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name: clip_zeroshot_retrieval_eval description: Evaluate CLIP-style zero-shot classification and cross-modal retrieval with normalized similarity rankings.

CLIP Zero-Shot And Retrieval Evaluation

Use this skill when checking downstream CLIP transfer mechanisms: class-prompt similarity for zero-shot classification and image/text ranking for retrieval.

Inputs

• Image embeddings.
• Class text embeddings and labels for classification.
• Caption/text embeddings aligned by index for retrieval.
• Recall cutoffs.

Outputs

• Top-1 accuracy percentage.
• Recall@K percentages.
• Ranking traces.

Workflow

1. Normalize image and text/class embeddings.
2. For classification, choose the class with maximum similarity.
3. For retrieval, rank candidates by similarity with deterministic tie-breaking.
4. Compute percentages and save trace data.

Validation

Run python tests/test_zeroshot_retrieval_eval.py.

Limitations

This skill evaluates provided embeddings; it does not download datasets or run large model inference.