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# Google utils: https://cloud.google.com/storage/docs/reference/libraries
import os
import platform
import subprocess
import time
from pathlib import Path
import torch
def gsutil_getsize(url=''):
# gs://bucket/file size https://cloud.google.com/storage/docs/gsutil/commands/du
s = subprocess.check_output('gsutil du %s' % url, shell=True).decode('utf-8')
return eval(s.split(' ')[0]) if len(s) else 0 # bytes
def attempt_download(weights):
# Attempt to download pretrained weights if not found locally
weights = weights.strip().replace("'", '')
file = Path(weights).name
msg = weights + ' missing, try downloading from https://github.com/WongKinYiu/yolor/releases/'
models = ['yolor_p6.pt', 'yolor_w6.pt'] # available models
if file in models and not os.path.isfile(weights):
try: # GitHub
url = 'https://github.com/WongKinYiu/yolor/releases/download/v1.0/' + file
print('Downloading %s to %s...' % (url, weights))
torch.hub.download_url_to_file(url, weights)
assert os.path.exists(weights) and os.path.getsize(weights) > 1E6 # check
except Exception as e: # GCP
print('ERROR: Download failure.')
print('')
def attempt_load(weights, map_location=None):
# Loads an ensemble of models weights=[a,b,c] or a single model weights=[a] or weights=a
model = Ensemble()
for w in weights if isinstance(weights, list) else [weights]:
attempt_download(w)
model.append(torch.load(w, map_location=map_location)['model'].float().fuse().eval()) # load FP32 model
if len(model) == 1:
return model[-1] # return model
else:
print('Ensemble created with %s\n' % weights)
for k in ['names', 'stride']:
setattr(model, k, getattr(model[-1], k))
return model # return ensemble
def gdrive_download(id='1n_oKgR81BJtqk75b00eAjdv03qVCQn2f', name='coco128.zip'):
# Downloads a file from Google Drive. from utils.google_utils import *; gdrive_download()
t = time.time()
print('Downloading https://drive.google.com/uc?export=download&id=%s as %s... ' % (id, name), end='')
os.remove(name) if os.path.exists(name) else None # remove existing
os.remove('cookie') if os.path.exists('cookie') else None
# Attempt file download
out = "NUL" if platform.system() == "Windows" else "/dev/null"
os.system('curl -c ./cookie -s -L "drive.google.com/uc?export=download&id=%s" > %s ' % (id, out))
if os.path.exists('cookie'): # large file
s = 'curl -Lb ./cookie "drive.google.com/uc?export=download&confirm=%s&id=%s" -o %s' % (get_token(), id, name)
else: # small file
s = 'curl -s -L -o %s "drive.google.com/uc?export=download&id=%s"' % (name, id)
r = os.system(s) # execute, capture return
os.remove('cookie') if os.path.exists('cookie') else None
# Error check
if r != 0:
os.remove(name) if os.path.exists(name) else None # remove partial
print('Download error ') # raise Exception('Download error')
return r
# Unzip if archive
if name.endswith('.zip'):
print('unzipping... ', end='')
os.system('unzip -q %s' % name) # unzip
os.remove(name) # remove zip to free space
print('Done (%.1fs)' % (time.time() - t))
return r
def get_token(cookie="./cookie"):
with open(cookie) as f:
for line in f:
if "download" in line:
return line.split()[-1]
return ""
# def upload_blob(bucket_name, source_file_name, destination_blob_name):
# # Uploads a file to a bucket
# # https://cloud.google.com/storage/docs/uploading-objects#storage-upload-object-python
#
# storage_client = storage.Client()
# bucket = storage_client.get_bucket(bucket_name)
# blob = bucket.blob(destination_blob_name)
#
# blob.upload_from_filename(source_file_name)
#
# print('File {} uploaded to {}.'.format(
# source_file_name,
# destination_blob_name))
#
#
# def download_blob(bucket_name, source_blob_name, destination_file_name):
# # Uploads a blob from a bucket
# storage_client = storage.Client()
# bucket = storage_client.get_bucket(bucket_name)
# blob = bucket.blob(source_blob_name)
#
# blob.download_to_filename(destination_file_name)
#
# print('Blob {} downloaded to {}.'.format(
# source_blob_name,
# destination_file_name))
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