blob: 2177298ecd04519084e6ec74c4e877a3001da8b4 [file] [log] [blame]
# Copyright (c) 2016-present, Facebook, Inc.
#
# 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.
##############################################################################
## @package download
# Module caffe2.python.models.download
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import argparse
import os
import sys
import signal
import re
# Import urllib
try:
import urllib.error as urlliberror
import urllib.request as urllib
HTTPError = urlliberror.HTTPError
URLError = urlliberror.URLError
except ImportError:
import urllib2 as urllib
HTTPError = urllib.HTTPError
URLError = urllib.URLError
# urllib requires more work to deal with a redirect, so not using vanity url
DOWNLOAD_BASE_URL = "https://s3.amazonaws.com/download.caffe2.ai/models/"
DOWNLOAD_COLUMNS = 70
# Don't let urllib hang up on big downloads
def signalHandler(signal, frame):
print("Killing download...")
exit(0)
signal.signal(signal.SIGINT, signalHandler)
def deleteDirectory(top_dir):
for root, dirs, files in os.walk(top_dir, topdown=False):
for name in files:
os.remove(os.path.join(root, name))
for name in dirs:
os.rmdir(os.path.join(root, name))
os.rmdir(top_dir)
def progressBar(percentage):
full = int(DOWNLOAD_COLUMNS * percentage / 100)
bar = full * "#" + (DOWNLOAD_COLUMNS - full) * " "
sys.stdout.write(u"\u001b[1000D[" + bar + "] " + str(percentage) + "%")
sys.stdout.flush()
def downloadFromURLToFile(url, filename, show_progress=True):
try:
print("Downloading from {url}".format(url=url))
response = urllib.urlopen(url)
size = int(response.info().get('Content-Length').strip())
chunk = min(size, 8192)
print("Writing to {filename}".format(filename=filename))
if show_progress:
downloaded_size = 0
progressBar(0)
with open(filename, "wb") as local_file:
while True:
data_chunk = response.read(chunk)
if not data_chunk:
break
local_file.write(data_chunk)
if show_progress:
downloaded_size += len(data_chunk)
progressBar(int(100 * downloaded_size / size))
print("") # New line to fix for progress bar
except HTTPError as e:
raise Exception("Could not download model. [HTTP Error] {code}: {reason}."
.format(code=e.code, reason=e.reason))
except URLError as e:
raise Exception("Could not download model. [URL Error] {reason}."
.format(reason=e.reason))
except Exception as e:
raise e
def getURLFromName(name, filename):
return "{base_url}{name}/{filename}".format(base_url=DOWNLOAD_BASE_URL,
name=name, filename=filename)
def downloadModel(model, args):
# Figure out where to store the model
model_folder = '{folder}'.format(folder=model)
dir_path = os.path.dirname(os.path.realpath(__file__))
if args.install:
model_folder = '{dir_path}/{folder}'.format(dir_path=dir_path,
folder=model)
# Check if that folder is already there
if os.path.exists(model_folder) and not os.path.isdir(model_folder):
if not args.force:
raise Exception("Cannot create folder for storing the model,\
there exists a file of the same name.")
else:
print("Overwriting existing file! ({filename})"
.format(filename=model_folder))
os.remove(model_folder)
if os.path.isdir(model_folder):
if not args.force:
response = ""
query = "Model already exists, continue? [y/N] "
try:
response = raw_input(query)
except NameError:
response = input(query)
if response.upper() == 'N' or not response:
print("Cancelling download...")
exit(0)
print("Overwriting existing folder! ({filename})".format(filename=model_folder))
deleteDirectory(model_folder)
# Now we can safely create the folder and download the model
os.makedirs(model_folder)
for f in ['predict_net.pb', 'init_net.pb']:
try:
downloadFromURLToFile(getURLFromName(model, f),
'{folder}/{f}'.format(folder=model_folder,
f=f))
except Exception as e:
print("Abort: {reason}".format(reason=str(e)))
print("Cleaning up...")
deleteDirectory(model_folder)
exit(0)
if args.install:
os.symlink("{folder}/__sym_init__.py".format(folder=dir_path),
"{folder}/__init__.py".format(folder=model_folder))
def validModelName(name):
invalid_names = ['__init__']
if name in invalid_names:
return False
if not re.match("^[a-zA-Z_]+$", name):
return False
return True
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description='Download or install pretrained models.')
parser.add_argument('model', nargs='+',
help='Model to download/install.')
parser.add_argument('-i', '--install', action='store_true',
help='Install the model.')
parser.add_argument('-f', '--force', action='store_true',
help='Force a download/installation.')
args = parser.parse_args()
for model in args.model:
if validModelName(model):
downloadModel(model, args)
else:
print("'{model}' is not a valid model name.".format(model))