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.
Project details
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