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- # Copyright (c) OpenMMLab. All rights reserved.
- executor_cfg = dict(
- # Basic configurations of the executor
- name='Pose Estimation',
- camera_id=0,
- # Define nodes.
- # The configuration of a node usually includes:
- # 1. 'type': Node class name
- # 2. 'name': Node name
- # 3. I/O buffers (e.g. 'input_buffer', 'output_buffer'): specify the
- # input and output buffer names. This may depend on the node class.
- # 4. 'enable_key': assign a hot-key to toggle enable/disable this node.
- # This may depend on the node class.
- # 5. Other class-specific arguments
- nodes=[
- # 'DetectorNode':
- # This node performs object detection from the frame image using an
- # MMDetection model.
- dict(
- type='DetectorNode',
- name='detector',
- model_config='projects/rtmpose/rtmdet/person/'
- 'rtmdet_nano_320-8xb32_coco-person.py',
- model_checkpoint='https://download.openmmlab.com/mmpose/v1/'
- 'projects/rtmpose/rtmdet_nano_8xb32-100e_coco-obj365-person-05d8511e.pth', # noqa
- input_buffer='_input_', # `_input_` is an executor-reserved buffer
- output_buffer='det_result'),
- # 'TopdownPoseEstimatorNode':
- # This node performs keypoint detection from the frame image using an
- # MMPose top-down model. Detection results is needed.
- dict(
- type='TopdownPoseEstimatorNode',
- name='human pose estimator',
- model_config='projects/rtmpose/rtmpose/body_2d_keypoint/'
- 'rtmpose-t_8xb256-420e_coco-256x192.py',
- model_checkpoint='https://download.openmmlab.com/mmpose/v1/'
- 'projects/rtmpose/rtmpose-tiny_simcc-aic-coco_pt-aic-coco_420e-256x192-cfc8f33d_20230126.pth', # noqa
- labels=['person'],
- input_buffer='det_result',
- output_buffer='human_pose'),
- # 'ObjectAssignerNode':
- # This node binds the latest model inference result with the current
- # frame. (This means the frame image and inference result may be
- # asynchronous).
- dict(
- type='ObjectAssignerNode',
- name='object assigner',
- frame_buffer='_frame_', # `_frame_` is an executor-reserved buffer
- object_buffer='human_pose',
- output_buffer='frame'),
- # 'ObjectVisualizerNode':
- # This node draw the pose visualization result in the frame image.
- # Pose results is needed.
- dict(
- type='ObjectVisualizerNode',
- name='object visualizer',
- enable_key='v',
- enable=True,
- show_bbox=True,
- must_have_keypoint=False,
- show_keypoint=True,
- input_buffer='frame',
- output_buffer='vis'),
- # 'NoticeBoardNode':
- # This node show a notice board with given content, e.g. help
- # information.
- dict(
- type='NoticeBoardNode',
- name='instruction',
- enable_key='h',
- enable=True,
- input_buffer='vis',
- output_buffer='vis_notice',
- content_lines=[
- 'This is a demo for pose visualization and simple image '
- 'effects. Have fun!', '', 'Hot-keys:',
- '"v": Pose estimation result visualization',
- '"h": Show help information',
- '"m": Show diagnostic information', '"q": Exit'
- ],
- ),
- # 'MonitorNode':
- # This node show diagnostic information in the frame image. It can
- # be used for debugging or monitoring system resource status.
- dict(
- type='MonitorNode',
- name='monitor',
- enable_key='m',
- enable=False,
- input_buffer='vis_notice',
- output_buffer='display'),
- # 'RecorderNode':
- # This node save the output video into a file.
- dict(
- type='RecorderNode',
- name='recorder',
- out_video_file='webcam_api_demo.mp4',
- input_buffer='display',
- output_buffer='_display_'
- # `_display_` is an executor-reserved buffer
- )
- ])
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