learning model for surface water mapping based on satellite optical image.
xusanpangzi/Yet-Another-EfficientDet-Pytorch
The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.
xusanpangzi/yolov3
YOLOv3 in PyTorch > ONNX > CoreML > TFLite
xusanpangzi/yolov5
YOLOv5 in PyTorch > ONNX > CoreML > TFLite
xusanpangzi/YOLOX
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/