immich/machine-learning

Immich Machine Learning

• CLIP embeddings
• Facial recognition

Setup

This project uses Poetry, so be sure to install it first. Running poetry install --no-root --with dev --with cpu will install everything you need in an isolated virtual environment. CUDA and OpenVINO are supported as acceleration APIs. To use them, you can replace --with cpu with either of --with cuda or --with openvino.

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 with poetry lock --no-update to reflect any changes in dependencies.

Load Testing

To measure inference throughput and latency, you can use Locust using the provided locustfile.py. Locust works by querying the model endpoints and aggregating their statistics, meaning the app must be deployed. You can change the models or adjust options like score thresholds through the Locust UI.

To get started, you can simply run locust --web-host 127.0.0.1 and open localhost:8089 in a browser to access the UI. See the Locust documentation for more info on running Locust.

Note that in Locust's jargon, concurrency is measured in users, and each user runs one task at a time. To achieve a particular per-endpoint concurrency, multiply that number by the number of endpoints to be queried. For example, if there are 3 endpoints and you want each of them to receive 8 requests at a time, you should set the number of users to 24.

Facial Recognition

Acknowledgements

This project utilizes facial recognition models from the InsightFace project. We appreciate the work put into developing these models, which have been beneficial to the machine learning part of this project.

Used Models

• antelopev2
• buffalo_l
• buffalo_m
• buffalo_s

License and Use Restrictions

We have received permission to use the InsightFace facial recognition models in our project, as granted via email by Jia Guo (guojia@insightface.ai) on 18th March 2023. However, it's important to note that this permission does not extend to the redistribution or commercial use of their models by third parties. Users and developers interested in using these models should review the licensing terms provided in the InsightFace GitHub repository.

For more information on the capabilities of the InsightFace models and to ensure compliance with their license, please refer to their official repository. Adhering to the specified licensing terms is crucial for the respectful and lawful use of their work.