def process_folder(self, folder):
"""
Process folder
Returns: (positive, negative)
Tuple with two lists: positive and negative file names
"""
return self.process_file_list(FileHelper.read_images_in_dir(folder))
def tag_folder(self, folder, output):
print folder
if folder[-1] == '\\':
folder = folder[:-1]
self.currentFolder = folder
self.uplevelFolder = os.path.split(folder)[-1]
try:
self.currentTag = getTagCoordinates(self.uplevelFolder, YX=False)
except ValueError:
pass
self.negativePath = os.path.join(output, 'negative')
self.goodPath = os.path.join(output, 'good')
self.badPath = os.path.join(output, 'bad')
self.awfulPath = os.path.join(output, 'awful')
self.twitterPath = os.path.join(output, 'twitter')
self.facebookPath = os.path.join(output, 'facebook')
self.atPath = os.path.join(output, 'at')
self.filelist = sorted(FileHelper.read_images_in_dir(folder, includeDir=True))
if not self.show_next():
shutil.rmtree(folder)
return True
while True:
action = self.wait_for_action()
if action == 'break':
return False
elif action == 'next':
if not self.show_next():
shutil.rmtree(folder)
return True
def __load_prepare_templates(self):
"""Load templates. Template MUST be white on black background"""
templates = []
filelist = sorted(FileHelper.read_images_in_dir(self.templates_dir))
for filename in filelist:
templ = self.__load_template(os.path.join(self.templates_dir, filename))
if templ is not None:
templates.append(templ)
return templates
def __getFeaturesFromTemplates(self):
features = {}
images = FileHelper.read_images_in_dir(self.templates_dir)
for filename in images:
im = cv2.imread(os.path.join(self.templates_dir, filename), cv2.IMREAD_GRAYSCALE)
kp, desc = self.detector.detectAndCompute(im, None)
logging.debug('{0} - {1} features'.format(filename, len(kp)))
# features.append((kp, desc))
features[filename] = (kp, desc)
return features
def binarize_folder_threshold(inFolder, outFolder):
fileList = FileHelper.read_images_in_dir(inFolder)
FileHelper.create_or_clear_dir(outFolder)
for filename in fileList:
image = load_image_thresholding(os.path.join(inFolder, filename), 190)
cv2.imwrite(os.path.join(outFolder, filename), image)
def process_folder(folder, rules=default_sample):
files = FileHelper.read_images_in_dir(folder)
return get_ruled_files(files, rules)
def process_folder(classifier, inputFolder, countPositive, positiveOutputFolder=None, negativeOutputFolder=None, jobs=-1):
filelist = [os.path.join(inputFolder, fn) for fn in FileHelper.read_images_in_dir(inputFolder)]
return process_file_list(classifier, filelist, countPositive, positiveOutputFolder, negativeOutputFolder, jobs)
base_template = drawContours(base_template, template_contours)
cv2.imwrite('/home/valeriy/projects/hashtag/logos/bw/twitter_big_template_contours.png', base_template)
if len(template_contours) > 1:
print 'Warning: too complex template'
template_contours = template_contours[0]
# print len(template_contours)
print '%0.3f %3d %0.2f %0.2f ' % (0.0, len(template_contours), contourSolidity(template_contours), contourExtent(template_contours))
# template_contours = approxContour(template_contours)
inFolder = '/home/valeriy/projects/hashtag/logos/twitter_frames/'
outFolder = '/home/valeriy/projects/hashtag/logos/bin_twitter_frames/'
FileHelper.create_or_clear_dir(outFolder)
for filename in sorted(FileHelper.read_images_in_dir(inFolder))[:3]:
print filename
basefile = os.path.join(inFolder, filename)
basefile_without_ext = os.path.join(outFolder, os.path.splitext(filename)[0])
# image = binarization.load_image_adaptive(basefile, 11, 10, inverse=False)
image = binarization.load_image_thresholding(basefile, 180)
# image = binarization.load_image_thresholding(basefile, 200, binary_type=cv2.THRESH_BINARY_INV)
contour_image = image.copy()
contours, hierarchy = cv2.findContours(contour_image, cv2.RETR_TREE, findContourMethod)
image_drawed = drawContours(image, contours)
# cv2.imwrite(basefile_without_ext + '_bin_thresh_100.jpg', image_drawed)
# cv2.imwrite(basefile_without_ext + '_contour.jpg', contour_image)
# contours = approxAllContours(contours)
image = contour_match(template_contours, contours, image)
