# DiffCR **Repository Path**: wei2351/DiffCR ## Basic Information - **Project Name**: DiffCR - **Description**: No description available - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-04-23 - **Last Updated**: 2025-04-23 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README README

DiffCR: A Fast Conditional Diffusion Framework for Cloud Removal from Optical Satellite Images

This repository is the official PyTorch implementation of the paper DiffCR.

Xuechao Zou1*, Kai Li2*, Student Member, IEEE, Junliang Xing2, Senior Member, IEEE,
Yu Zhang1, Shiying Wang1, Lei Jin3, Pin Tao1,2,†, Member, IEEE

Qinghai University1 , Tsinghua University2,
Beijing University of Posts and Telecommunications3

DiffCR

Requirements

To install dependencies:

pip install -r requirements.txt

To download datasets:

Training

To train the models in the paper, run these commands:

python run.py -p train -c config/ours_sigmoid.json

Test

To test the pre-trained models in the paper, run these commands:

python run.py -p test -c config/ours_sigmoid.json

Evaluation

To evaluate my models on two datasets, run:

python evaluation/eval.py -s [ground-truth image path] -d [predicted-sample image path]

Results

Quantitative Results

ablation

exp

Qualitative Results

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