96 lines
3.6 KiB
Python
96 lines
3.6 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 os
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import sys
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import tarfile
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import requests
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from tqdm import tqdm
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from ppocr.utils.logging import get_logger
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MODELS_DIR = os.path.expanduser("~/.paddleocr/models/")
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def download_with_progressbar(url, save_path):
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logger = get_logger()
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if save_path and os.path.exists(save_path):
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logger.info(f"Path {save_path} already exists. Skipping...")
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return
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response = requests.get(url, stream=True)
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if response.status_code == 200:
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total_size_in_bytes = int(response.headers.get("content-length", 1))
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block_size = 1024 # 1 Kibibyte
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progress_bar = tqdm(total=total_size_in_bytes, unit="iB", unit_scale=True)
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with open(save_path, "wb") as file:
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for data in response.iter_content(block_size):
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progress_bar.update(len(data))
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file.write(data)
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progress_bar.close()
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else:
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logger.error("Something went wrong while downloading models")
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sys.exit(0)
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def maybe_download(model_storage_directory, url):
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# using custom model
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tar_file_name_list = [".pdiparams", ".pdiparams.info", ".pdmodel"]
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if not os.path.exists(
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os.path.join(model_storage_directory, "inference.pdiparams")
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) or not os.path.exists(os.path.join(model_storage_directory, "inference.pdmodel")):
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assert url.endswith(".tar"), "Only supports tar compressed package"
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tmp_path = os.path.join(model_storage_directory, url.split("/")[-1])
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print("download {} to {}".format(url, tmp_path))
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os.makedirs(model_storage_directory, exist_ok=True)
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download_with_progressbar(url, tmp_path)
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with tarfile.open(tmp_path, "r") as tarObj:
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for member in tarObj.getmembers():
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filename = None
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for tar_file_name in tar_file_name_list:
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if member.name.endswith(tar_file_name):
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filename = "inference" + tar_file_name
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if filename is None:
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continue
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file = tarObj.extractfile(member)
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with open(os.path.join(model_storage_directory, filename), "wb") as f:
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f.write(file.read())
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os.remove(tmp_path)
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def maybe_download_params(model_path):
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if os.path.exists(model_path) or not is_link(model_path):
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return model_path
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else:
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url = model_path
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tmp_path = os.path.join(MODELS_DIR, url.split("/")[-1])
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print("download {} to {}".format(url, tmp_path))
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os.makedirs(MODELS_DIR, exist_ok=True)
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download_with_progressbar(url, tmp_path)
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return tmp_path
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def is_link(s):
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return s is not None and s.startswith("http")
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def confirm_model_dir_url(model_dir, default_model_dir, default_url):
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url = default_url
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if model_dir is None or is_link(model_dir):
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if is_link(model_dir):
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url = model_dir
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file_name = url.split("/")[-1][:-4]
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model_dir = default_model_dir
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model_dir = os.path.join(model_dir, file_name)
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return model_dir, url
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