immich

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History

fix(ml): handle empty/corrupt images in face detection (#27391 )

* fix(ml): handle empty/corrupt images in face detection

When a corrupt or degenerate image with zero-dimension (0 width or 0 height)
reaches the face detection pipeline, insightface's RetinaFace.detect() calls
cv2.resize() with a target size of 0, triggering an OpenCV assertion failure:

  error: (-215:Assertion failed) inv_scale_x > 0 in function 'resize'

This crashes the ML worker and returns a 500 error to the server.

Add an early return in FaceDetector._predict() that checks for zero-dimension
images after decoding and returns empty detection results instead of passing
them to the insightface model.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix(ml): move empty image validation to request level

Per review feedback, validate image dimensions in the predict endpoint
(returning 400) rather than in each model's _predict method. This
catches all zero-dimension images before they reach any model task.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix(ml): resolve mypy strict type error in predict endpoint

Use intermediate `decoded` variable so mypy knows `.width` and `.height`
are accessed on `Image`, not on `Image | str`.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-27 11:14:34 -04:00

models

fix(ml): batch size setting (#26524 )

2026-03-05 12:01:47 -05:00

sessions

feat(ml): enable openvino for cpu (#22948 )

2026-03-07 18:40:43 +00:00

__init__.py

chore(ml): installable package (#17153 )

2025-03-27 19:49:09 +00:00

__main__.py

fix(ml): ipv6 check (#22735 )