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qwencloud-vision

Analyze images and videos with QwenVL models for OCR and structured outputs.

36|Updated Mar 11, 2026
Search Tags:#ocr#image#multimodal#video#thinking#json#vision
One-click install
npx skills add https://github.com/QwenCloud/qwencloud-ai --skill qwencloud-vision
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: qwencloud-vision
Source: https://github.com/QwenCloud/qwencloud-ai/tree/main/skills/vision/qwencloud-vision
Command: npx skills add https://github.com/QwenCloud/qwencloud-ai --skill qwencloud-vision

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires alibabacloud-oss-v2, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Analyze images and videos using Qwen VL and VL-OCR models to understand scenes, extract text, answer questions, and produce structured outputs for automation and agents.

Core Features & Use Cases

  • Image and video understanding (including thinking-mode support) for descriptions, Q&A, and reasoning.
  • OCR text extraction with structured data outputs and language support.
  • Multi-image comparison and visual reasoning for charts, scenes, and visual problems.
  • JSON Schema or JSON object outputs for easy integration with pipelines and agents.

Quick Start

Describe an image or video by running python scripts/analyze.py with a prompt and the media file.

Frequently Asked Questions about qwencloud-vision

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I extract text from images and videos using OCR?▼

To perform OCR text extraction, you can analyze media files with QwenVL models to extract text and output structured data. This process uses a valid API key and Python 3.9+ to execute the operation scripts.

Can I get structured JSON outputs from image understanding models?▼

Yes, image understanding with QwenVL models supports JSON Schema or JSON object outputs. This enables easy integration of extracted visual insights into automation pipelines and agents.

Do I need a specific Python version to run multimodal visual reasoning tasks?▼

Yes, multimodal visual reasoning tasks require Python 3.9 or higher. You must also configure a valid DASHSCOPE_API_KEY or QWEN_API_KEY to authenticate the QwenVL model requests.

What is the best way to compare multiple images and perform visual reasoning?▼

The best way to compare multiple images is using QwenVL models that support multi-image inputs. This allows you to perform visual reasoning across charts, scenes, and visual problems to produce actionable insights.

Does this approach support video understanding and scene analysis?▼

Yes, video understanding is fully supported alongside image analysis. You can analyze video inputs to generate descriptions, answer questions, and perform reasoning using thinking-mode support.

Why does my OCR and visual reasoning script require alibabacloud-oss-v2?▼

The OCR and visual reasoning scripts use alibabacloud-oss-v2 as a dependency to handle media file operations. This integration supports processing single or multi-image inputs and video files for structured outputs.

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