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118 lines
4.7 KiB
118 lines
4.7 KiB
# Copyright (c) OpenMMLab. All rights reserved.
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runner = dict(
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# Basic configurations of the runner
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name='Human Pose and Effects',
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camera_id=0,
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camera_fps=30,
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# Define nodes.
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#
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# The configuration of a node usually includes:
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# 1. 'type': Node class name
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# 2. 'name': Node name
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# 3. I/O buffers (e.g. 'input_buffer', 'output_buffer'): specify the
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# input and output buffer names. This may depend on the node class.
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# 4. 'enable_key': assign a hot-key to toggle enable/disable this node.
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# This may depend on the node class.
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# 5. Other class-specific arguments
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nodes=[
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# 'DetectorNode':
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# This node performs object detection from the frame image using an
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# MMDetection model.
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dict(
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type='DetectorNode',
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name='Detector',
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model_config='demo/mmdetection_cfg/'
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'ssdlite_mobilenetv2_scratch_600e_coco.py',
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model_checkpoint='https://download.openmmlab.com'
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'/mmdetection/v2.0/ssd/'
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'ssdlite_mobilenetv2_scratch_600e_coco/ssdlite_mobilenetv2_'
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'scratch_600e_coco_20210629_110627-974d9307.pth',
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input_buffer='_input_', # `_input_` is a runner-reserved buffer
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output_buffer='det_result'),
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# 'TopDownPoseEstimatorNode':
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# This node performs keypoint detection from the frame image using an
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# MMPose top-down model. Detection results is needed.
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dict(
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type='TopDownPoseEstimatorNode',
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name='Human Pose Estimator',
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model_config='configs/wholebody/2d_kpt_sview_rgb_img/'
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'topdown_heatmap/coco-wholebody/'
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'vipnas_mbv3_coco_wholebody_256x192_dark.py',
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model_checkpoint='https://download.openmmlab.com/mmpose/top_down/'
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'vipnas/vipnas_mbv3_coco_wholebody_256x192_dark'
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'-e2158108_20211205.pth',
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cls_names=['person'],
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input_buffer='det_result',
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output_buffer='pose_result'),
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# 'ModelResultBindingNode':
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# This node binds the latest model inference result with the current
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# frame. (This means the frame image and inference result may be
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# asynchronous).
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dict(
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type='ModelResultBindingNode',
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name='ResultBinder',
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frame_buffer='_frame_', # `_frame_` is a runner-reserved buffer
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result_buffer='pose_result',
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output_buffer='frame'),
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# 'PoseVisualizerNode':
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# This node draw the pose visualization result in the frame image.
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# Pose results is needed.
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dict(
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type='PoseVisualizerNode',
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name='Visualizer',
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enable_key='v',
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enable=False,
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frame_buffer='frame',
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output_buffer='vis'),
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# 'ValentineMagicNode':
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# This node draw heart in the image.
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# It can launch dynamically expanding heart from the middle of
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# hands if the persons pose a "hand heart" gesture or blow a kiss.
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# Only there are two persons in the image can trigger this effect.
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# Pose results is needed.
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dict(
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type='ValentineMagicNode',
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name='Visualizer',
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enable_key='l',
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frame_buffer='vis',
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output_buffer='vis_heart',
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),
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# 'NoticeBoardNode':
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# This node show a notice board with given content, e.g. help
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# information.
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dict(
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type='NoticeBoardNode',
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name='Helper',
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enable_key='h',
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enable=False,
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frame_buffer='vis_heart',
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output_buffer='vis_notice',
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content_lines=[
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'This is a demo for pose visualization and simple image '
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'effects. Have fun!', '', 'Hot-keys:',
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'"h": Show help information', '"l": LoveHeart Effect',
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'"v": PoseVisualizer', '"m": Show diagnostic information',
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'"q": Exit'
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],
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),
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# 'MonitorNode':
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# This node show diagnostic information in the frame image. It can
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# be used for debugging or monitoring system resource status.
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dict(
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type='MonitorNode',
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name='Monitor',
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enable_key='m',
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enable=False,
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frame_buffer='vis_notice',
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output_buffer='display'), # `_frame_` is a runner-reserved buffer
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# 'RecorderNode':
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# This node record the frames into a local file. It can save the
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# visualiztion results. Uncommit the following lines to turn it on.
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dict(
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type='RecorderNode',
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name='Recorder',
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out_video_file='record.mp4',
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frame_buffer='display',
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output_buffer='_display_')
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])
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