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Code Issues Projects Releases Wiki Activity

Fix list paths (#721) 

* Add list paths on check_dataset

* missing raise statement

* Update general.py

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
pull/727/head
Hatovix 2020-08-13 03:53:38 +02:00 committed by GitHub
parent 0892c44bc4
commit 56c2c344ff
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1 changed files with 22 additions and 18 deletions
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40
utils/general.py
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@ -9,7 +9,7 @@ import logging
from contextlib import contextmanager
from copy import copy
from pathlib import Path
from sys import platform
import platform
import cv2
import matplotlib
@ -66,7 +66,7 @@ def get_latest_run(search_dir='./runs'):
def check_git_status():
# Suggest 'git pull' if repo is out of date
if platform in ['linux', 'darwin'] and not os.path.isfile('/.dockerenv'):
if platform.system() in ['Linux', 'Darwin'] and not os.path.isfile('/.dockerenv'):
s = subprocess.check_output('if [ -d .git ]; then git fetch && git status -uno; fi', shell=True).decode('utf-8')
if 'Your branch is behind' in s:
print(s[s.find('Your branch is behind'):s.find('\n\n')] + '\n')
@ -126,7 +126,7 @@ def check_anchor_order(m):
def check_file(file):
# Searches for file if not found locally
# Search for file if not found
if os.path.isfile(file) or file == '':
return file
else:
@ -137,21 +137,25 @@ def check_file(file):
def check_dataset(dict):
# Download dataset if not found
train, val = os.path.abspath(dict['train']), os.path.abspath(dict['val']) # data paths
if not (os.path.exists(train) and os.path.exists(val)):
print('\nWARNING: Dataset not found, nonexistant paths: %s' % [train, val])
if 'download' in dict:
s = dict['download']
print('Attempting autodownload from: %s' % s)
if s.startswith('http') and s.endswith('.zip'): # URL
f = Path(s).name # filename
torch.hub.download_url_to_file(s, f)
r = os.system('unzip -q %s -d ../ && rm %s' % (f, f))
else: # bash script
r = os.system(s)
print('Dataset autodownload %s\n' % ('success' if r == 0 else 'failure')) # analyze return value
else:
Exception('Dataset autodownload unavailable.')
val, s = dict.get('val'), dict.get('download')
if val and len(val):
val = [os.path.abspath(x) for x in (val if isinstance(val, list) else [val])] # val path
if not all(os.path.exists(x) for x in val):
print('\nWARNING: Dataset not found, nonexistant paths: %s' % [*val])
if s and len(s): # download script
print('Attempting autodownload from: %s' % s)
if s.startswith('http') and s.endswith('.zip'): # URL
f = Path(s).name # filename
if platform.system() == 'Darwin': # avoid MacOS python requests certificate error
os.system('curl -L %s -o %s' % (s, f))
else:
torch.hub.download_url_to_file(s, f)
r = os.system('unzip -q %s -d ../ && rm %s' % (f, f)) # unzip
else: # bash script
r = os.system(s)
print('Dataset autodownload %s\n' % ('success' if r == 0 else 'failure')) # analyze return value
else:
raise Exception('Dataset not found.')
def make_divisible(x, divisor):