105 lines
3.5 KiB
Python
Executable File
105 lines
3.5 KiB
Python
Executable File
# 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 logging
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import os
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import imghdr
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import cv2
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from paddle import fluid
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def initial_logger():
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FORMAT = '%(asctime)s-%(levelname)s: %(message)s'
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logging.basicConfig(level=logging.INFO, format=FORMAT)
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logger = logging.getLogger(__name__)
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return logger
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import importlib
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def create_module(module_str):
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tmpss = module_str.split(",")
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assert len(tmpss) == 2, "Error formate\
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of the module path: {}".format(module_str)
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module_name, function_name = tmpss[0], tmpss[1]
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somemodule = importlib.import_module(module_name, __package__)
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function = getattr(somemodule, function_name)
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return function
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def get_check_global_params(mode):
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check_params = ['use_gpu', 'max_text_length', 'image_shape',\
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'image_shape', 'character_type', 'loss_type']
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if mode == "train_eval":
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check_params = check_params + [\
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'train_batch_size_per_card', 'test_batch_size_per_card']
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elif mode == "test":
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check_params = check_params + ['test_batch_size_per_card']
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return check_params
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def get_check_reader_params(mode):
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check_params = []
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if mode == "train_eval":
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check_params = ['TrainReader', 'EvalReader']
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elif mode == "test":
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check_params = ['TestReader']
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return check_params
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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 Exception("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 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 Exception("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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logging.info("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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def create_multi_devices_program(program, loss_var_name):
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build_strategy = fluid.BuildStrategy()
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build_strategy.memory_optimize = False
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build_strategy.enable_inplace = True
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exec_strategy = fluid.ExecutionStrategy()
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exec_strategy.num_iteration_per_drop_scope = 1
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compile_program = fluid.CompiledProgram(program).with_data_parallel(
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loss_name=loss_var_name,
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build_strategy=build_strategy,
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exec_strategy=exec_strategy)
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return compile_program
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