PaddleOCR/ppocr/utils/utility.py

105 lines
3.5 KiB
Python
Executable File

# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import logging
import os
import imghdr
import cv2
from paddle import fluid
def initial_logger():
FORMAT = '%(asctime)s-%(levelname)s: %(message)s'
logging.basicConfig(level=logging.INFO, format=FORMAT)
logger = logging.getLogger(__name__)
return logger
import importlib
def create_module(module_str):
tmpss = module_str.split(",")
assert len(tmpss) == 2, "Error formate\
of the module path: {}".format(module_str)
module_name, function_name = tmpss[0], tmpss[1]
somemodule = importlib.import_module(module_name, __package__)
function = getattr(somemodule, function_name)
return function
def get_check_global_params(mode):
check_params = ['use_gpu', 'max_text_length', 'image_shape',\
'image_shape', 'character_type', 'loss_type']
if mode == "train_eval":
check_params = check_params + [\
'train_batch_size_per_card', 'test_batch_size_per_card']
elif mode == "test":
check_params = check_params + ['test_batch_size_per_card']
return check_params
def get_check_reader_params(mode):
check_params = []
if mode == "train_eval":
check_params = ['TrainReader', 'EvalReader']
elif mode == "test":
check_params = ['TestReader']
return check_params
def get_image_file_list(img_file):
imgs_lists = []
if img_file is None or not os.path.exists(img_file):
raise Exception("not found any img file in {}".format(img_file))
img_end = {'jpg', 'bmp', 'png', 'jpeg', 'rgb', 'tif', 'tiff', 'gif', 'GIF'}
if os.path.isfile(img_file) and imghdr.what(img_file) in img_end:
imgs_lists.append(img_file)
elif os.path.isdir(img_file):
for single_file in os.listdir(img_file):
file_path = os.path.join(img_file, single_file)
if imghdr.what(file_path) in img_end:
imgs_lists.append(file_path)
if len(imgs_lists) == 0:
raise Exception("not found any img file in {}".format(img_file))
return imgs_lists
def check_and_read_gif(img_path):
if os.path.basename(img_path)[-3:] in ['gif', 'GIF']:
gif = cv2.VideoCapture(img_path)
ret, frame = gif.read()
if not ret:
logging.info("Cannot read {}. This gif image maybe corrupted.")
return None, False
if len(frame.shape) == 2 or frame.shape[-1] == 1:
frame = cv2.cvtColor(frame, cv2.COLOR_GRAY2RGB)
imgvalue = frame[:, :, ::-1]
return imgvalue, True
return None, False
def create_multi_devices_program(program, loss_var_name):
build_strategy = fluid.BuildStrategy()
build_strategy.memory_optimize = False
build_strategy.enable_inplace = True
exec_strategy = fluid.ExecutionStrategy()
exec_strategy.num_iteration_per_drop_scope = 1
compile_program = fluid.CompiledProgram(program).with_data_parallel(
loss_name=loss_var_name,
build_strategy=build_strategy,
exec_strategy=exec_strategy)
return compile_program