# roboflow/awesome-openai-vision-api-experiments

Must-have resource for anyone who wants to experiment with and build on the OpenAI vision API 🔥

Repository: https://github.com/roboflow/awesome-openai-vision-api-experiments
Canonical: https://ross.abutalabs.com/products/awesome-openai-vision-api-experiments
Language: Python
License Family: other
Topics: chatgpt, computer-vision, openai, classification, clip, zero-shot, grounding-dino, open-vocabulary-detection, open-vocabulary-segmentation, segment-anything
Last push: 2025-01-14T16:38:43+00:00

## Health v2 (maintenance only)
Score: 27/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 1, release rhythm 35, longevity 73
- inputs: {"age_days": 1030, "days_push": 596, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1690, forks 135 (observed 2026-08-28T04:05:22.541831+00:00)

## What it is
A curated collection of experiments demonstrating how to build applications on top of the OpenAI Vision API (GPT-4V), including zero-shot classification, detection with GroundingDINO, and webcam chat apps. It serves as a hub for learning and combining GPT-4V with foundational computer vision models.

## Use cases
- experiment with the openai vision api
- build zero-shot image classification with gpt-4v
- do object detection with gpt-4v and grounding dino
- chat with a webcam video stream using gpt-4v
- compare gpt-4v against clip for image understanding
- learn to combine vision language models with sam segmentation

## When to choose
- you want ready-made example code for the OpenAI Vision API
- you need inspiration for combining GPT-4V with models like GroundingDINO or SAM
- you are exploring zero-shot visual AI applications

## When to avoid
- you need a production-ready library or SDK rather than example experiments
- you need object detection or segmentation from GPT-4V alone without complementary models
- you cannot obtain an OpenAI API key or need fully offline solutions

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: computer-vision, image-processing, machine-learning, llm-inference, developer-tools
- domain: computer-vision, artificial-intelligence, large-language-models, tutorials, awesome-lists
- platform: python, cross-platform
- tags: openai-vision-api, gpt-4v, zero-shot-learning, grounding-dino, segment-anything, clip, awesome-list, experiments

## Member repositories
- roboflow/awesome-openai-vision-api-experiments (main) score 27

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:22.541831+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:38:39.323379+00:00, confidence not recorded.
  - readme: https://github.com/roboflow/awesome-openai-vision-api-experiments (fetched 2026-08-28T04:05:22.541831+00:00, sha 9da97dfa305c)
- Data as of 2026-08-30T08:39:29.467469+00:00.