🎨 Vision-X ✨

Advanced AI Image Analysis A powerful AI-powered tool that analyzes images to detect objects, scenes, colors, and text using the Gemma3 model.

✨ Features

• 🔍 Deep image analysis with AI
• 🎯 Object and scene detection
• 🌈 Color palette extraction
• 📝 Text recognition in images
• 🎭 Character and emotion detection
• 📊 Progress tracking and resumption
• 🚀 Batch processing support
• 💾 Automatic progress saving

🚀 Installation

1. Prerequisites:

   • Python 3.8+
   • Ollama with Gemma3 model installed

2. Clone and install:

   git clone https://github.com/mahirox36/Vision-X.git
   cd image-analysis-tool IAT
   pip install -r requirements.txt

💻 Usage

Command Line Options

# Analyze a single image
python main.py analyze -f "path/to/image.jpg"

# Process an entire directory
python main.py analyze -d "path/to/images" -b 10

# Show analysis details for a specific image
python main.py show "path/to/image.jpg"

# Show shortened analysis output
python main.py show -s "path/to/image.jpg"

# Save results in text format
python main.py analyze -d "path/to/images" --format txt

Commands

analyze

Process images and generate analysis data.

Argument	Description	Default
-f, --file	Single image to analyze	-
-d, --directory	Directory containing images	-
-o, --output	Output file path	image_analysis_results.[json/txt]
--format	Output format (json/txt)	json
-b, --batch-size	Number of images to process simultaneously	10
--no-progress	Disable progress bar	False

show

Display analysis results for a previously analyzed image.

Argument	Description
-s, --short	Show shortened output
-f, --full	Show full output
file	Path to the image file

🔄 Progress Tracking

• Automatically saves progress after each image
• Resumes from last processed image if interrupted
• Tracks successful and failed analyses
• Saves detailed logs in logs/image_analysis.log

📝 Output Format

JSON Output

{
  "analysis_timestamp": "2024-...",
  "total_images": 100,
  "successful_analyses": 98,
  "failed_analyses": 2,
  "results": {
    "image1.jpg": {
      "summary": "...",
      "tags": ["..."],
      "objects": ["..."],
      "scene": "...",
      "colors": ["..."]
    }
  }
}

Text Output

=== image1.jpg ===
Summary: ...
Scene: ...
Objects: object1, object2, ...

📄 License

MIT License - See LICENSE file for details.

🤝 Contributing

Contributions are welcome! Please feel free to submit pull requests.