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## @package download
# Module caffe2.python.models.download
import argparse
import os
import sys
import signal
import re
import json
from caffe2.proto import caffe2_pb2
# Import urllib
from urllib.error import HTTPError, URLError
import urllib.request as urllib
# 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))
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("^[/0-9a-zA-Z_-]+$", name):
return False
return True
class ModelDownloader:
def __init__(self, model_env_name='CAFFE2_MODELS'):
self.model_env_name = model_env_name
def _model_dir(self, model):
caffe2_home = os.path.expanduser(os.getenv('CAFFE2_HOME', '~/.caffe2'))
models_dir = os.getenv(self.model_env_name, os.path.join(caffe2_home, 'models'))
return os.path.join(models_dir, model)
def _download(self, model):
model_dir = self._model_dir(model)
assert not os.path.exists(model_dir)
os.makedirs(model_dir)
for f in ['predict_net.pb', 'init_net.pb', 'value_info.json']:
url = getURLFromName(model, f)
dest = os.path.join(model_dir, f)
try:
downloadFromURLToFile(url, dest, show_progress=False)
except TypeError:
# show_progress not supported prior to
# Caffe2 78c014e752a374d905ecfb465d44fa16e02a28f1
# (Sep 17, 2017)
downloadFromURLToFile(url, dest)
except Exception:
deleteDirectory(model_dir)
raise
# This version returns an extra debug_str argument that helps to understand
# why our work sometimes fails in sandcastle
def get_c2_model_dbg(self, model_name):
debug_str = "get_c2_model debug:\n"
model_dir = self._model_dir(model_name)
if not os.path.exists(model_dir):
self._download(model_name)
c2_predict_pb = os.path.join(model_dir, 'predict_net.pb')
debug_str += "c2_predict_pb path: " + c2_predict_pb + "\n"
c2_predict_net = caffe2_pb2.NetDef()
with open(c2_predict_pb, 'rb') as f:
len_read = c2_predict_net.ParseFromString(f.read())
debug_str += "c2_predict_pb ParseFromString = " + str(len_read) + "\n"
c2_predict_net.name = model_name
c2_init_pb = os.path.join(model_dir, 'init_net.pb')
debug_str += "c2_init_pb path: " + c2_init_pb + "\n"
c2_init_net = caffe2_pb2.NetDef()
with open(c2_init_pb, 'rb') as f:
len_read = c2_init_net.ParseFromString(f.read())
debug_str += "c2_init_pb ParseFromString = " + str(len_read) + "\n"
c2_init_net.name = model_name + '_init'
with open(os.path.join(model_dir, 'value_info.json')) as f:
value_info = json.load(f)
return c2_init_net, c2_predict_net, value_info, debug_str
def get_c2_model(self, model_name):
init_net, predict_net, value_info, _ = self.get_c2_model_dbg(model_name)
return init_net, predict_net, value_info
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("'{}' is not a valid model name.".format(model))
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