Open Model Zoo

Open Model ZooはOpenVINOを知るためのデモアプリケーションです


通常、インストールされているのは、
/opt/intel/openvino/deployment_tools/open_model_zoo/demos
で、複数のアプリケーションが格納されています

デモ名称 場所 内容
3D Human Pose Estimation Python* Demo python_demos/human_pose_estimation_3d_demo 3D human pose estimation demo.
Action Recognition Python* Demopython_demos/action_recognition Demo application for Action Recognition algorithm, which classifies actions that are being performed on input video.
Crossroad Camera C++ Democrossroad_camera_demo Person Detection followed by the Person Attributes Recognition and Person Reidentification Retail, supports images/video and camera inputs.
Gaze Estimation C++ Demogaze_estimation_demo Face detection followed by gaze estimation, head pose estimation and facial landmarks regression.
Human Pose Estimation C++ Demohuman_pose_estimation_demo Human pose estimation demo.
Image Retrieval Python* Demopython_demos/image_retrieval_demo The demo demonstrates how to run Image Retrieval models using OpenVINO.
Image Segmentation C++ Demo segmentation_demo Inference of image segmentation networks like FCN8 (the demo supports only images as inputs)
Image Segmentation Python Demopython_demos/segmentation_demo Inference of image segmentation networks like FCN8 (the demo supports only images as inputs)
Instance Segmentation Python* Demo python_demos/instance_segmentation_demo Inference of instance segmentation networks trained in `Detectron` or `maskrcnn-benchmark`.
Interactive Face Detection C++ Demointeractive_face_detection_demo Face Detection coupled with Age/Gender, Head-Pose, Emotion, and Facial Landmarks detectors. Supports video and camera inputs.
Interactive Face Recognition Python* Demopython_demos/face_recognition_demo Face Detection coupled with Head-Pose, Facial Landmarks and Face Recognition detectors. Supports video and camera inputs.
Mask R-CNN C++ Demo for TensorFlow* Object Detection API mask_rcnn_demo Inference of instance segmentation networks created with TensorFlow\* Object Detection API.
Multi-Camera Multi-Person Tracking Python* Demopython_demos/multi_camera_multi_person_tracking  Demo application for multiple persons tracking on multiple cameras.
Multi-Channel C++ Demos multi_channel Several demo applications for multi-channel scenarios.
Object Detection for CenterNet Python* Demoobject_detection_demo_centernet Demo application for CenterNet object detection network.
Object Detection for Faster R-CNN C++ Demoobject_detection_demo_faster_rcnn Inference of object detection networks like Faster R-CNN (the demo supports only images as inputs).
Object Detection for SSD C++ Demoobject_detection_demo_ssd_async Demo application for SSD-based Object Detection networks, new Async API performance showcase, and simple OpenCV interoperability (supports video and camera inputs).
Object Detection for YOLO V3 C++ Demoobject_detection_demo_yolov3_async Demo application for YOLOV3-based Object Detection networks, new Async API performance showcase, and simple OpenCV interoperability (supports video and camera inputs).
Pedestrian Tracker C++ Demopedestrian_tracker_demo Demo application for pedestrian tracking scenario.
Security Barrier Camera C++ Demosecurity_barrier_camera_demo Vehicle Detection followed by the Vehicle Attributes and License-Plate Recognition, supports images/video and camera inputs.
Single Human Pose Estimation Python* Demopython_demos/single_human_pose_estimation_demo 2D human pose estimation demo.
Smart Classroom C++ Demosmart_classroom_demo Face recognition and action detection demo for classroom environment.
Super Resolution C++ Demosuper_resolution_demo Super Resolution demo (the demo supports only images as inputs). It enhances the resolution of the input image.
Text Detection C++ Demotext_detection_demo Text Detection demo. It detects and recognizes multi-oriented scene text on an input image and puts a bounding box around detected area.
Text Spotting Python* Demopython_demos/text_spotting_demo The demo demonstrates how to run Text Spotting models.

C++サンプルのビルド

/opt/intel/openvino/deployment_tools/open_model_zoo/demos
ディレクトリにあるbuild_demos.shでビルドできます
このコマンドを実行すると、
ホームディレクトリ/omz_demos_build が作成され、その中の、
omz_demos_build/intel64/Release
に実行ファイルがビルドされます