1# Licensed to the Apache Software Foundation (ASF) under one 2# or more contributor license agreements. See the NOTICE file 3# distributed with this work for additional information 4# regarding copyright ownership. The ASF licenses this file 5# to you under the Apache License, Version 2.0 (the 6# "License"); you may not use this file except in compliance 7# with the License. You may obtain a copy of the License at 8# 9# http://www.apache.org/licenses/LICENSE-2.0 10# 11# Unless required by applicable law or agreed to in writing, 12# software distributed under the License is distributed on an 13# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY 14# KIND, either express or implied. See the License for the 15# specific language governing permissions and limitations 16# under the License. 17# pylint: disable=invalid-name, too-many-nested-blocks 18"Roi align in python" 19import math 20import numpy as np 21 22 23def roi_align_nchw_python(a_np, rois_np, pooled_size, spatial_scale, sample_ratio): 24 """Roi align in python""" 25 _, channel, height, width = a_np.shape 26 num_roi = rois_np.shape[0] 27 b_np = np.zeros((num_roi, channel, pooled_size, pooled_size), dtype=a_np.dtype) 28 29 if isinstance(pooled_size, int): 30 pooled_size_h = pooled_size_w = pooled_size 31 else: 32 pooled_size_h, pooled_size_w = pooled_size 33 34 def _bilinear(b, c, y, x): 35 if y < -1 or y > height or x < -1 or x > width: 36 return 0 37 y = max(y, 0.0) 38 x = max(x, 0.0) 39 y_low = int(y) 40 x_low = int(x) 41 42 y_high = min(y_low + 1, height - 1) 43 x_high = min(x_low + 1, width - 1) 44 45 ly = y - y_low 46 lx = x - x_low 47 return ( 48 (1 - ly) * (1 - lx) * a_np[b, c, y_low, x_low] 49 + (1 - ly) * lx * a_np[b, c, y_low, x_high] 50 + ly * (1 - lx) * a_np[b, c, y_high, x_low] 51 + ly * lx * a_np[b, c, y_high, x_high] 52 ) 53 54 for i in range(num_roi): 55 roi = rois_np[i] 56 batch_index = int(roi[0]) 57 roi_start_w, roi_start_h, roi_end_w, roi_end_h = roi[1:] * spatial_scale 58 roi_h = max(roi_end_h - roi_start_h, 1.0) 59 roi_w = max(roi_end_w - roi_start_w, 1.0) 60 61 bin_h = roi_h / pooled_size_h 62 bin_w = roi_w / pooled_size_w 63 64 if sample_ratio > 0: 65 roi_bin_grid_h = roi_bin_grid_w = int(sample_ratio) 66 else: 67 roi_bin_grid_h = int(math.ceil(roi_h / pooled_size)) 68 roi_bin_grid_w = int(math.ceil(roi_w / pooled_size)) 69 70 count = roi_bin_grid_h * roi_bin_grid_w 71 72 for c in range(channel): 73 for ph in range(pooled_size_h): 74 for pw in range(pooled_size_w): 75 total = 0.0 76 for iy in range(roi_bin_grid_h): 77 for ix in range(roi_bin_grid_w): 78 y = roi_start_h + ph * bin_h + (iy + 0.5) * bin_h / roi_bin_grid_h 79 x = roi_start_w + pw * bin_w + (ix + 0.5) * bin_w / roi_bin_grid_w 80 total += _bilinear(batch_index, c, y, x) 81 b_np[i, c, ph, pw] = total / count 82 return b_np 83