fix build and instructions for apple m1

This commit is contained in:
Jules Youngberg 2022-07-26 17:43:21 -07:00
parent b72fc70c01
commit 7b57938699
5 changed files with 43 additions and 22 deletions

2
.gitignore vendored
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@ -10,3 +10,5 @@ Cargo.lock
**/*.rs.bk
/refs/
/mediapipe/
/logs/
.DS_Store

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@ -12,10 +12,10 @@ edition = "2018"
name = "mediapipe"
[dependencies]
cgmath = "0.18.0"
libc = "0.2.0"
opencv = { version = "0.63", features = ["clang-runtime"] }
protobuf = "2.23.0"
cgmath = "0.18"
libc = "0.2"
opencv = "0.66"
protobuf = "2.23"
[build-dependencies]
bindgen = "*"

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@ -12,31 +12,46 @@ And heavily based on this example: https://github.com/asprecic/mediapipe-qt-inte
## setup
To run the examples clone this project.
```shell
git clone https://github.com/julesyoungberg/mediapipe-rs.git
```
Mediapipe is a framework for building AI-powered computer vision applications. It provides high level libraries exposing some of its solutions for common problems. This package makes some of these solutions available in Rust. In order to use it we must build a custom mediapipe C++ library.
Clone the modified Mediapipe repo.
Clone the modified Mediapipe repo next to `mediapipe-rs` or a project that uses `mediapipe-rs`.
```shell
git clone https://github.com/julesyoungberg/mediapipe.git
cd mediapipe
```
### building mediapipe
Build & install the mediagraph library.
### mac os
#### mac os
```shell
bazel build --define MEDIAPIPE_DISABLE_GPU=1 mediapipe:libmediagraph.dylib
sudo cp bazel-bin/mediapipe/libmediagraph.dylib /usr/local/lib/libmediagraph.dylib
cp mediapipe/mediagraph.h /usr/local/include/mediagraph.h
```
### linux (untested)
#### linux (untested)
```shell
bazel build --define MEDIAPIPE_DISABLE_GPU=1 mediapipe:mediagraph
cp bazel-bin/mediapipe/libmediagraph.so /usr/local/lib/libmediagraph.so
cp mediapipe/mediagraph.h /usr/local/include/mediagraph.h
```
### linking & building
Navigate to the project directory and create a symbolic link to the `../mediapipe/mediapipe`.
```shell
cd ../mediapipe-rs # or the path to your project
ln -s ../mediapipe/mediapipe .
```
## usage
@ -47,13 +62,7 @@ Add the following to your dependencies list in `Cargo.toml`:
mediapipe = { git = "https://github.com/julesyoungberg/mediapipe-rs" }
```
Mediapipe relies on tflite files which must be available at `./mediapipe/modules/`. The easiest way to satisfy this is by creating a symbolic link to mediapipe. Run the following command from the project directory.
```shell
ln -s ../mediapipe/mediapipe .
```
The path to mediapipe may be different depending on where you have cloned it to.
Mediapipe relies on tflite files which must be available at `./mediapipe/modules/`. The easiest way to satisfy this is by creating a symbolic link to mediapipe as explained in the `linking & building` section above.
## examples

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@ -10,7 +10,7 @@ fn main() {
.clang_arg("-std=c++14")
.clang_arg("-I/usr/local/include/opencv4")
.generate_comments(true)
.header("/usr/local/include/mediagraph.h")
.header("./mediapipe/mediagraph.h")
.allowlist_function("mediagraph.*")
.allowlist_type("mediagraph.*")
.allowlist_var("mediagraph.*")

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@ -1,3 +1,10 @@
profiler_config {
trace_enabled: true
# enable_profiler: true
trace_log_interval_count: 200
trace_log_path: "/Users/jules/workspace/mediapipe-rs/logs/"
}
# MediaPipe graph that performs pose tracking with TensorFlow Lite on CPU.
# CPU buffer. (ImageFrame)
@ -6,17 +13,19 @@ input_stream: "input_video"
# Output image with rendered results. (ImageFrame)
output_stream: "multi_pose_landmarks"
output_stream: "pose_detections"
# output_stream: "pose_detections"
output_stream: "roi_from_landmarks"
# Generates side packet to enable segmentation.
node {
calculator: "ConstantSidePacketCalculator"
output_side_packet: "PACKET:enable_segmentation"
output_side_packet: "PACKET:0:enable_segmentation"
output_side_packet: "PACKET:1:num_poses"
node_options: {
[type.googleapis.com/mediapipe.ConstantSidePacketCalculatorOptions]: {
packet { bool_value: true }
packet { bool_value: false }
packet { int_value: 2 }
}
}
}
@ -34,7 +43,7 @@ node {
node {
calculator: "FlowLimiterCalculator"
input_stream: "input_video"
input_stream: "FINISHED:output_video"
input_stream: "FINISHED:roi_from_landmarks"
input_stream_info: {
tag_index: "FINISHED"
back_edge: true
@ -47,7 +56,8 @@ node {
calculator: "MultiPoseLandmarkCpu"
input_side_packet: "ENABLE_SEGMENTATION:enable_segmentation"
input_stream: "IMAGE:throttled_input_video"
input_side_packet: "NUM_POSES:num_poses"
output_stream: "LANDMARKS:multi_pose_landmarks"
output_stream: "DETECTION:pose_detections"
# output_stream: "DETECTION:pose_detections"
output_stream: "ROI_FROM_LANDMARKS:roi_from_landmarks"
}