Classify images, search semantically, and moderate content with OpenAI's CLIP model.
npx skills add https://github.com/superfhp/lumi-agent --skill clip-superfhp
Please help me install this Agent Skill. Skill: clip Source: https://github.com/superfhp/lumi-agent/tree/main/optional-skills/mlops/clip Command: npx skills add https://github.com/superfhp/lumi-agent --skill clip-superfhp
This Skill provides a comprehensive solution for image classification, semantic image search, and content moderation using OpenAI's CLIP model, enabling zero-shot image understanding and analysis without fine-tuning.
Use the clip skill to classify the image 'sunset.jpg' and print the top 3 categories.
High-intent search queries and answers about installing and using this skill.
Zero-shot image classification categorizes images into predefined classes without training data by using OpenAI's CLIP model to match image features against text labels, returning the most probable categories automatically.
Yes, you can use the CLIP model for content moderation to detect and flag inappropriate images by evaluating the image against text descriptions of restricted or adult content to determine if it should be flagged.
Semantic image search uses the CLIP model to embed images and text into the same vector space, allowing you to retrieve visually or contextually similar images by matching their semantic content embeddings.
Yes, running CLIP for image analysis requires the transformers, torch, and pillow libraries to process image and text data, load the model, and perform the underlying tensor computations for classification.
The best way to classify images into custom categories using CLIP is zero-shot classification, which directly compares image embeddings against your custom text category labels without requiring any model fine-tuning.
Using CLIP for visual question answering is limited by its zero-shot design, meaning it matches image features to text prompts but lacks deep multi-step reasoning required for complex visual question answering scenarios.
HarriesConnects images and text in a shared embedding space using CLIP.
zhouboyu-xrealClassify images and match text using OpenAI's CLIP model.
automatedigitalClassify images zero-shot and retrieve cross-modal matches via cosine similarity.
NVIDIA-TAOFine-tune CLIP models for image-text retrieval, classification, and ONNX/TensorRT deployment.
