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Photo categorizor/analyzer with digitapik AI-assist

Project description

digitapik_photoassist

AI-powered photo analysis and categorization

Overview

digitapik_photoassist is a powerful Python package that leverages AI to analyze, categorize, and enhance images with precision. Whether you're an individual, business, or developer, this tool helps automate image processing with advanced machine learning capabilities.

Features

✅ AI-Powered Image Analysis – Extract insights from images with deep learning.
✅ Automated Categorization – Classify images into relevant categories.
✅ Metadata Extraction – Retrieve EXIF data, colors, and other attributes.
✅ Face & Object Detection – Identify faces, objects, and scenes in photos.
✅ Image Quality Assessment – Score images based on clarity and noise levels.

Installation

Install the package via pip:

pip install digitapik_photoassist

Usage

Importing the Package

from digitapik_photoassist import PhotoAssist

Analyzing an Image

analyzer = PhotoAssist()
result = analyzer.analyze("image.jpg")
print(result)

Categorizing Images

category = analyzer.categorize("image.jpg")
print(f"Category: {category}")

Extracting Metadata

metadata = analyzer.get_metadata("image.jpg")
print(metadata)

Face and Object Detection

detections = analyzer.detect_objects("image.jpg")
print(detections)

Enhancing Image Quality

enhanced_image = analyzer.enhance("image.jpg")
enhanced_image.save("enhanced_image.jpg")

Licensing

digitapik_photoassist is dual-licensed under:

  • MIT License (Open-Source Version) – Free for non-commercial, educational, and personal use.
  • Commercial License – Required for business or enterprise use.

Commercial License

If you are using this package in a commercial product, SaaS, or enterprise application, you must obtain a commercial license.

For licensing inquiries, please contact: support@digitapik.com

Roadmap

Upcoming Features

  • Advanced OCR for text extraction
  • Support for cloud-based processing
  • Batch image processing

Contributing

Contributions are welcome! Feel free to submit a pull request or open an issue.

License

This project is available under the MIT License for non-commercial use.
For commercial use, please obtain a license.

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