Billedklassificering
Klassificer billedindhold med AI-konfidensscorer.
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About Billedklassificering
OptiPix Image Classifier uses a Vision Transformer (ViT) AI model to classify the content of images and provide top predictions with confidence scores. The model is trained on ImageNet with over 1,000 categories covering everyday objects, animals, plants, food, vehicles, landmarks, and more. Simply drop an image and the classifier will provide its top 5 predictions ranked by confidence, displayed as a clean bar chart. This is useful for understanding what AI sees in your images, auto-tagging photo collections, educational exploration of computer vision, and quick image categorization. The ViT model runs entirely in your browser using the Hugging Face Transformers.js library with ONNX Runtime. The model downloads once (approximately 85 MB) and is cached for offline use. Classification is fast, typically completing in 1-3 seconds on modern devices.
How It Works
The tool uses a Vision Transformer (ViT) model from the Hugging Face Transformers.js library. The image is preprocessed into a fixed-size tensor, processed through the transformer encoder, and the output is mapped to ImageNet categories with softmax confidence scores.
Use Cases
- •Auto-tag photo collections with content labels
- •Understand what AI sees in ambiguous images
- •Educational exploration of computer vision models
- •Quick image categorization for organizing large libraries
- •Content analysis for accessibility descriptions