157 lines
6.5 KiB
Markdown
157 lines
6.5 KiB
Markdown
# Coral Dev Board Setup (experimental)
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**Disclaimer**: Running MediaPipe on Coral is experimental, and this process may
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not be exact and is subject to change. These instructions have only been tested
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on the [Coral Dev Board](https://coral.ai/products/dev-board/)
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running [Mendel Enterprise Day 13](https://coral.ai/software/) OS and
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using [Diploria2](https://github.com/google-coral/edgetpu/tree/diploria2)
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edgetpu libs, and may vary for different devices and workstations.
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This file describes how to prepare a Coral Dev Board and setup a Linux
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Docker container for building MediaPipe applications that run on Edge TPU.
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## Before creating the Docker
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* (on host machine) run _setup.sh_ from MediaPipe root directory
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sh mediapipe/examples/coral/setup.sh
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* Setup the coral device via [here](https://coral.withgoogle.com/docs/dev-board/get-started/), and ensure the _mdt_ command works
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Note: alias mdt="python3 -m mdt.main" may be needed on some systems
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* (on coral device) prepare MediaPipe
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cd ~
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sudo apt-get update && sudo apt-get install -y git
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git clone https://github.com/google/mediapipe.git
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mkdir mediapipe/bazel-bin
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* (on coral device) install opencv 3.2
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sudo apt-get update && sudo apt-get install -y libopencv-dev
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* (on coral device) find all opencv libs
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find /usr/lib/aarch64-linux-gnu/ -name 'libopencv*so'
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* (on host machine) copy core opencv libs from coral device to a local folder inside MediaPipe checkout:
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# in root level mediapipe folder #
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mdt pull /usr/lib/aarch64-linux-gnu/libopencv_core.so opencv32_arm64_libs
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mdt pull /usr/lib/aarch64-linux-gnu/libopencv_calib3d.so opencv32_arm64_libs
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mdt pull /usr/lib/aarch64-linux-gnu/libopencv_features2d.so opencv32_arm64_libs
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mdt pull /usr/lib/aarch64-linux-gnu/libopencv_highgui.so opencv32_arm64_libs
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mdt pull /usr/lib/aarch64-linux-gnu/libopencv_imgcodecs.so opencv32_arm64_libs
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mdt pull /usr/lib/aarch64-linux-gnu/libopencv_imgproc.so opencv32_arm64_libs
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mdt pull /usr/lib/aarch64-linux-gnu/libopencv_video.so opencv32_arm64_libs
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mdt pull /usr/lib/aarch64-linux-gnu/libopencv_videoio.so opencv32_arm64_libs
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* (on host machine) Create and start the docker environment
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# from mediapipe root level directory #
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docker build -t coral .
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docker run -it --name coral coral:latest
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## Inside the Docker environment
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* Update library paths in /mediapipe/third_party/opencv_linux.BUILD
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(replace 'x86_64-linux-gnu' with 'aarch64-linux-gnu')
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"lib/aarch64-linux-gnu/libopencv_core.so",
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"lib/aarch64-linux-gnu/libopencv_calib3d.so",
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"lib/aarch64-linux-gnu/libopencv_features2d.so",
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"lib/aarch64-linux-gnu/libopencv_highgui.so",
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"lib/aarch64-linux-gnu/libopencv_imgcodecs.so",
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"lib/aarch64-linux-gnu/libopencv_imgproc.so",
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"lib/aarch64-linux-gnu/libopencv_video.so",
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"lib/aarch64-linux-gnu/libopencv_videoio.so",
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* Attempt to build hello world (to download external deps)
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bazel build -c opt --define MEDIAPIPE_DISABLE_GPU=1 mediapipe/examples/desktop/hello_world:hello_world
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* Edit /edgetpu/libedgetpu/BUILD
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to add this build target
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cc_library(
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name = "lib",
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srcs = [
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"libedgetpu.so",
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],
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visibility = ["//visibility:public"],
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)
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* Edit /edgetpu/WORKSPACE
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update /mediapipe/WORKSPACE TENSORFLOW_* variables to match what /edgetpu/WORKSPACE has:
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grep TENSORFLOW_ /mediapipe/WORKSPACE
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grep TENSORFLOW_ /edgetpu/WORKSPACE
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# Make sure the /mediapipe/WORKSPACE _TENSORFLOW_GIT_COMMIT and _TENSORFLOW_SHA256
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# match the /edgetpu/WORKSPACE TENSORFLOW_COMMIT and TENSORFLOW_SHA256 respectively.
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# If they do not match, modify /mediapipe/WORKSPACE to match what /edgetpu/WORKSPACE has.
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# Also comment out the MediaPipe org_tensorflow patch section.
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* Edit /mediapipe/mediapipe/calculators/tflite/BUILD to change rules for *tflite_inference_calculator.cc*
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sed -i 's/\":tflite_inference_calculator_cc_proto\",/\":tflite_inference_calculator_cc_proto\",\n\t\"@edgetpu\/\/:header\",\n\t\"@libedgetpu\/\/:lib\",/g' /mediapipe/mediapipe/calculators/tflite/BUILD
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The above command should add
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"@edgetpu//:header",
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"@libedgetpu//:lib",
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to the _deps_ of tflite_inference_calculator.cc
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Now also remove XNNPACK deps:
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sed -i 's/\"@org_tensorflow\/\/tensorflow\/lite\/delegates\/xnnpack/#\"@org_tensorflow\/\/tensorflow\/lite\/delegates\/xnnpack/g' /mediapipe/mediapipe/calculators/tflite/BUILD
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#### Now try cross-compiling for device
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* Object detection demo
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bazel build -c opt --crosstool_top=@crosstool//:toolchains --compiler=gcc --cpu=aarch64 --define MEDIAPIPE_DISABLE_GPU=1 --copt -DMEDIAPIPE_EDGE_TPU --copt=-flax-vector-conversions mediapipe/examples/coral:object_detection_tpu
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Copy object_detection_tpu binary to the MediaPipe checkout on the coral device
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# outside docker env, open new terminal on host machine #
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docker ps
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docker cp <container-id>:/mediapipe/bazel-bin/mediapipe/examples/coral/object_detection_tpu /tmp/.
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mdt push /tmp/object_detection_tpu /home/mendel/mediapipe/bazel-bin/.
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* Face detection demo
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bazel build -c opt --crosstool_top=@crosstool//:toolchains --compiler=gcc --cpu=aarch64 --define MEDIAPIPE_DISABLE_GPU=1 --copt -DMEDIAPIPE_EDGE_TPU --copt=-flax-vector-conversions mediapipe/examples/coral:face_detection_tpu
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Copy face_detection_tpu binary to the MediaPipe checkout on the coral device
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# outside docker env, open new terminal on host machine #
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docker ps
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docker cp <container-id>:/mediapipe/bazel-bin/mediapipe/examples/coral/face_detection_tpu /tmp/.
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mdt push /tmp/face_detection_tpu /home/mendel/mediapipe/bazel-bin/.
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## On the coral device (with display)
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# Object detection
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cd ~/mediapipe
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chmod +x bazel-bin/object_detection_tpu
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export GLOG_logtostderr=1
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bazel-bin/object_detection_tpu --calculator_graph_config_file=mediapipe/examples/coral/graphs/object_detection_desktop_live.pbtxt
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# Face detection
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cd ~/mediapipe
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chmod +x bazel-bin/face_detection_tpu
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export GLOG_logtostderr=1
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bazel-bin/face_detection_tpu --calculator_graph_config_file=mediapipe/examples/coral/graphs/face_detection_desktop_live.pbtxt
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