Spaces:
Running
on
Zero
Running
on
Zero
File size: 3,108 Bytes
a891a57 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 |
"""
This code file mainly comes from https://github.com/dmlc/gluon-cv/blob/master/gluoncv/model_zoo/model_store.py
"""
from __future__ import print_function
__all__ = ['get_model_file']
import os
import zipfile
import glob
from ..utils import download, check_sha1
_model_sha1 = {
name: checksum
for checksum, name in [
('95be21b58e29e9c1237f229dae534bd854009ce0', 'arcface_r100_v1'),
('', 'arcface_mfn_v1'),
('39fd1e087a2a2ed70a154ac01fecaa86c315d01b', 'retinaface_r50_v1'),
('2c9de8116d1f448fd1d4661f90308faae34c990a', 'retinaface_mnet025_v1'),
('0db1d07921d005e6c9a5b38e059452fc5645e5a4', 'retinaface_mnet025_v2'),
('7dd8111652b7aac2490c5dcddeb268e53ac643e6', 'genderage_v1'),
]
}
base_repo_url = 'https://insightface.ai/files/'
_url_format = '{repo_url}models/{file_name}.zip'
def short_hash(name):
if name not in _model_sha1:
raise ValueError(
'Pretrained model for {name} is not available.'.format(name=name))
return _model_sha1[name][:8]
def find_params_file(dir_path):
if not os.path.exists(dir_path):
return None
paths = glob.glob("%s/*.params" % dir_path)
if len(paths) == 0:
return None
paths = sorted(paths)
return paths[-1]
def get_model_file(name, root=os.path.join('~', '.insightface', 'models')):
r"""Return location for the pretrained on local file system.
This function will download from online model zoo when model cannot be found or has mismatch.
The root directory will be created if it doesn't exist.
Parameters
----------
name : str
Name of the model.
root : str, default '~/.mxnet/models'
Location for keeping the model parameters.
Returns
-------
file_path
Path to the requested pretrained model file.
"""
file_name = name
root = os.path.expanduser(root)
dir_path = os.path.join(root, name)
file_path = find_params_file(dir_path)
#file_path = os.path.join(root, file_name + '.params')
sha1_hash = _model_sha1[name]
if file_path is not None:
if check_sha1(file_path, sha1_hash):
return file_path
else:
print(
'Mismatch in the content of model file detected. Downloading again.'
)
else:
print('Model file is not found. Downloading.')
if not os.path.exists(root):
os.makedirs(root)
if not os.path.exists(dir_path):
os.makedirs(dir_path)
zip_file_path = os.path.join(root, file_name + '.zip')
repo_url = base_repo_url
if repo_url[-1] != '/':
repo_url = repo_url + '/'
download(_url_format.format(repo_url=repo_url, file_name=file_name),
path=zip_file_path,
overwrite=True)
with zipfile.ZipFile(zip_file_path) as zf:
zf.extractall(dir_path)
os.remove(zip_file_path)
file_path = find_params_file(dir_path)
if check_sha1(file_path, sha1_hash):
return file_path
else:
raise ValueError(
'Downloaded file has different hash. Please try again.')
|