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Update Dockerfile for Raspberry Pi Support #8123

Merged
merged 17 commits into from
Feb 19, 2024
Merged

Update Dockerfile for Raspberry Pi Support #8123

merged 17 commits into from
Feb 19, 2024

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lakshanthad
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@lakshanthad lakshanthad commented Feb 9, 2024

This PR updates Docker support for the latest Raspberry Pi Bookworm OS which is based on Debian 12.

I have read the CLA Document and I hereby sign the CLA

🛠️ PR Summary

Made with ❤️ by Ultralytics Actions

🌟 Summary

Adding Docker support for Raspberry Pi 🥧🐍

📊 Key Changes

  • New Dockerfile-raspberrypi file for building Ultralytics images on Raspberry Pi
  • Based on the Debian Bookworm image for ARM64 architectures
  • Installation of dependencies tailored to Raspberry Pi compatibility
  • Provides a YOLOv8n pretrained model file for immediate use

🎯 Purpose & Impact

  • 🎯 Purpose: Enhance the accessibility of Ultralytics software on Raspberry Pi devices, making it possible to run Ultralytics in a containerized environment on ARM64 devices.
  • 👥 Impact: Raspberry Pi users can now easily deploy Ultralytics in Docker, leveraging the ease of Docker for managing dependencies and environments. This expands the reach of Ultralytics to a wider range of platforms and could potentially boost adoption for edge computing applications on Raspberry Pi.

🛠️ PR Summary

Made with ❤️ by Ultralytics Actions

🌟 Summary

Update to Dockerfile for ARM64: Switch to Debian base and add needed packages.

📊 Key Changes

  • 🍏 Expanded compatibility to include Apple's M2 and future M3 chips alongside the M1, as well as other ARM architectures.
  • 🐧 Switched from an Ubuntu base image to a Debian "bookworm-slim" base image for the ARM64 Docker build.
  • 👷‍♂️ Added cmake and build-essential to the list of installed packages, required for building onnxsim when exporting models to tflite format.

🎯 Purpose & Impact

  • 🔨 The compatibility expansion ensures broader support for users with newer Apple Silicon chips and maintains support for other popular ARM architectures.
  • 🛠 The switch to Debian may provide a more lightweight and streamlined container environment.
  • ✨ The additional packages allow for enhanced functionality within the Docker environment, enabling users to perform more tasks without additional setup, especially in model conversions.
  • 🚀 These updates aim to improve the overall developer and user experience by ensuring compatibility, easing deployment, and reducing potential issues when interacting with Ultralytics projects on ARM64 platforms.

This is based on Debian 12 which is the same flavor installed on the latest Raspberry Pi Bookworm OS
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CLA Assistant Lite bot All Contributors have signed the CLA. ✅

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👋 Hello @lakshanthad, thank you for submitting an Ultralytics YOLOv8 🚀 PR! To allow your work to be integrated as seamlessly as possible, we advise you to:

  • ✅ Verify your PR is up-to-date with ultralytics/ultralytics main branch. If your PR is behind you can update your code by clicking the 'Update branch' button or by running git pull and git merge main locally.
  • ✅ Verify all YOLOv8 Continuous Integration (CI) checks are passing.
  • ✅ Update YOLOv8 Docs for any new or updated features.
  • ✅ Reduce changes to the absolute minimum required for your bug fix or feature addition. "It is not daily increase but daily decrease, hack away the unessential. The closer to the source, the less wastage there is." — Bruce Lee

See our Contributing Guide for details and let us know if you have any questions!

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codecov bot commented Feb 9, 2024

Codecov Report

All modified and coverable lines are covered by tests ✅

Comparison is base (9e24743) 75.75% compared to head (d03c73e) 39.06%.

Additional details and impacted files
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##             main    #8123       +/-   ##
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@lakshanthad
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I have read the CLA Document and I sign the CLA

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@glenn-jocher

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@lakshanthad thanks, looks good! This won't autodeploy to Dockerhub without some additions to the Action also in https://github.com/ultralytics/ultralytics/blob/main/.github/workflows/docker.yaml

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@lakshanthad also we need some updates to the Docs Quickstart page that explains the Dockerfile types and their purpose in https://github.com/ultralytics/ultralytics/blob/main/docs/en/quickstart.md, I think just adding this Dockerfile to the bullet points there should suffice.

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glenn-jocher commented Feb 10, 2024

@lakshanthad additionally add a line to https://docs.ultralytics.com/guides/docker-quickstart/

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@lakshanthad was reviewing this some more and it's unclear to me the benefits of creating two arm64/v8 images. Since we already have Dockerfile-arm64 with an ubuntu base, we'd have two nearly identical Dockerfiles with duplicate maintenance no?

Also we get hurt on our security scans if our image bases have more vulnerabilities, and a check between the two bases shows that:

  • Slim bookworm is larger than ubuntu 22.04
  • Slim bookworm introduces an additional High Severity vulnerability

I used Dockerhub to check both:

Screenshot 2024-02-10 at 19 52 31

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lakshanthad commented Feb 12, 2024

Hello @glenn-jocher,
I understand your concerns. The reason I created a separate Dockerfile for Raspberry Pi with Debian slim bookworm (Debian 12) is that the latest official Raspberry Pi OS Bookworm (based on Debian 12) is running the same flavor and thought would be better to have a Docker which has similar environment as the RPi OS (example: Debian bookworm and latest RPi OS has same Python version). In this way, if there are any issues need to fix for Raspberry Pi OS side, we can reflect the same changes for the Docker image based on Bookworm.

Also, the high severity vulnerabilities on the official Debian image seem to be gone now:
https://hub.docker.com/layers/library/debian/bookworm-slim/images/sha256-6bdbd579ba71f6855deecf57e64524921aed6b97ff1e5195436f244d2cb42b12?context=explore

@lakshanthad
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@glenn-jocher If you are on the same page as me with my previous comment, I can make further changes as well inside the below files to reflect the new "raspberrypi" Dockerfile.

In this case, we can get rid of "arm64" Dockerfile. But that will remain us with wanting another Dockerfile for Apple Silicon as well.

@lakshanthad lakshanthad changed the title Add Dockerfile for Raspberry Pi Support Update Dockerfile for Raspberry Pi Support Feb 19, 2024
@lakshanthad
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@glenn-jocher FYI

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lakshanthad commented Feb 19, 2024

Please help to test on Apple Silicon and verify as well. I do not have Apple Silicon to test here.

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glenn-jocher commented Feb 19, 2024

@lakshanthad ah, we'll have to send you a Macbook too now 😂

Apple M1 runners are actually available for free now in GitHub, i.e. the macos-14 runners in the CI below are running on Apple M1 chips, I wonder if we should add Docker tests on these.

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lakshanthad commented Feb 19, 2024

@glenn-jocher

haha. will be nice to have Apple silicon :)

You can make the call to add the Docker tests on the M1 chips. I think there is nothing to lose by adding that.

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@lakshanthad yeah that would be really nice, but also a bit complicated right now since we're running all Docker publishing and testing right now on a single ubuntu-latest type in https://github.com/ultralytics/ultralytics/blob/main/.github/workflows/docker.yaml

@Burhan-Q can you add a TODO to update docker.yaml for arm64-runner build and testing on macos-14?

@glenn-jocher glenn-jocher merged commit 61088b4 into ultralytics:main Feb 19, 2024
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@lakshanthad PR merged!!

@Burhan-Q Burhan-Q mentioned this pull request Feb 19, 2024
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DannyCooler added a commit to ecs-enerserv/ultralytics that referenced this pull request Mar 28, 2024
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* Add `distance calculation` feature in `vision-eye` (ultralytics#8616)

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* `ultralytics 8.1.21` Add YOLOv8-World-v2 models (ultralytics#8580)

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* `ultralytics 8.1.22` HUB model `pathlib` fix (ultralytics#8621)

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* `ultralytics 8.1.23` add YOLOv9-C and E models (ultralytics#8571)

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* Add settings `runs_dir` == `datasets_dir` warning (ultralytics#8653)

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* Add Ultralytics HUB Cloud Training banner to Docs (ultralytics#8656)

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* Update CITATION.cff with cffinit corrections (ultralytics#8658)

* Update Colab notebook for YOLOv8.1 (ultralytics#8660)

* `ultralytics 8.1.24` new OpenVINO 2023.3 export updates (ultralytics#8417)

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* OBB: Fix when training on zip data (ultralytics#8680)

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* Object Counter improvements (ultralytics#8648)

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* Clarify triton server boolean value (ultralytics#8532)

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* Add `model.eval()` in TensorBoad graph visualization to avoid BN stats changes (ultralytics#8629)

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* Add domain checks to CI docs page (ultralytics#8714)

* `ultralytics 8.1.25` OpenVINO `LATENCY` and `THROUGHPUT` modes (ultralytics#8058)

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* Add https://youtu.be/OpWpBI35A5Y to inference-api Docs (ultralytics#8717)

* OpenVino 2024.0.0 (ultralytics#8726)

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* Fix tfjs exports for ARM64 Dockerfile (ultralytics#8766)

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* Modify tuner best.pt logic to train first (ultralytics#8792)

* Update CI.md with CI links (ultralytics#8786)

* Add https://youtu.be/ZzUSXQkLbNw to Integration Docs (ultralytics#8793)

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* `ultralytics 8.1.25` fix `**kwargs: (dict)` warnings (ultralytics#8815)

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* Add docs guide terminal images (ultralytics#8819)

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* `RTDETRDetectionModel` TorchScript, ONNX Predict and Val support (ultralytics#8818)

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* New `MLFLOW_KEEP_RUN_ACTIVE` flag for enhanced MLflow run management (ultralytics#8808)

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* `ultralytics 8.1.26` `LoadImagesAndVideos` batched inference (ultralytics#8817)

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* Update `fraction` arg to employ a random selection (ultralytics#8234)

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* Batch inference fixes (ultralytics#8854)

* Integrate OpenVINO `CUMULATIVE_THROUGHPUT` mode batched inference (ultralytics#8834)

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* Add PaddlePaddle Docs Integrations Page (ultralytics#8858)

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* `ultralytics 8.1.27` batched tracking fixes (ultralytics#8842)

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* Faster batch `same_shapes` (ultralytics#8851)

* More robust PNNX downloads (ultralytics#8866)

* Fix `test_mlflow_keep_run_active()` (ultralytics#8868)

* Add polygon regions drawing support in `object-counting.md` and minor docs update (ultralytics#8885)

* Add TFLite Edge TPU Docs Integrations Page  (ultralytics#8900)

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* Update Docs README (ultralytics#8919)

* Fix `names` bug when exporting YOLOv8-World to ONNX (ultralytics#8941)

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* New test for labels and crops (ultralytics#8861)

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* Optimize TFJS export on ARM64 (ultralytics#8946)

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* Auto-format by https://ultralytics.com/actions

* `ultralytics 8.1.28` avoid * ops on bool Tensors for RT-DETR OpenVINO export (ultralytics#8937)

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* Add https://youtu.be/YDXKa1EljmU and https://youtu.be/5BO0Il_YYAg to Docs (ultralytics#8958)

* `ultralytics 8.1.29` improved disk space checking on correct path (ultralytics#8977)

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* Add OpenVINO Latency vs Throughput modes Docs page (ultralytics#9001)

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* Add `brain-tumor` dataset docs page (ultralytics#9041)

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* Fix Neural Magic links (ultralytics#9144)

* Updating a typo on paddlepaddle.md (ultralytics#9108)

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* `ultralytics 8.1.30` add advanced HUB train arguments (ultralytics#9110)

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* fix yolo classify model loading error (ultralytics#9196)

* Add TF GraphDef Docs Integrations Page (ultralytics#9203)

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* `ultralytics 8.1.31` NCNN and CLIP updates (ultralytics#9235)

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* Fix TypeError in check_cfg() (ultralytics#9245)

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* Add https://youtu.be/aeAX6vWpfR0 to docs & `african-wildlife` dataset docs page (ultralytics#9102)

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* Add TF SavedModel Docs Integrations Page (ultralytics#9162)

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* Limit `ray<2.9.3` due to bug in `ray==2.10.0` (ultralytics#9254)

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* `ultralytics 8.1.32` fix CLIP backwards compatibility (ultralytics#9253)

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* Conda cv2 ImportError libEGL.so.1 fix (ultralytics#9255)

* Fix `IS_PYTHON_3_12` bug (ultralytics#9258)

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* Reverse IoU threshold for NMS docs descriptions (ultralytics#9151)

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* Add `bgr` hyperparameter (ultralytics#9139)

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* Update pyproject.toml `[tool.pytest.ini_options]` (ultralytics#9259)

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* Fix OpenVINO missing batch-size bug (ultralytics#9264)

* `ultralytics 8.1.33` fix HUB model checks (ultralytics#9153)

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* Update Discord and Contributing Guide URLs (ultralytics#9270)

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* Add https://youtu.be/uDrn9QZJ2lk and `object_counting.py`, `ai_gym.py` updates (ultralytics#9265)

* `ultralytics 8.1.34` Inference API robust imgsz checks (ultralytics#9274)

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* Bump contributor-assistant/github-action from 2.3.1 to 2.3.2 in /.github/workflows (ultralytics#9279)

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* Add https://youtu.be/u3pLlgzUeV8 to docs (ultralytics#9367)

* Fix typo in YOLOv8-Libtorch-CPP-Inference (ultralytics#9330)

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* Simplify metrics calculation (ultralytics#9338)

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* Fix typo in example readme (ultralytics#9306)

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* Specify YOLODataset task arg during INT8 calibration (ultralytics#9309)

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* `ultralytics 8.1.35` simplify network modules (ultralytics#9321)

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---------

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hmurari pushed a commit to hmurari/ultralytics that referenced this pull request Apr 17, 2024
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gkinman pushed a commit to Octasic/ultralytics that referenced this pull request May 30, 2024
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