Ophora-160K
包含16万+眼科手术视频-文本对的数据集，用于文本引导的手术视频生成和流程理解。
基本信息
资源简介
Ophora-160K
【数据集背景】
本数据集源站标题为《uni-medical/Ophora》。源站首次发布：2025-02-27。
【数据内容】
源站原始描述：# Ophora: A Large-Scale Data-Driven Text-Guided Ophthalmic Surgical Video Generation Model **Abstract:** In ophthalmic surgery, developing an AI system capable of interpreting surgical videos and predicting subsequent operations requires numerous ophthalmic surgical videos with high-quality annotations, which are difficult to collect due to privacy concerns and labor consumption. Text-guided video generation (T2V) emerges as a promising solution to overcome this issue by generating ophthalmic su…
【适用方向】
多模态数据适合跨模态对齐、融合建模与联合表征学习方向的研究。
【获取与许可】
源站页面：https://github.com/uni-medical/Ophora
【使用注意】
· 源站最后修改于 2025-07-16，引用时请注意版本时效。
下载信息
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需要注册 Kaggle 账号并登录后下载，适合需要跟踪下载记录和使用 API 的用户。
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暂未开放当前数据集主要来源为 Kaggle 公开托管，完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取
git clone https://github.com/mar-cry/Ophora.git
curl -L -o repo.zip https://github.com/mar-cry/Ophora/archive/refs/heads/main.zip
unzip repo.zip
源站 README 摘录（使用方式）
Ophora: A Large-Scale Data-Driven Text-Guided Ophthalmic Surgical Video Generation Model
Abstract: In ophthalmic surgery, developing an AI system capable of interpreting surgical videos and predicting subsequent operations requires numerous ophthalmic surgical videos with high-quality annotations, which are difficult to collect due to privacy concerns and labor consumption. Text-guided video generation (T2V) emerges as a promising solution to overcome this issue by generating ophthalmic surgical videos based on surgeon instructions. In this paper, we present Ophora, a pioneering model that can generate ophthalmic surgical videos following natural language instructions. To construct Ophora, we first propose a Comprehensive Data Curation pipeline to convert narrative ophthalmic surgical videos into a large-scale, high-quality dataset comprising over 160K video-instruction pairs, Ophora-160K. Then, we propose a Progressive Video-Instruction Tuning scheme to transfer rich spatial-temporal knowledge from a T2V model pre-trained on natural video-text datasets for privacy-preserved ophthalmic surgical video generation based on Ophora-160K. Experiments on video quality evaluation via quantitative analysis and ophthalmologist feedback demonstrate that Ophora can generate realistic and reliable ophthalmic surgical videos based on surgeon instructions. We also validate the capability of Ophora for empowering downstream task of ophthalmic surgical workflow understanding.
Introduction
This repository is for our work submitted to MICCAI25, titled “Ophora: A Large-Scale Data-Driven Text-Guided Ophthalmic Surgical Video Generation Model”.
We have released the training and inference codes of Ophora. The model checkpoint and dataset are released.
Synthesized Videos
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| Anterio Chamber Flushing: Simulated procedure demonstrating anterior chamber irrigation during ophthalmic surgery. | Capsule Polishing: Synthesized video showing delicate capsule polishing with micro-instruments. |
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数据加载示例（表格/文本类）
import pandas as pd, glob, os
files = (glob.glob(os.path.join(path, "**", "*.csv"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.tsv"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.xlsx"), recursive=True))
print("数据文件:", files)
df = pd.read_csv(files[0])
print(df.shape); print(df.columns.tolist()); print(df.head(3))
数据缺失？
依托陕西、四川两大基地，我们与超过十家三甲医院建立直接合作关系，覆盖合规授权、采集治理、专业标注、数据交付的全流程，为AI医疗团队提供即拿即用的高质量临床数据。
⚡️ 需要数据支持或标注服务？立即联系我们获取专业方案。
