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immich/machine-learning
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Zeeshan Khan 34201be74c
feat(ml) backend takes image over HTTP (#2783) 
* using pydantic BaseSetting

* ML API takes image file as input

* keeping image in memory

* reducing duplicate code

* using bytes instead of UploadFile & other small code improvements

* removed form-multipart, using HTTP body

* format code

---------

Co-authored-by: Alex Tran <alex.tran1502@gmail.com>
2023-06-17 22:49:19 -05:00
..
app feat(ml) backend takes image over HTTP (#2783) 2023-06-17 22:49:19 -05:00
.dockerignore feat: facial recognition (#2180) 2023-05-17 12:07:17 -05:00
.gitignore feat: facial recognition (#2180) 2023-05-17 12:07:17 -05:00
Dockerfile chore(deps): update python:3.11.4-slim-bullseye docker digest to 91d194f (#2797) 2023-06-16 11:38:59 -05:00
poetry.lock feat(ml) backend takes image over HTTP (#2783) 2023-06-17 22:49:19 -05:00
pyproject.toml feat(ml): model unloading (#2661) 2023-06-06 20:48:51 -05:00
README.md chore(ml): updated dockerfile, added typing, packaging (#2642) 2023-06-05 09:40:48 -05:00

README.md

Immich Machine Learning

  • Image classification
  • CLIP embeddings
  • Facial recognition

Setup

This project uses Poetry, so be sure to install it first. Running poetry install --no-root --with dev will install everything you need in an isolated virtual environment.

To add or remove dependencies, you can use the commands poetry add $PACKAGE_NAME and poetry remove $PACKAGE_NAME, respectively. Be sure to commit the poetry.lock and pyproject.toml files to reflect any changes in dependencies.