wehub-resource-sync
69 lines
2.8 KiB
Python
69 lines
2.8 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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# pylint: disable=invalid-name, too-many-nested-blocks
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"Roi pool in python"
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import math
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import numpy as np
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def roi_pool_nchw_python(a_np, rois_np, pooled_size, spatial_scale):
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"""Roi pool in python"""
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_, channel, height, width = a_np.shape
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num_roi = rois_np.shape[0]
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b_np = np.zeros((num_roi, channel, pooled_size, pooled_size), dtype=a_np.dtype)
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if isinstance(pooled_size, int):
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pooled_size_h = pooled_size_w = pooled_size
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else:
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pooled_size_h, pooled_size_w = pooled_size
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for i in range(num_roi):
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roi = rois_np[i]
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batch_index = int(roi[0])
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# Use ties-away-from-zero rounding to match ONNX runtime (std::round semantics).
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# Python's built-in round() uses ties-to-even, so use floor(x + 0.5) explicitly.
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roi_start_w = math.floor(roi[1] * spatial_scale + 0.5)
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roi_start_h = math.floor(roi[2] * spatial_scale + 0.5)
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roi_end_w = math.floor(roi[3] * spatial_scale + 0.5)
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roi_end_h = math.floor(roi[4] * spatial_scale + 0.5)
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roi_h = max(roi_end_h - roi_start_h + 1, 1)
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roi_w = max(roi_end_w - roi_start_w + 1, 1)
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bin_h = float(roi_h) / pooled_size_h
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bin_w = float(roi_w) / pooled_size_w
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for ph in range(pooled_size_h):
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for pw in range(pooled_size_w):
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hstart = math.floor(ph * bin_h)
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wstart = math.floor(pw * bin_w)
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hend = math.ceil((ph + 1) * bin_h)
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wend = math.ceil((pw + 1) * bin_w)
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hstart = min(max(hstart + roi_start_h, 0), height)
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hend = min(max(hend + roi_start_h, 0), height)
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wstart = min(max(wstart + roi_start_w, 0), width)
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wend = min(max(wend + roi_start_w, 0), width)
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is_empty = (hend <= hstart) or (wend <= wstart)
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for c in range(channel):
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if is_empty:
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b_np[i, c, ph, pw] = 0.0
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else:
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b_np[i, c, ph, pw] = np.max(a_np[batch_index, c, hstart:hend, wstart:wend])
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return b_np
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