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61 lines
2.1 KiB
61 lines
2.1 KiB
# 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 os.path as osp |
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import cv2 |
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import numpy as np |
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import paddle |
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from paddle.utils.download import get_path_from_url |
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from .fcn import FCN |
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from .hrnet import HRNet_W18 |
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BISENET_WEIGHT_URL = 'https://paddlegan.bj.bcebos.com/models/faceseg_FCN-HRNetW18.pdparams' |
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class FaceSeg: |
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def __init__(self): |
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save_pth = get_path_from_url(BISENET_WEIGHT_URL, |
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osp.split(osp.realpath(__file__))[0]) |
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self.net = FCN(num_classes=2, backbone=HRNet_W18()) |
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state_dict = paddle.load(save_pth) |
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self.net.set_state_dict(state_dict) |
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self.net.eval() |
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def __call__(self, image): |
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image_input = self.input_transform(image) # RGB image |
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with paddle.no_grad(): |
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logits = self.net(image_input) |
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pred = paddle.argmax(logits[0], axis=1) |
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pred = pred.numpy() |
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mask = np.squeeze(pred).astype(np.uint8) |
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mask = self.output_transform(mask, shape=image.shape[:2]) |
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return mask |
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def input_transform(self, image): |
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image_input = cv2.resize( |
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image, (384, 384), interpolation=cv2.INTER_AREA) |
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image_input = (image_input / 255.)[np.newaxis, :, :, :] |
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image_input = np.transpose(image_input, (0, 3, 1, 2)).astype(np.float32) |
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image_input = paddle.to_tensor(image_input) |
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return image_input |
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@staticmethod |
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def output_transform(output, shape): |
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output = cv2.resize(output, (shape[1], shape[0])) |
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image_output = np.clip((output * 255), 0, 255).astype(np.uint8) |
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return image_output
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