image-understander
$
npx mdskill add openakita/openakita/image-understanderAnalyze images for text, objects, and visual questions using GPT-4 Vision.
- Extracts text from screenshots and identifies objects in photos.
- Depends on OpenAI GPT-4 Vision API for image processing.
- Executes specific modes like OCR, description, or visual Q&A.
- Returns structured JSON output with analysis results.
SKILL.md
.github/skills/image-understanderView on GitHub ↗
---
name: openakita/skills@image-understander
description: Analyze images using GPT-4 Vision for detailed description, OCR text extraction, object recognition, and visual Q&A. Use when the user needs to understand image content, extract text from screenshots, identify objects in photos, or ask questions about images via OpenAI GPT-4 Vision API.
license: MIT
metadata:
author: openakita
version: "1.0.0"
---
# 图片理解技能 (Image Understander)
## 📋 概述
一个基于 OpenAI GPT-4 Vision 的图片理解工具,支持图片描述、文字识别(OCR)、物体识别和图片问答。
## 🚀 功能
| 功能 | 命令 | 说明 |
|------|------|------|
| 图片描述 | `-m describe` | 详细描述图片内容 |
| 文字提取 | `-m ocr` | 提取图片中的所有文字 |
| 物体识别 | `-m objects` | 识别并列出图片中的物体 |
| 图片问答 | `-m qa` | 针对图片回答问题 |
## 📦 安装
```bash
# 安装依赖
pip install openai pillow requests
```
## 🔧 配置
### 方式一:环境变量
```bash
set OPENAI_API_KEY=sk-your-api-key-here
```
### 方式二:命令行传入
```bash
python scripts/main.py -i photo.jpg -a sk-your-key
```
## 📖 使用方法
### 基本使用
```bash
# 描述图片
python scripts/main.py -i photo.jpg -m describe
# 提取文字(OCR)
python scripts/main.py -i screenshot.png -m ocr
# 识别物体
python scripts/main.py -i photo.jpg -m objects
# 图片问答
python scripts/main.py -i photo.jpg -m qa -q "这个图片里有什么?"
```
### 完整参数
```bash
python scripts/main.py \
--image PATH_TO_IMAGE \
--mode describe|ocr|objects|qa \
--api-key YOUR_API_KEY \
--prompt "你的问题" \
--output OUTPUT.json \
--verbose
```
## 📁 输出示例
```json
{
"mode": "describe",
"image": "photo.jpg",
"result": "A beautiful sunset over the ocean with orange and purple sky...",
"objects": [],
"text": ""
}
```
## ⚠️ 注意事项
- 需要 OpenAI API Key(支持 GPT-4 Vision)
- 支持的图片格式:PNG、JPG、GIF、BMP
- 图片大小建议小于 20MB