CLIP: Get Image Insights
From the repo · “CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image”
CLIP predicts the most relevant text snippet given an image, allowing startup founders to automatically generate text descriptions of images
- •Automating image captioning for e-commerce products
- •Generating text summaries of visual content for social media
- •Creating image-based chatbot responses
python scripts/demo.py --prompt 'A picture of a cat' --image-path 'path/to/image.jpg' --model 'ViT-B/32'
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/clip && curl -fsSL https://workflowstacks.com/api/skills/clip/claude-skill -o ~/.claude/skills/clip/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
CLIP: Get Image Insights is a small Jupyter Notebook project (~900 lines across 6 code files, plus 1 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit 5 months ago, MIT license, has a test suite.
- 1README.mdStart here — what it does and how to install it
- 2requirements.txtDependencies and the commands it exposes
- 3clip/__init__.pyInside clip/ — the main logic begins here
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/clip && curl -fsSL https://workflowstacks.com/api/skills/clip/claude-skill -o ~/.claude/skills/clip/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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