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November 27, 2017 08:43
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Preparing data for training on FloydHub by downloading from Google Drive
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import logging | |
import os | |
import requests | |
from common import utils | |
CHUNK_SIZE = 32768 | |
def download_file_from_google_drive(id, destination): | |
URL = "https://docs.google.com/uc?export=download" | |
session = requests.Session() | |
response = session.get(URL, params={'id': id}, stream=True) | |
token = get_confirm_token(response) | |
if token: | |
params = {'id': id, 'confirm': token} | |
response = session.get(URL, params=params, stream=True) | |
save_response_content(response, destination) | |
def get_confirm_token(response): | |
for key, value in response.cookies.items(): | |
if key.startswith('download_warning'): | |
return value | |
return None | |
def save_response_content(response, destination): | |
with open(destination, "wb") as f: | |
for chunk in response.iter_content(CHUNK_SIZE): | |
if chunk: # filter out keep-alive new chunks | |
f.write(chunk) | |
def download_files_from_google_drive(file_id, output_path): | |
logging.info('Downloading data from Google Drive') | |
output_path_dir = os.path.dirname(os.path.abspath(output_path)) | |
utils.makedirs(output_path_dir) | |
logging.debug('Downloading data [%s] to [%s]' % (file_id, output_path)) | |
download_file_from_google_drive(file_id, output_path) |
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import logging | |
import sys | |
from common.data import download_from_drive | |
from common.data import unpack | |
def main(args): | |
prefix = "" | |
FORMAT = "%(asctime)s - %(levelname)s - %(message)s" | |
logging.basicConfig(format=FORMAT, level=logging.DEBUG) | |
logging.info('Preparing Redux data') | |
file_id = "0B7lvbTNg1cHtOWtyQU9LbU1yaE0" | |
output_dir = prefix + "/output/train_data.tar.gz" | |
download_from_drive.download_files_from_google_drive(file_id, output_dir) | |
file_id = "0B7lvbTNg1cHtWUdXcG9US0dhclk" | |
output_dir = prefix + "/output/tf_vgg16.tar.gz" | |
download_from_drive.download_files_from_google_drive(file_id, output_dir) | |
archive_path = prefix + "/output/train_data.tar.gz" | |
output_dir = prefix + "/output" | |
unpack.unpack_data(archive_path, output_dir, True) | |
archive_path = prefix + "/output/tf_vgg16.tar.gz" | |
output_dir = prefix + "/output" | |
unpack.unpack_data(archive_path, output_dir, True) | |
logging.info('Prepared data') | |
if __name__ == '__main__': | |
main(sys.argv[1:]) |
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#!/bin/bash | |
SCRIPT_DIR=$(cd $(dirname "$0"); pwd -P) | |
export PYTHONPATH=${SCRIPT_DIR} | |
python py_redux/prepare/prepare_train_full_fh.py |
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#!/bin/bash | |
SCRIPT_DIR=$(cd $(dirname "$0"); pwd -P) | |
export PYTHONPATH=${SCRIPT_DIR} | |
floyd run --env tensorflow-1.2 "bash prepare_train_full_fh.sh" |
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import logging | |
import os | |
import tarfile | |
import zipfile | |
from common import utils | |
def unpack_data(archive_path, output_dir, remove_archive): | |
utils.makedirs(output_dir) | |
logging.info('Unpacking [%s] to [%s]' % (archive_path, output_dir)) | |
if archive_path.endswith("zip"): | |
with zipfile.ZipFile(archive_path, "r") as zip_ref: | |
zip_ref.extractall(output_dir) | |
elif archive_path.endswith("tar.gz") or archive_path.endswith("tar") or archive_path.endswith("tgz"): | |
tar = tarfile.open(archive_path) | |
tar.extractall(output_dir) | |
tar.close() | |
else: | |
raise Exception('Unknown archive type') | |
if remove_archive: | |
logging.info('Removing archive [%s]' % archive_path) | |
os.remove(archive_path) |
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