def execute(self, arff_data, attributes, X):
base_width = np.array(arff_data['data'][:, attributes.index('baseWidth')], dtype='float64')
target_width = np.array(arff_data['data'][:, attributes.index('targetWidth')], dtype='float64')
base_height = np.array(arff_data['data'][:, attributes.index('baseHeight')], dtype='float64')
target_height = np.array(arff_data['data'][:, attributes.index('targetHeight')], dtype='float64')
base_viewport = np.array(arff_data['data'][:, attributes.index('baseViewportWidth')], dtype='float64')
target_viewport = np.array(arff_data['data'][:, attributes.index('targetViewportWidth')], dtype='float64')
X.append(np.abs((base_width - target_width)/np.maximum(np.abs(base_viewport - target_viewport), 1)))
X.append(np.abs((base_height - target_height)/np.maximum(np.maximum(base_height, target_height), 1)))
arff_data['features'] = arff_data['features'] + ['width_comp', 'height_comp']
return X
def execute(self, arff_data, attributes, X):
base_width = np.array(arff_data['data'][:, attributes.index('baseWidth')], dtype='float64')
target_width = np.array(arff_data['data'][:, attributes.index('targetWidth')], dtype='float64')
base_viewport = np.array(arff_data['data'][:, attributes.index('baseViewportWidth')], dtype='float64')
target_viewport = np.array(arff_data['data'][:, attributes.index('targetViewportWidth')], dtype='float64')
base_left = np.array(arff_data['data'][:, attributes.index('baseX')], dtype='float64')
base_right = np.array(base_viewport - (base_left + base_width), dtype='float64')
target_left = np.array(arff_data['data'][:, attributes.index('targetX')], dtype='float64')
target_right = np.array(target_viewport - (target_left + target_width), dtype='float64')
X.append(np.abs((base_left - target_left) / np.maximum(np.abs(base_viewport - target_viewport), 1)))
X.append(np.abs((base_right - target_right) / np.maximum(np.abs(base_viewport - target_viewport), 1)))
base_y = np.array(arff_data['data'][:, attributes.index('baseY')], dtype='float64')
target_y = np.array(arff_data['data'][:, attributes.index('targetY')], dtype='float64')
X.append(np.abs((base_y - target_y) / np.maximum(np.abs(base_viewport - target_viewport), 1)))
arff_data['features'] = arff_data['features'] + ['left_comp', 'right_comp', 'y_comp']
return X
def execute(self, arff_data, attributes, X):
X.append(arff_data['data'][:, attributes.index('childsNumber')])
X.append(arff_data['data'][:, attributes.index('textLength')])
base_width = np.array(arff_data['data'][:, attributes.index('baseWidth')], dtype='float64')
target_width = np.array(arff_data['data'][:, attributes.index('targetWidth')], dtype='float64')
base_height = np.array(arff_data['data'][:, attributes.index('baseHeight')], dtype='float64')
target_height = np.array(arff_data['data'][:, attributes.index('targetHeight')], dtype='float64')
X.append(np.maximum(base_width * base_height, target_width * target_height))
arff_data['features'] = arff_data['features'] + ['childsNumber', 'textLength', 'area']
return X
def execute(self, arff_data, attributes, X):
X.append(arff_data['data'][:, attributes.index('phash')])
X.append(arff_data['data'][:, attributes.index('chiSquared')])
image_diff = np.array(arff_data['data'][:, attributes.index('imageDiff')], dtype='float64')
base_width = np.array(arff_data['data'][:, attributes.index('baseWidth')], dtype='float64')
target_width = np.array(arff_data['data'][:, attributes.index('targetWidth')], dtype='float64')
base_height = np.array(arff_data['data'][:, attributes.index('baseHeight')], dtype='float64')
target_height = np.array(arff_data['data'][:, attributes.index('targetHeight')], dtype='float64')
min_area = np.minimum(base_width * base_height, target_width * target_height)
X.append(image_diff / (np.maximum(min_area, 1) * 255))
arff_data['features'] = arff_data['features'] + ['phash', 'chiSquared', 'imageDiff']
return X
def pack_raw(raw):
# pack Bayer image to 4 channels
im = raw.raw_image_visible.astype(np.float32)
im = np.maximum(im - 512, 0) / (16383 - 512) # subtract the black level
im = np.expand_dims(im, axis=2)
img_shape = im.shape
H = img_shape[0]
W = img_shape[1]
out = np.concatenate((im[0:H:2, 0:W:2, :], im[0:H:2, 1:W:2, :],
im[1:H:2, 1:W:2, :], im[1:H:2, 0:W:2, :]),
axis=2)
return out
def execute(self, arff_data):
attributes = [attribute[0] for attribute in arff_data['attributes']]
dataset = arff_data['data']
X = (arff_data['X'].T.tolist() if 'X' in arff_data else [])
base_height = np.array(dataset[:, attributes.index('baseHeight')],
dtype='float64')
target_height = np.array(dataset[:,
attributes.index('targetHeight')],
dtype='float64')
base_width = np.array(dataset[:, attributes.index('baseWidth')],
dtype='float64')
target_width = np.array(dataset[:, attributes.index('targetWidth')],
dtype='float64')
X.append(
np.minimum(base_height * base_width, target_height * target_width))
base_x = np.array(dataset[:, attributes.index('baseX')],
dtype='float64')
target_x = np.array(dataset[:, attributes.index('targetX')],
dtype='float64')
base_y = np.array(dataset[:, attributes.index('baseY')],
dtype='float64')
target_y = np.array(dataset[:, attributes.index('targetY')],
dtype='float64')
X.append(
np.sqrt(
np.power(np.abs(base_x - target_x), 2) +
np.power(np.abs(base_y - target_y), 2)))
X.append(
np.abs((base_height * base_width) -
(target_height * target_width)) / np.maximum(
np.minimum(base_height * base_width, target_height *
target_width), np.ones(len(base_height))))
X.append(dataset[:, attributes.index('chiSquared')])
arff_data['X'] = np.array(X, dtype='float64').T
prev_features = (arff_data['features']
if 'features' in arff_data else [])
arff_data['features'] = prev_features + [
'area', 'displacement', 'sdr', 'chisquared'
]
arff_data['y'] = np.array(
arff_data['data'][:, attributes.index(self._class_attr)],
dtype='int16')
return arff_data