mirror of
https://github.com/RapidAI/RapidOCR.git
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65 lines
2.4 KiB
Python
65 lines
2.4 KiB
Python
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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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
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import cv2
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import imghdr
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def get_image_file_list(img_file):
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imgs_lists = []
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if img_file is None or not os.path.exists(img_file):
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raise ValueError("not found any img file in {}".format(img_file))
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img_end = {'jpg', 'bmp', 'png', 'jpeg', 'rgb', 'tif', 'tiff', 'gif', 'GIF'}
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if os.path.isfile(img_file) and imghdr.what(img_file) in img_end:
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imgs_lists.append(img_file)
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elif os.path.isdir(img_file):
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for single_file in os.listdir(img_file):
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file_path = os.path.join(img_file, single_file)
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if os.path.isfile(file_path) and imghdr.what(file_path) in img_end:
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imgs_lists.append(file_path)
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if len(imgs_lists) == 0:
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raise ValueError("not found any img file in {}".format(img_file))
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return imgs_lists
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def check_and_read_gif(img_path):
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if os.path.basename(img_path)[-3:] in ['gif', 'GIF']:
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gif = cv2.VideoCapture(img_path)
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ret, frame = gif.read()
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if not ret:
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print("Cannot read {}. This gif image maybe corrupted.")
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return None, False
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if len(frame.shape) == 2 or frame.shape[-1] == 1:
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frame = cv2.cvtColor(frame, cv2.COLOR_GRAY2RGB)
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imgvalue = frame[:, :, ::-1]
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return imgvalue, True
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return None, False
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class ClsPostProcess(object):
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""" Convert between text-label and text-index """
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def __init__(self, label_list, **kwargs):
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super(ClsPostProcess, self).__init__()
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self.label_list = label_list
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def __call__(self, preds, label=None, *args, **kwargs):
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pred_idxs = preds.argmax(axis=1)
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decode_out = [(self.label_list[idx], preds[i, idx])
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for i, idx in enumerate(pred_idxs)]
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if label is None:
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return decode_out
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label = [(self.label_list[idx], 1.0) for idx in label]
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return decode_out, label |