RRepoGEO

REPOGEO REPORT · LITE

letmaik/rawpy

Default branch main · commit 326494be · scanned 6/9/2026, 8:41:51 PM

GitHub: 799 stars · 86 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)

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

AI VISIBILITY SCORE
89 /100
Healthy
Category recall
2 / 2
Avg rank #2.0 when recommended
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 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 letmaik/rawpy, 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 opening to clarify specialized role

    Why:

    CURRENT
    rawpy is an easy-to-use Python wrapper for the [LibRaw library][libraw]. It also contains some extra functionality for finding and repairing hot/dead pixels.
    COPY-PASTE FIX
    rawpy is the premier Python library for comprehensive RAW image processing, providing an easy-to-use, high-performance wrapper for the powerful [LibRaw library][libraw]. It offers fine-grained control over demosaicing, color management, and includes advanced features like hot/dead pixel repair.
  • mediumreadme#2
    Add a 'Key Features' section to the README

    Why:

    COPY-PASTE FIX
    ## Key Features

*   **Comprehensive RAW Processing:** Full control over demosaicing, color profiles, exposure, and more, powered by LibRaw.
*   **Embedded Thumbnail/Preview Extraction:** Easily retrieve thumbnails from various RAW formats.
*   **Hot/Dead Pixel Repair:** Advanced functionality to find and correct sensor defects.
*   **NumPy Integration:** Seamlessly work with image data as NumPy arrays for further processing.
  • lowtopics#3
    Add 'libraw' to repository topics

    Why:

    CURRENT
    camera-calibration, camera-image, image-optimization, image-processing, python
    COPY-PASTE FIX
    camera-calibration, camera-image, image-optimization, image-processing, python, libraw

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
2 / 2
100% of queries surface letmaik/rawpy
Avg rank
#2.0
Lower is better. #1 = top recommendation.
Share of voice
12%
Of all named tools, what % are you?
Top rival
ImageIO
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ImageIO · recommended 2×
  2. Pillow · recommended 2×
  3. OpenCV · recommended 2×
  4. ExifTool · recommended 2×
  5. LibRaw · recommended 1×
  • CATEGORY QUERY
    How to process camera RAW files programmatically using Python?
    you: #1
    AI recommended (in order):
    1. RawPy ← you
    2. LibRaw
    3. ImageIO
    4. imageio-ffmpeg
    5. imageio-libraw
    6. Pillow
    7. dcraw
    8. OpenCV
    9. ExifTool
    10. pyexiftool
    11. Darktable
    12. Adobe DNG Converter
    Show full AI answer
  • CATEGORY QUERY
    Python library to extract embedded thumbnails from camera RAW images?
    you: #3
    AI recommended (in order):
    1. ExifTool
    2. Pillow
    3. RawPy ← you
    4. ImageIO
    5. OpenCV
    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 letmaik/rawpy?
    pass
    AI named letmaik/rawpy explicitly

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

  • If a team adopts letmaik/rawpy in production, what risks or prerequisites should they evaluate first?
    pass
    AI named letmaik/rawpy 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 letmaik/rawpy solve, and who is the primary audience?
    pass
    AI named letmaik/rawpy explicitly

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

Embed your GEO score

Drop this badge into the README of letmaik/rawpy. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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letmaik/rawpy — 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