Fix ARM64 Docker building (#13217)

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

.github/workflows/docker.yaml

@@ -18,22 +18,26 @@ on:
       Dockerfile-cpu:
         type: boolean
         description: Use Dockerfile-cpu
+        default: true
       Dockerfile-arm64:
         type: boolean
         description: Use Dockerfile-arm64
+        default: true
       Dockerfile-jetson:
         type: boolean
         description: Use Dockerfile-jetson
+        default: true
       Dockerfile-python:
         type: boolean
         description: Use Dockerfile-python
+        default: true
       Dockerfile-conda:
         type: boolean
         description: Use Dockerfile-conda
+        default: true
       push:
         type: boolean
-        description: Push images to Docker Hub
-        default: true
+        description: Publish all Images to Docker Hub
 
 jobs:
   docker:

docker/Dockerfile-arm64

@@ -33,8 +33,9 @@ ADD https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt $A
 RUN rm -rf /usr/lib/python3.11/EXTERNALLY-MANAGED
 
 # Install pip packages
+# Install tensorstore from .whl because PyPI does not include aarch64 binaries
 RUN python3 -m pip install --upgrade pip wheel
-RUN pip install --no-cache-dir -e ".[export]"
+RUN pip install --no-cache-dir https://github.com/ultralytics/yolov5/releases/download/v7.0/tensorstore-0.1.59-cp311-cp311-linux_aarch64.whl -e ".[export]"
 
 # Creates a symbolic link to make 'python' point to 'python3'
 RUN ln -sf /usr/bin/python3 /usr/bin/python

docker/Dockerfile-jetson

@@ -32,12 +32,11 @@ ADD https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt $A
 RUN grep -v "opencv-python" pyproject.toml > temp.toml && mv temp.toml pyproject.toml
 
 # Download onnxruntime-gpu 1.15.1 for Jetson Linux 35.2.1 (JetPack 5.1). Other versions can be seen in https://elinux.org/Jetson_Zoo#ONNX_Runtime
-RUN wget https://nvidia.box.com/shared/static/mvdcltm9ewdy2d5nurkiqorofz1s53ww.whl -O onnxruntime_gpu-1.15.1-cp38-cp38-linux_aarch64.whl
+ADD https://nvidia.box.com/shared/static/mvdcltm9ewdy2d5nurkiqorofz1s53ww.whl onnxruntime_gpu-1.15.1-cp38-cp38-linux_aarch64.whl
 
 # Install pip packages manually for TensorRT compatibility https://github.com/NVIDIA/TensorRT/issues/2567
 RUN python3 -m pip install --upgrade pip wheel
 RUN pip install onnxruntime_gpu-1.15.1-cp38-cp38-linux_aarch64.whl
-RUN pip install --no-cache-dir tqdm matplotlib pyyaml psutil pandas onnx
 RUN pip install --no-cache-dir -e ".[export]"
 
 

pyproject.toml

@@ -102,7 +102,7 @@ export = [
     "openvino>=2024.0.0", # OpenVINO export
     "tensorflow>=2.0.0", # TF bug https://github.com/ultralytics/ultralytics/issues/5161
     "tensorflowjs>=3.9.0", # TF.js export, automatically installs tensorflow
-    "keras",  # not installed auotomatically by tensorflow>=2.16
+    "keras",  # not installed automatically by tensorflow>=2.16
     "flatbuffers>=23.5.26,<100; platform_machine == 'aarch64'", # update old 'flatbuffers' included inside tensorflow package
     "numpy==1.23.5; platform_machine == 'aarch64'", # fix error: `np.bool` was a deprecated alias for the builtin `bool` when using TensorRT models on NVIDIA Jetson
     "h5py!=3.11.0; platform_machine == 'aarch64'", # fix h5py build issues due to missing aarch64 wheels in 3.11 release
@@ -112,9 +112,6 @@ explorer = [
     "duckdb<=0.9.2", # SQL queries, duckdb==0.10.0 bug https://github.com/ultralytics/ultralytics/pull/8181
     "streamlit", # visualizing with GUI
 ]
-# tflite-support  # for TFLite model metadata
-# nvidia-pyindex  # TensorRT export
-# nvidia-tensorrt  # TensorRT export
 logging = [
     "comet", # https://docs.ultralytics.com/integrations/comet/
     "tensorboard>=2.13.0",