def show_picture(url):
local_folder = os.path.join(get_data_path(), "images")
if not os.path.exists(local_folder):
try:
os.mkdir(local_folder)
except:
pass
local_file = os.path.join(local_folder, "temp.jpg")
# Download picture
urllib_request.urlretrieve(url, local_file)
# Show picture
xbmc.executebuiltin("SlideShow(" + local_folder + ")")
def maybe_download(directory, filename, url):
"""Download filename from url unless it's already in directory.
Args:
directory: path to the directory that will be used.
filename: name of the file to download to (do nothing if it already exists).
url: URL to download from.
Returns:
The path to the downloaded file.
"""
if not tf.gfile.Exists(directory):
tf.logging.info("Creating directory %s" % directory)
os.mkdir(directory)
filepath = os.path.join(directory, filename)
if not tf.gfile.Exists(filepath):
tf.logging.info("Downloading %s to %s" % (url, filepath))
inprogress_filepath = filepath + ".incomplete"
inprogress_filepath, _ = urllib.urlretrieve(
url, inprogress_filepath, reporthook=download_report_hook)
# Print newline to clear the carriage return from the download progress
print()
tf.gfile.Rename(inprogress_filepath, filepath)
statinfo = os.stat(filepath)
tf.logging.info("Succesfully downloaded %s, %s bytes." %
(filename, statinfo.st_size))
else:
tf.logging.info("Not downloading, file already found: %s" % filepath)
return filepath
def maybe_download(directory, filename, url):
"""Download filename from url unless it's already in directory.
Args:
directory: path to the directory that will be used.
filename: name of the file to download to (do nothing if it already exists).
url: URL to download from.
Returns:
The path to the downloaded file.
"""
if not tf.gfile.Exists(directory):
tf.logging.info("Creating directory %s" % directory)
os.mkdir(directory)
filepath = os.path.join(directory, filename)
if not tf.gfile.Exists(filepath):
tf.logging.info("Downloading %s to %s" % (url, filepath))
inprogress_filepath = filepath + ".incomplete"
inprogress_filepath, _ = urllib.urlretrieve(
url, inprogress_filepath, reporthook=download_report_hook)
# Print newline to clear the carriage return from the download progress
print()
tf.gfile.Rename(inprogress_filepath, filepath)
statinfo = os.stat(filepath)
tf.logging.info("Successfully downloaded %s, %s bytes." %
(filename, statinfo.st_size))
else:
tf.logging.info("Not downloading, file already found: %s" % filepath)
return filepath
def maybe_download(directory, filename, uri):
"""Download filename from uri unless it's already in directory.
Copies a remote file to local if that local file does not already exist. If
the local file pre-exists this function call, it does not check that the local
file is a copy of the remote.
Remote filenames can be filepaths, any URI readable by tensorflow.gfile, or a
URL.
Args:
directory: path to the directory that will be used.
filename: name of the file to download to (do nothing if it already exists).
uri: URI to copy (or download) from.
Returns:
The path to the downloaded file.
"""
if not tf.gfile.Exists(directory):
tf.logging.info("Creating directory %s" % directory)
tf.gfile.MakeDirs(directory)
filepath = os.path.join(directory, filename)
if not tf.gfile.Exists(filepath):
tf.logging.info("Downloading %s to %s" % (uri, filepath))
try:
tf.gfile.Copy(uri, filepath)
except tf.errors.UnimplementedError:
if uri.startswith("http"):
inprogress_filepath = filepath + ".incomplete"
inprogress_filepath, _ = urllib.urlretrieve(
uri, inprogress_filepath, reporthook=download_report_hook)
# Print newline to clear the carriage return from the download progress
print()
tf.gfile.Rename(inprogress_filepath, filepath)
else:
raise ValueError("Unrecognized URI: " + filepath)
statinfo = os.stat(filepath)
tf.logging.info("Successfully downloaded %s, %s bytes." %
(filename, statinfo.st_size))
else:
tf.logging.info("Not downloading, file already found: %s" % filepath)
return filepath
def maybe_download(directory, filename, uri):
"""Download filename from uri unless it's already in directory.
Copies a remote file to local if that local file does not already exist. If
the local file pre-exists this function call, it does not check that the local
file is a copy of the remote.
Remote filenames can be filepaths, any URI readable by tensorflow.gfile, or a
URL.
Args:
directory: path to the directory that will be used.
filename: name of the file to download to (do nothing if it already exists).
uri: URI to copy (or download) from.
Returns:
The path to the downloaded file.
"""
if not tf.gfile.Exists(directory):
tf.logging.info("Creating directory %s" % directory)
tf.gfile.MakeDirs(directory)
filepath = os.path.join(directory, filename)
if not tf.gfile.Exists(filepath):
tf.logging.info("Downloading %s to %s" % (uri, filepath))
try:
tf.gfile.Copy(uri, filepath)
except tf.errors.UnimplementedError:
if uri.startswith("http"):
inprogress_filepath = filepath + ".incomplete"
inprogress_filepath, _ = urllib.urlretrieve(
uri, inprogress_filepath, reporthook=download_report_hook)
# Print newline to clear the carriage return from the download progress
print()
tf.gfile.Rename(inprogress_filepath, filepath)
else:
raise ValueError("Unrecognized URI: " + filepath)
statinfo = os.stat(filepath)
tf.logging.info("Successfully downloaded %s, %s bytes." %
(filename, statinfo.st_size))
else:
tf.logging.info("Not downloading, file already found: %s" % filepath)
return filepath
