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| _base_ = ( | |
| '../../third_party/mmyolo/configs/deploy/' | |
| 'detection_tensorrt-fp16_static-640x640.py') | |
| onnx_config = dict( | |
| type='onnx', | |
| export_params=True, | |
| keep_initializers_as_inputs=False, | |
| opset_version=11, | |
| save_file='end2end.onnx', | |
| input_names=['input'], | |
| output_names=['dets', 'labels'], | |
| input_shape=(640, 640), | |
| optimize=True) | |
| backend_config = dict( | |
| type='tensorrt', | |
| common_config=dict(fp16_mode=True, max_workspace_size=1 << 34), | |
| model_inputs=[ | |
| dict( | |
| input_shapes=dict( | |
| input=dict( | |
| min_shape=[1, 3, 640, 640], | |
| opt_shape=[1, 3, 640, 640], | |
| max_shape=[1, 3, 640, 640]))) | |
| ]) | |
| use_efficientnms = False # whether to replace TRTBatchedNMS plugin with EfficientNMS plugin # noqa E501 | |
| codebase_config = dict( | |
| type='mmyolo', | |
| task='ObjectDetection', | |
| model_type='end2end', | |
| post_processing=dict( | |
| score_threshold=0.25, | |
| confidence_threshold=0.005, | |
| iou_threshold=0.65, | |
| max_output_boxes_per_class=100, | |
| pre_top_k=1, | |
| keep_top_k=1, | |
| background_label_id=-1), | |
| module=['mmyolo.deploy']) | |