A library for comparing text and images using CLIP
Project description
Abril - Text-Image Comparison using CLIP
Abril is a Python library that makes it easy to compare text and images using OpenAI's CLIP model. It provides a simple interface for calculating similarity scores between text descriptions and images.
Installation
# First, install CLIP:
pip install git+https://github.com/openai/CLIP.git
# Then install abril:
pip install abril
Usage
from abril import ClipComparer
from PIL import Image
# Initialize the comparer
comparer = ClipComparer()
# Compare a single text with an image
score = comparer.compare_text_with_image(
"a photo of a dog",
"path/to/image.jpg"
)
print(f"Similarity score: {score}")
# Find the best matching text for an image
texts = [
"a photo of a dog",
"a photo of a cat",
"a photo of a car"
]
best_text, score = comparer.find_best_match(texts, "./image.jpg")
print(f"Best match: {best_text} (score: {score})")
Features
- Easy-to-use interface for text-image comparison
- Support for both single and multiple text comparisons
- Uses CLIP's ViT-B/32 model by default (can be changed)
- Automatically uses GPU if available for faster processing
- Handles both file paths and PIL Images flexibly
- Normalizes features for better comparison
- Returns scores between 0 and 1 for easy interpretation
- Built on OpenAI's CLIP model
- GPU acceleration when available
Requirements
- Python ≥ 3.7
- PyTorch ≥ 1.7.1
- Other dependencies are handled automatically during installation
License
MIT License - see LICENSE file for details.
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