Coverage for image_processing/simplification_manager.py : 39%

import cv2 

import os 

import imutils 

import numpy as np 

from imutils.perspective import four_point_transform 

from hutts_utils.hutts_logger import logger 

DESKTOP = os.path.join(os.path.join(os.path.expanduser('~')), 'Desktop') 

# The minimum contour area must be to be transformed. 

CONTOUR_AREA_THRESHOLD = 150000 

class SimplificationManager: 

""" 

The Simplification manger is used to remove unwanted content in an image thus 

simplifying process like OCR and facial comparisons. 

""" 

def perspectiveTransformation(self, image, use_io): 

""" 

The perspective transformation takes the image passed and applies edge detection and 

a function to detect the contours of a identification document. If contours of an 

identification document is detected the image is converted from a non-perspective view 

to an perspective view. 

Author(s): 

Stephan Nell, Nicolai van Niekerk 

Args: 

image (:obj:'OpenCV image'): Image containing a identification document 

use_io (boolean): Whether or not to write images to disk 

Returns: 

obj:'OpenCV image': Returns as warped image where just the identification document 

is present and the identification document is now in a perspective view. 

Raises: 

TypeError: If a parameter is passed that is not of type Numpy array. 

""" 

if not isinstance(image, np.ndarray): 

raise TypeError( 

'Bad type for arg image - expected image in numpy array. Received type "%s".' % 

type(image).__name__ 

) 

ratio = image.shape[0] / 500.0 

orig = image.copy() 

image = imutils.resize(image, height=500) 

gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) 

gray = cv2.GaussianBlur(gray, (5, 5), 0) 

edged = cv2.Canny(gray, 75, 200) 

49 ↛ 50line 49 didn't jump to line 50, because the condition on line 49 was never true if use_io: 

cv2.imwrite(DESKTOP + "/output/1.png", edged) 

(_, contours, _) = cv2.findContours(edged.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) 

contours = sorted(contours, key=cv2.contourArea, reverse=True)[:5] 

warped = orig 

# Used to prevent false positive detection 

logger.debug('Contour area Threshold: ' + str(cv2.contourArea(contours[0]))) 

56 ↛ 57line 56 didn't jump to line 57, because the condition on line 56 was never true if cv2.contourArea(contours[0]) > CONTOUR_AREA_THRESHOLD: 

for c in contours: 

peri = cv2.arcLength(c, True) 

approx = cv2.approxPolyDP(c, 0.02 * peri, True) 

if len(approx) == 4: 

screen_contours = approx 

break 

cv2.drawContours(image, [screen_contours], -1, (0, 255, 0), 2) 

if use_io: 

cv2.imwrite(DESKTOP + "/output/2.png", image) 

logger.debug('Performing four point simplification') 

warped = four_point_transform(orig, screen_contours.reshape(4, 2) * ratio) 

return warped