YOLOv2 Tiny Example Pipeline

This is an example implementation of an inference pipeline using the pipeline framework. This example pipeline executes the YOLO V2 Tiny model and decodes its output.

Compiling the Example

1. Check if model was downloaded during the env preparation step by ansible and models files exist in the folder $HOME/autoware_data/tvm_utility/models/yolo_v2_tiny.

   If not you can download them manually, see Manual Artifacts Downloading.

2. Download an example image to be used as test input. This image needs to be saved in the artifacts/yolo_v2_tiny/ folder.

   curl https://raw.githubusercontent.com/pjreddie/darknet/master/data/dog.jpg \
   > artifacts/yolo_v2_tiny/test_image_0.jpg
   

3. Build.

   colcon build --packages-up-to tvm_utility --cmake-args -DBUILD_EXAMPLE=ON
   

4. Run.

   ros2 launch tvm_utility yolo_v2_tiny_example.launch.xml
   

Parameters

Name	Type	Default Value	Description
image_filename	string	$(find-pkg-share tvm_utility)/artifacts/yolo_v2_tiny/test_image_0.jpg	Filename of the image on which to run the inference.
label_filename	string	$(find-pkg-share tvm_utility)/artifacts/yolo_v2_tiny/labels.txt	Name of file containing the human readable names of the classes. One class on each line.
anchor_filename	string	$(find-pkg-share tvm_utility)/artifacts/yolo_v2_tiny/anchors.csv	Name of file containing the anchor values for the network. Each line is one anchor. each anchor has 2 comma separated floating point values.
data_path	string	$(env HOME)/autoware_data	Packages data and artifacts directory path.

GPU backend

Vulkan is supported by default by the tvm_vendor package. It can be selected by setting the tvm_utility_BACKEND variable:

colcon build --packages-up-to tvm_utility -Dtvm_utility_BACKEND=vulkan