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RunningLeonRunningLeon
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Update supported mmseg models (#181)
* fix ocrnet cascade decoder * update mmseg support models * update mmseg configs * support emanet and icnet * set max K of TopK for tensorrt * update supported models for mmseg in docs * add test for emamodule * add configs and update docs * Update docs * update benchmark
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‎configs/mmseg/segmentation_ncnn_static.py‎

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‎configs/mmseg/segmentation_onnxruntime_static-1024x2048.py‎

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_base_ = ['./segmentation_static.py', '../_base_/backends/onnxruntime.py']
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onnx_config = dict(input_shape=[2048, 1024])

configs/mmseg/segmentation_onnxruntime_static.py renamed to configs/mmseg/segmentation_onnxruntime_static-512x512.py

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_base_ = ['./segmentation_static.py', '../_base_/backends/onnxruntime.py']
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onnx_config = dict(input_shape=None)
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onnx_config = dict(input_shape=[512, 512])

‎configs/mmseg/segmentation_openvino_static-512x512.py‎

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_base_ = ['./segmentation_static.py', '../_base_/backends/openvino.py']
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backend_config = dict(
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model_inputs=[dict(opt_shapes=dict(input=[1, 3, 512, 512]))])

‎configs/mmseg/segmentation_tensorrt-fp16_static-1024x1024.py‎

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_base_ = ['./segmentation_static.py', '../_base_/backends/tensorrt-fp16.py']
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onnx_config = dict(input_shape=[1024, 1024])
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backend_config = dict(
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common_config=dict(max_workspace_size=1 << 30),
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model_inputs=[
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dict(
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input_shapes=dict(
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input=dict(
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min_shape=[1, 3, 1024, 1024],
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opt_shape=[1, 3, 1024, 1024],
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max_shape=[1, 3, 1024, 1024])))
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])

‎configs/mmseg/segmentation_tensorrt-fp16_static-512x512.py‎

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_base_ = ['./segmentation_static.py', '../_base_/backends/tensorrt-fp16.py']
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onnx_config = dict(input_shape=[512, 512])
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backend_config = dict(
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common_config=dict(max_workspace_size=1 << 30),
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model_inputs=[
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dict(
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input_shapes=dict(
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input=dict(
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min_shape=[1, 3, 512, 512],
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opt_shape=[1, 3, 512, 512],
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max_shape=[1, 3, 512, 512])))
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])

‎configs/mmseg/segmentation_tensorrt-int8_static-1024x1024.py‎

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_base_ = ['./segmentation_static.py', '../_base_/backends/tensorrt-int8.py']
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onnx_config = dict(input_shape=[1024, 1024])
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backend_config = dict(
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common_config=dict(max_workspace_size=1 << 30),
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model_inputs=[
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dict(
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input_shapes=dict(
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input=dict(
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min_shape=[1, 3, 1024, 1024],
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opt_shape=[1, 3, 1024, 1024],
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max_shape=[1, 3, 1024, 1024])))
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])

‎configs/mmseg/segmentation_tensorrt-int8_static-512x512.py‎

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_base_ = ['./segmentation_static.py', '../_base_/backends/tensorrt-int8.py']
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onnx_config = dict(input_shape=[512, 512])
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backend_config = dict(
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common_config=dict(max_workspace_size=1 << 30),
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model_inputs=[
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dict(
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input_shapes=dict(
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input=dict(
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min_shape=[1, 3, 512, 512],
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opt_shape=[1, 3, 512, 512],
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max_shape=[1, 3, 512, 512])))
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])

‎configs/mmseg/segmentation_tensorrt_static-1024x1024.py‎

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_base_ = ['./segmentation_static.py', '../_base_/backends/tensorrt.py']
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onnx_config = dict(input_shape=[1024, 1024])
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backend_config = dict(
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common_config=dict(max_workspace_size=1 << 30),
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model_inputs=[
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dict(
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input_shapes=dict(
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input=dict(
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min_shape=[1, 3, 1024, 1024],
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opt_shape=[1, 3, 1024, 1024],
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max_shape=[1, 3, 1024, 1024])))
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])

‎configs/mmseg/segmentation_tensorrt_static-512x512.py‎

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_base_ = ['./segmentation_static.py', '../_base_/backends/tensorrt.py']
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onnx_config = dict(input_shape=[512, 512])
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backend_config = dict(
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common_config=dict(max_workspace_size=1 << 30),
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model_inputs=[
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dict(
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input_shapes=dict(
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input=dict(
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min_shape=[1, 3, 512, 512],
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opt_shape=[1, 3, 512, 512],
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max_shape=[1, 3, 512, 512])))
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])

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