def encode_entry(self, entry):
"""
Return numpy.ndarray
"""
feature_image_file = entry[0]
label_image_file = entry[1]
feature_image = self.encode_PIL_Image(
image.load_image(feature_image_file))
label_image = self.encode_PIL_Image(image.load_image(label_image_file))
return feature_image, label_image
def encode_entry(self, entry):
"""
Return numpy.ndarray
"""
feature_image_file = entry[0]
label_image_file = entry[1]
feature_image = self.encode_PIL_Image(
image.load_image(feature_image_file))
label_image = self.encode_PIL_Image(
image.load_image(label_image_file))
return feature_image, label_image
def encode_entry(self, entry):
"""
Return numpy.ndarray
"""
feature_image_file = entry[0]
label_image_file = entry[1]
# feature image
feature_image = self.encode_PIL_Image(
image.load_image(feature_image_file), self.channel_conversion)
# label image
label_image = self.load_label(label_image_file)
if label_image.getpalette() != self.userdata[COLOR_PALETTE_ATTRIBUTE]:
raise ValueError("All label images must use the same palette")
label_image = self.encode_PIL_Image(label_image)
return feature_image, label_image
def encode_entry(self, entry):
"""
Return numpy.ndarray
"""
feature_image_file = entry[0]
label_image_file = entry[1]
# feature image
feature_image = self.encode_PIL_Image(
image.load_image(feature_image_file),
self.channel_conversion)
# label image
label_image = self.load_label(label_image_file)
if label_image.getpalette() != self.userdata[COLOR_PALETTE_ATTRIBUTE]:
raise ValueError("All label images must use the same palette")
label_image = self.encode_PIL_Image(label_image)
return feature_image, label_image
def scale_image(self, filename):
im = np.array(image.load_image(filename))
# center crop
if self.userdata['center_crop_size']:
crop_size = int(self.userdata['center_crop_size'])
width, height = im.shape[0:2]
i = (width // 2) - crop_size // 2
j = (height // 2) - crop_size // 2
im = im[i:i + crop_size, j:j + crop_size, :]
# resize
if self.userdata['resize']:
resize = int(self.userdata['resize'])
im = image.resize_image(im, resize, resize, resize_mode='squash')
# transpose to CHW
feature = im.transpose(2, 0, 1)
return feature
def scale_image(self, filename):
im = np.array(image.load_image(filename))
# center crop
if self.userdata['center_crop_size']:
crop_size = int(self.userdata['center_crop_size'])
width, height = im.shape[0:2]
i = (width // 2) - crop_size // 2
j = (height // 2) - crop_size // 2
im = im[i:i + crop_size, j:j + crop_size, :]
# resize
if self.userdata['resize']:
resize = int(self.userdata['resize'])
im = image.resize_image(im, resize, resize, resize_mode='squash')
# transpose to CHW
feature = im.transpose(2, 0, 1)
return feature
