116 lines
3.2 KiB
Python
116 lines
3.2 KiB
Python
# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# 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, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import numpy as np
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from .warp_mls import WarpMLS
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def tia_distort(src, segment=4):
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img_h, img_w = src.shape[:2]
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cut = img_w // segment
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thresh = cut // 3
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src_pts = list()
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dst_pts = list()
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src_pts.append([0, 0])
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src_pts.append([img_w, 0])
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src_pts.append([img_w, img_h])
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src_pts.append([0, img_h])
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dst_pts.append([np.random.randint(thresh), np.random.randint(thresh)])
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dst_pts.append(
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[img_w - np.random.randint(thresh), np.random.randint(thresh)])
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dst_pts.append(
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[img_w - np.random.randint(thresh), img_h - np.random.randint(thresh)])
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dst_pts.append(
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[np.random.randint(thresh), img_h - np.random.randint(thresh)])
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half_thresh = thresh * 0.5
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for cut_idx in np.arange(1, segment, 1):
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src_pts.append([cut * cut_idx, 0])
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src_pts.append([cut * cut_idx, img_h])
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dst_pts.append([
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cut * cut_idx + np.random.randint(thresh) - half_thresh,
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np.random.randint(thresh) - half_thresh
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])
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dst_pts.append([
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cut * cut_idx + np.random.randint(thresh) - half_thresh,
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img_h + np.random.randint(thresh) - half_thresh
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])
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trans = WarpMLS(src, src_pts, dst_pts, img_w, img_h)
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dst = trans.generate()
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return dst
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def tia_stretch(src, segment=4):
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img_h, img_w = src.shape[:2]
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cut = img_w // segment
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thresh = cut * 4 // 5
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src_pts = list()
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dst_pts = list()
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src_pts.append([0, 0])
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src_pts.append([img_w, 0])
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src_pts.append([img_w, img_h])
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src_pts.append([0, img_h])
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dst_pts.append([0, 0])
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dst_pts.append([img_w, 0])
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dst_pts.append([img_w, img_h])
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dst_pts.append([0, img_h])
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half_thresh = thresh * 0.5
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for cut_idx in np.arange(1, segment, 1):
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move = np.random.randint(thresh) - half_thresh
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src_pts.append([cut * cut_idx, 0])
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src_pts.append([cut * cut_idx, img_h])
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dst_pts.append([cut * cut_idx + move, 0])
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dst_pts.append([cut * cut_idx + move, img_h])
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trans = WarpMLS(src, src_pts, dst_pts, img_w, img_h)
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dst = trans.generate()
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return dst
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def tia_perspective(src):
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img_h, img_w = src.shape[:2]
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thresh = img_h // 2
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src_pts = list()
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dst_pts = list()
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src_pts.append([0, 0])
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src_pts.append([img_w, 0])
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src_pts.append([img_w, img_h])
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src_pts.append([0, img_h])
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dst_pts.append([0, np.random.randint(thresh)])
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dst_pts.append([img_w, np.random.randint(thresh)])
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dst_pts.append([img_w, img_h - np.random.randint(thresh)])
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dst_pts.append([0, img_h - np.random.randint(thresh)])
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trans = WarpMLS(src, src_pts, dst_pts, img_w, img_h)
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dst = trans.generate()
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return dst |