インスタンスのセグメント化 Python* デモ#

usage: instance_segmentation_demo.py [-h] -m MODEL [--adapter {openvino,ovms}] 
                                     -i INPUT [-d DEVICE] --labels LABELS [-t PROB_THRESHOLD] 
                                     [--no_track] [--show_scores] 
                                     [--show_boxes] [--layout LAYOUT] 
                                     [-nireq NUM_INFER_REQUESTS] [-nstreams NUM_STREAMS] 
                                     [-nthreads NUM_THREADS] [--loop] 
                                     [-o OUTPUT] [-limit OUTPUT_LIMIT] 
                                     [--no_show] [--output_resolution OUTPUT_RESOLUTION] 
                                     [-u UTILIZATION_MONITORS] [-r] 

optional arguments: 
  -h, --help            show this help message and exitz 

Options: 
  -m MODEL, --model MODEL 
                        Required. Path to an .xml file with a trained model or address of model inference service if using ovms adapter.
  --adapter {openvino,ovms} 
                        Optional.Specify the model adapter.Default is openvino.
  -i INPUT, --input INPUT 
                        Required.An input to process.The input must be a single image, 
                        a folder of images, video file or camera id. 
  -d DEVICE, --device DEVICE 
                        Optional.Specify the target device to infer on; CPU or 
                        GPU is acceptable.The demo will look for a suitable plugin for device specified.Default value is CPU.

Common model options: 
  --labels LABELS       Required. Path to a text file with class labels.
  -t PROB_THRESHOLD, --prob_threshold PROB_THRESHOLD 
                        Optional. Probability threshold for detections filtering.
  --no_track            Optional. Disable object tracking for video/camera input.
  --show_scores         Optional. Show detection scores.
  --show_boxes          Optional. Show bounding boxes.
  --layout LAYOUT       Optional.Model inputs layouts. Format "[<layout>]" or "<input1>[<layout1>],<input2>[<layout2>]" in case of more than one input. To define layout you should use only capital letters 

Inference options: 
  -nireq NUM_INFER_REQUESTS, --num_infer_requests NUM_INFER_REQUESTS 
                        Optional.Number of infer requests 
  -nstreams NUM_STREAMS, --num_streams NUM_STREAMS 
                        Optional. Number of streams to use for inference on the CPU or/and GPU in throughput mode (for HETERO and MULTI device cases use format <device1>:<nstreams1>,<device2>:<nstreams2> or just <nstreams>).
  -nthreads NUM_THREADS, --num_threads NUM_THREADS 
                        Optional.Number of threads to use for inference on CPU (including HETERO cases).

Input/output options: 
  --loop                Optional. Enable reading the input in a loop.
  -o OUTPUT, --output OUTPUT 
                        Optional. Name of the output file(s) to save. Frames of odd width or height can be truncated.See https://github.com/opencv/opencv/pull/24086 
  -limit OUTPUT_LIMIT, --output_limit OUTPUT_LIMIT 
                        Optional. Number of frames to store in output. If 0 is set, all frames are stored.
  --no_show 
                        Optional. Don't show output.
  --output_resolution OUTPUT_RESOLUTION 
                        Optional. Specify the maximum output window resolution in (width x height) format. Example: 1280x720. Input frame size used by default.
  -u UTILIZATION_MONITORS, --utilization_monitors UTILIZATION_MONITORS 
                        Optional. List of monitors to show initially.

Debug options: 
  -r, --raw_output_message 
                          Optional. Output inference results raw values showing.