def get_data_files(dest, source):
retval = []
for dirname, subdirs, files in os.walk(source):
retval.append(
(os.path.join(dest, dirname[len(source)+1:]), glob(os.pathjoin(dirname, '*.*')))
)
return retval
def get_data_files(dest, source):
retval = []
for dirname, subdirs, files in os.walk(source):
retval.append(
(os.path.join(dest, dirname[len(source)+1:]), glob(os.pathjoin(dirname, '*.*')))
)
return retval
def __init__(self):
global logPath, resultPath,proDir
proDir = readConfig.proDir
resultPath = os.path.join(proDir,"result")
#create result file if it doesn't exit
if not os.path.exists(resultPath):
os.mkdir(resultPath)
#defined test result file name by localtime
logPath = os.pathjoin(resultPath,str(datetime.now().strftime("%Y%m%d%H%M%S")))
#create test result file if it doesn't exist
if not os.path.exists(logPath):
os.makdir(logPath)
#defined logger
self.logger = logging.getLogger()
#defined log level
self.logger.setevel(logging.INFO)
#defined handler
handler = logging.FileHandler(os.path.join(logPath,"output.log"))
#defined formatter
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
#defined formatter
handler.setFormatter(formatter)
#add handler
self.logger.addHandler(handler)
def create_training_progress_vis(results_path):
with open(os.path.join(results_path, 'training_progress.txt')) as f:
training_progress_data = list(
zip(*[line.strip().split() for line in f]))
try:
with open(os.pathjoin(results_path, 'training_progress_val.txt')) as f:
validation_progress_data = list(
zip(*[line.strip().split() for line in f]))
except FileNotFoundError:
# this means that no validation data has been created, set to empty
validation_progress_data = []
reset_grad()
g_loss.backward()
g_optimizer.step()
return g_loss, fake_images
# lets create a directory to save the outputs of the generator as we go along to see the process
sample_dir = 'samples'
if not os.path.exists(sample_dir):
os.makedirs(sample_dir)
# now lets save a real image for visual comparison
for images, _ in data_loader:
images = images.reshape(images.size(0), 1, 28, 28)
save_image(denorm(images), os.pathjoin(sample_dir, 'real_images.png'), nrow=10)
break
Image(os.path.join(sample_dir, 'real_image.png'))
sample_vectors = torch.randn(batch_size, latent_size)
def save_fake_images(index):
fake_images = G(sample_vectors)
fake_images = fake_images.reshape(fake_images.size(0), 1, 28, 28)
fake_fname = 'fake_images-{0:0=4d}.png'.format(index)
print('Saving', fake_fname)
save_image(denorm(fake_images), os.path.join(sample_dir, fake_fname), nrow=10)
import os
import shutil
path = '.'
filenames = os.listdir('.')
for filename in filenames:
just_filename, extension = os.path.splitext(filename)
if filename.endswith(".jpg"):
resize_filename = os.path.join(path, filename)
newdir = r'C:\Users\chris\Desktop\OneDrive\GitHub\GitHub\Projects\Python\Computer_vision\Edit_Pix'
print(resize_filename)
i = 1
just_filename = os.path.join(newdir,
"%s%d%s" % (just_filename, i, extension))
print(just_filename)
while os.path.isfile(just_filename):
i += 1
just_filename = os.pathjoin(
newdir, "%s%d%s" % (just_filename, i, extension))
for image in just_filename:
img = cv2.imread(image, 0)
rsize = cv2.resize(img, (100, 100))
cv2.imshow("Hi There", rsize)
cv2.waitKey(500)
cv2.destroyAllWindows()
shutil.copy(os.path.join(path, filename), just_filename)
def execute(years, roll):
#If there already exists a file with the same name.
try:
os.remove(' temp.zip ')
except:
pass
#roll = raw_input()
#Processing the Roll Number
if int(roll[0:2]) == 14:
k = 0
else:
k = (14 - int(roll[0:2])) * 2 - 1
inp = roll[2:4]
ext = ''
if int(roll[4]) == 1:
ext = ''
elif int(roll[4]) == 3:
ext = '1'
inp = inp + ext
#After processing the roll number, retrieving the required Pickle File
#with all the corresponding subject numbers.
with open("./Pickle/" + inp + '.pickle', 'rb') as restoremydata:
a_list = pickle.load(restoremydata)
#Looping over all the subjects
for x in range(len(a_list[k])):
a_list[k][x] = a_list[k][x] + ".pdf"
#make a temporary directory to store the files
dirpath = tempfile.mkdtemp()
pattern = re.compile("\d{4}")
years_lop = []
#as the string is unicode, its difficult to read, hence a if else for
#everything to make the requried array of required years.
if '2011' in years:
years_lop.append('2011')
if '2010' in years:
years_lop.append('2010')
if '2012' in years:
years_lop.append('2012')
if '2013' in years:
years_lop.append('2013')
#looping over the required folders
for key in years_lop:
for lookfor in a_list[k]:
for root, dirs, files in os.walk('./Files/peqp/' + key + '/'):
if lookfor in files:
pat = os.pathjoin(root, lookfor)
shutil.copy(pat, dirpath)
head, tail = os.path.split(pat)
match = re.search(pattern, pat)
rname = pat[match.start():match.end()]
os.rename(dirpath + '/' + tail,
dirpath + "/" + rname + '_' + tail)
#add files to the zipfile
zf = zipfile.ZipFile('temp.zip', mode='a')
for root1, dirs1, files1 in os.walk(dirpath):
for f in files1:
zf.write(os.path.join(root1, f),
os.path.basename(os.path.join(root1, f)))
zf.close()
#close the remporary directory
shutil.rmtree(dirpath)
#Complete the process by returning the required zipfile.
return os.path.abspath('temp.zip')
