# sml2h3/ddddocr-fastapi

使用ddddocr的最简api搭建项目，支持docker

Repository: https://github.com/sml2h3/ddddocr-fastapi
Canonical: https://ross.abutalabs.com/products/ddddocr-fastapi
Language: Python
License Family: other
Topics: ddddocr, captcha
Last push: 2024-11-13T02:31:09+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 1700, "days_push": 659, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1126, forks 500 (observed 2026-08-28T04:03:41.252035+00:00)

## What it is
A minimal FastAPI-based REST API service wrapping the DdddOcr OCR engine, exposing endpoints for image text recognition, slide captcha matching, and object detection. It ships with Docker support for easy deployment.

## Use cases
- solve captchas via an ocr api
- recognize text in images over http
- match slider captcha positions
- self-host an ocr microservice with docker
- detect objects in captcha images
- ocr base64 images from any client

## When to choose
- you need a ready-made HTTP API around ddddocr without writing code
- you want to deploy captcha/OCR recognition as a Dockerized microservice
- you need slide-captcha gap matching from other applications

## When to avoid
- you need general-purpose document OCR rather than captcha-style text
- you need a client-side or offline library instead of a network service
- you require a maintained license or long-term support guarantees

## Facets
- artifact type: service
- maturity: active
- function: ocr, http-server, api-framework, image-processing
- domain: computer-vision, image-processing, apis, web-development
- platform: python, self-hosted
- tags: captcha, captcha-solving, fastapi, ddddocr, ocr-api, slide-captcha, object-detection, docker, linux

## Member repositories
- sml2h3/ddddocr-fastapi (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:41.252035+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 2026-08-30T06:39:13.773651+00:00, confidence not recorded.
  - readme: https://github.com/sml2h3/ddddocr-fastapi (fetched 2026-08-28T04:03:41.252035+00:00, sha f6ce5235a3f6)
- Data as of 2026-08-30T08:39:29.467469+00:00.