def __is_initial_screen__(self, *args, **kwargs):
original = cv2.imread(os.path.join(self.assets, "start_screen.png"))
against = self.get_img_from_screen_shot()
# convert the images to grayscale
original = mask_image([127], [255], cv2.cvtColor(original, cv2.COLOR_BGR2GRAY), True)
against = mask_image([127], [255], cv2.cvtColor(against, cv2.COLOR_BGR2GRAY), True)
(score, diff) = compare_ssim(original, against, full=True)
if score > .9:
return True
return False
def test_initial_pass_through_compare(self):
original = cv2.imread(
os.path.join(self.provider.assets, "start_screen.png"))
against = self.provider.get_img_from_screen_shot()
wrong = cv2.imread(os.path.join(self.provider.assets, "battle.png"))
# convert the images to grayscale
original = mask_image([127], [255],
cv2.cvtColor(original, cv2.COLOR_BGR2GRAY), True)
against = mask_image([127], [255],
cv2.cvtColor(against, cv2.COLOR_BGR2GRAY), True)
wrong = mask_image([127], [255],
cv2.cvtColor(wrong, cv2.COLOR_BGR2GRAY), True)
# initialize the figure
(score, diff) = compare_ssim(original, against, full=True)
diff = (diff * 255).astype("uint8")
self.assertTrue(
score > .90,
'If this is less then .90 the initial compare of the app will fail'
)
(score, nothing) = compare_ssim(original, wrong, full=True)
self.assertTrue(score < .90)
if self.__debug_pictures__:
# threshold the difference image, followed by finding contours to
# obtain the regions of the two input images that differ
thresh = cv2.threshold(diff, 0, 255,
cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0]
# loop over the contours
for c in cnts:
# compute the bounding box of the contour and then draw the
# bounding box on both input images to represent where the two
# images differ
(x, y, w, h) = cv2.boundingRect(c)
cv2.rectangle(original, (x, y), (x + w, y + h), (0, 0, 255), 2)
cv2.rectangle(against, (x, y), (x + w, y + h), (0, 0, 255), 2)
# show the output images
diffs = ("Original",
original), ("Modified",
against), ("Diff", diff), ("Thresh", thresh)
images = ("Original", original), ("Against", against), ("Wrong",
wrong)
self.setup_compare_images(diffs)
self.setup_compare_images(images)
def get_current_page(self, img):
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
area = crop_image(img, **self.predefined.page_area)
area = mask_image([254], [255], area)
height, width = area.shape
current_page = 0
for x in range(4):
box = crop_image(area, (x * width / 4), 0, ((x + 1) * width / 4), height)
if cv2.countNonZero(box) > 0:
current_page = x
break
return current_page + 1
def img_to_string(img, char_set=None, mask_area=None):
if mask_area is not None:
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
lower, upper = mask_area[0], mask_area[1]
img = mask_image(lower, upper, img)
cv2.imwrite("tmp\\ocr.png", img)
command = "bin\\tess\\tesseract.exe --tessdata-dir bin\\tess\\tessdata tmp\\ocr.png tmp\\ocr "
if char_set is not None:
command += "-c tessedit_char_whitelist=" + char_set + " "
command += "-psm 7 "
command += "> nul 2>&1"
CREATE_NO_WINDOW = 0x08000000
subprocess.call(command, shell=True, creationflags=CREATE_NO_WINDOW)
# Get the largest line in txt
with open("tmp\\ocr.txt") as f:
content = f.read().splitlines()
output_line = ""
for line in content:
line = line.strip()
if len(line) > len(output_line):
output_line = line
return output_line
def prep_for_white_circles(self):
lower, upper = ([215, 215, 215], [255, 255, 255])
self.white_query = mask_image(lower,
upper,
self.query,
apply_mask=True)