RRepoGEO

REPOGEO REPORT · LITE

sml2h3/ddddocr-fastapi

Default branch main · commit a40a6b96 · scanned 6/25/2026, 11:42:21 AM

GitHub: 1,115 stars · 494 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface sml2h3/ddddocr-fastapi, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition README's opening description to clarify API focus

    Why:

    CURRENT
    > 基于 FastAPI 和 DdddOcr 的高性能 OCR API 服务，提供图像文字识别、滑动验证码匹配和目标检测功能。
> 
> 自营各类GPT聚合平台
    COPY-PASTE FIX
    > 基于 FastAPI 和 DdddOcr 的高性能 OCR API 服务，提供图像文字识别、滑动验证码匹配和目标检测功能。这是一个易于部署、支持 Docker 的自托管解决方案，专为快速集成 OCR 功能到您的应用而设计。
  • highlicense#2
    Add a LICENSE file with the MIT License

    Why:

    COPY-PASTE FIX
    MIT License

Copyright (c) [YEAR] [COPYRIGHT HOLDER]

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
  • mediumtopics#3
    Expand GitHub topics for better categorization

    Why:

    CURRENT
    captcha, ddddocr
    COPY-PASTE FIX
    captcha, ddddocr, fastapi, ocr-api, docker, object-detection, sliding-puzzle, image-processing, machine-learning, python

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface sml2h3/ddddocr-fastapi
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenCV
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenCV · recommended 2×
  2. TensorFlow · recommended 2×
  3. PyTorch · recommended 2×
  4. Google Cloud Vision AI · recommended 1×
  5. Amazon Rekognition · recommended 1×
  • CATEGORY QUERY
    Need a fast API service for image text extraction and breaking visual verification challenges.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Vision AI
    2. Amazon Rekognition
    3. Microsoft Azure Cognitive Services - Computer Vision
    4. Tesseract OCR
    5. PyTesseract
    6. Flask
    7. FastAPI
    8. OpenCV
    9. TensorFlow
    10. PyTorch

    AI recommended 10 alternatives but never named sml2h3/ddddocr-fastapi. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best Docker-deployable solutions for object detection and bypassing sliding puzzles?
    you: not recommended
    AI recommended (in order):
    1. YOLO (You Only Look Once)
    2. OpenCV
    3. Python
    4. PyTorch
    5. TensorFlow
    6. TensorFlow Object Detection API
    7. SSD
    8. Faster R-CNN
    9. EfficientDet
    10. Detectron2
    11. Mask R-CNN
    12. RetinaNet
    13. OpenVINO Toolkit
    14. ONNX Runtime
    15. ONNX (Open Neural Network Exchange)
    16. networkx

    AI recommended 16 alternatives but never named sml2h3/ddddocr-fastapi. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of sml2h3/ddddocr-fastapi?
    pass
    AI did not name sml2h3/ddddocr-fastapi — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts sml2h3/ddddocr-fastapi in production, what risks or prerequisites should they evaluate first?
    pass
    AI named sml2h3/ddddocr-fastapi explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo sml2h3/ddddocr-fastapi solve, and who is the primary audience?
    pass
    AI did not name sml2h3/ddddocr-fastapi — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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sml2h3/ddddocr-fastapi — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite