The contents in .yaml config file should be well structured and follow the supported rules and entity names.

Sample

pipeline_people.yaml

Pipelines:
- name: people
  inputs: [StandardCamera]
  infers:
    - name: FaceDetection
      model: /opt/intel/computer_vision_sdk/deployment_tools/intel_models/face-detection-adas-0001/FP32/face-detection-adas-0001.xml
      engine: CPU
      label: /opt/intel/computer_vision_sdk/deployment_tools/intel_models/face-detection-adas-0001/FP32/face-detection-adas-0001.labels
      batch: 1
    - name: AgeGenderRecognition
      model: /opt/intel/computer_vision_sdk/deployment_tools/intel_models/age-gender-recognition-retail-0013/FP32/age-gender-recognition-retail-0013.xml
      engine: CPU
      label: to/be/set/xxx.labels
      batch: 16
    - name: EmotionRecognition
      model: /opt/intel/computer_vision_sdk/deployment_tools/intel_models/emotions-recognition-retail-0003/FP32/emotions-recognition-retail-0003.xml
      engine: CPU
      label: /opt/intel/computer_vision_sdk/deployment_tools/intel_models/emotions-recognition-retail-0003/FP32/emotions-recognition-retail-0003.labels
      batch: 16
    - name: HeadPoseEstimation
      model: /opt/intel/computer_vision_sdk/deployment_tools/intel_models/head-pose-estimation-adas-0001/FP32/head-pose-estimation-adas-0001.xml
      engine: CPU
      label: to/be/set/xxx.labels
      batch: 16
  outputs: [ImageWindow, RosTopic, RViz]
  confidence_threshold: 0.2
  connects:
    - left: StandardCamera
      right: [FaceDetection]
    - left: FaceDetection
      right: [AgeGenderRecognition, EmotionRecognition, HeadPoseEstimation, ImageWindow, RosTopic, RViz]
    - left: AgeGenderRecognition
      right: [ImageWindow, RosTopic, RViz]
    - left: EmotionRecognition
      right: [ImageWindow, RosTopic, RViz]
    - left: HeadPoseEstimation
      right: [ImageWindow, RosTopic, RViz]

Common:

Interface Description

name

The name of this pipeline, its value can be any value other than empty.

inputs

Note:The value of the input parametar can only have one.
Currently, options for inputs are:

option	Description
StandardCamera	Any RGB camera with USB port supporting. Currently only the first USB camera if many are connected.
RealSenseCamera	Intel RealSense RGB-D Camera, directly calling RealSense Camera via librealsense plugin of openCV.
RealSenseCameraTopic	any ROS topic which is structured in image message.
Image	Any image file which can be parsed by openCV, such as .png, .jpeg.
Video	Any video file which can be parsed by openCV.

input_path

When input is Image or Video, need to use input_path to specify the path of the input file.

infers

The Inference Engine is a set of C++ classes to provides an API to read the Intermediate Representation, set the input and output formats, and execute the model on devices.

name

The name of the inference engine. Currently, the inference feature list is supported:

Inference	Description
FaceDetection	Object Detection task applied to face recognition using a sequence of neural networks.
EmotionRecognition	Emotion recognition based on detected face image.
AgeGenderRecognition	Age and gener recognition based on detected face image.
HeadPoseEstimation	Head pose estimation based on detected face image.
ObjectDetection	object detection based on SSD-based trained models.
VehicleDetection	Vehicle and passenger detection based on Intel models.
ObjectSegmentation	object detection and segmentation.

model

The path of the model. The scheme below illustrates the typical workflow for deploying a trained deep learning model.

engine

Note:Currently, only supports CPU and GPU.
options for target device are:

target device
CPU
Intel® Integrated Graphics
FPGA
Intel® Movidius™ Neural Compute Stick

label

Currently, This parameter does not work.

batch

Enable dynamic batch size for inference engine net.

outputs

Note:The value of the output parameter can be selected one or more.
Currently, options for outputs are:

option	Description
ImageWindow	window showing results
RosTopic	output the topic
RViz	display the result in rviz

confidence_threshold

Probability threshold for detections.

connects

The topology of the pipeline, left can only have one value, right can have multiple values.