def coords(this, shot=True):
this = this + '.png'
if shot:
Screenshot.shot()
else:
print('No screenshot')
small_image = cv2.imread(this)
h, w, c = small_image.shape
large_image = cv2.imread('playing.png')
result = cv2.matchTemplate(
small_image, large_image, cv2.TM_SQDIFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
# print('ImageCoordinate::coords => ' + this + ' ' + str(min_val))
mn, _, mn_loc, mx_loc = cv2.minMaxLoc(result)
mp_x, mp_y = mn_loc
# #pyautogui.moveTo(mp_x, mp_y)
# top_left = mn_loc
# mx_right = mx_loc
# bt_rt =(top_left[0]+h,top_left[1]+w)
# cv2.rectangle(large_image,top_left,bt_rt,255,2)
# bt_rt =(mx_right[0]+h,mx_right[1]+w)
# cv2.rectangle(large_image,mx_right,bt_rt,255,2)
# cv2.imwrite('result_'+this.replace('images/',''), large_image)
# print('saved'+str(min_val))
if min_val > 0.2:
return [0, 0, min_val]
mn, _, mn_loc, _ = cv2.minMaxLoc(result)
mp_x, mp_y = mn_loc
ordinal = random.randrange(1, 15)
a = random.randrange(-ordinal, ordinal)
b = random.randrange(-ordinal, ordinal)
location = [mp_x + w / 2+a, mp_y + h / 2+b, min_val]
return location
def count_occurrence(this):
Screenshot.shot()
this = this + '.png'
img_rgb = cv2.imread(this)
template = cv2.imread('playing.png')
res = cv2.matchTemplate(img_rgb, template, cv2.TM_SQDIFF_NORMED)
threshold = 0.8
loc = np.where(res >= threshold)
cv2.imwrite('result.png', img_rgb)
return loc
def is_on_screen(this):
this = this + '.png'
Screenshot.shot()
small_image = cv2.imread(this)
large_image = cv2.imread('playing.png')
result = cv2.matchTemplate(small_image, large_image,
cv2.TM_SQDIFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
# print('ImageCoordinate::is_on_screen => ' + this + ' ' + str(min_val))
mn, _, mn_loc, _ = cv2.minMaxLoc(result)
mp_x, mp_y = mn_loc
# pyautogui.moveTo(mp_x, mp_y)
if min_val > 0.05:
return False
else:
return True
def coords(this, shot=True):
this = this + '.png'
if shot:
Screenshot.shot()
else:
print('No screenshot')
small_image = cv2.imread(this)
h, w, c = small_image.shape
large_image = cv2.imread('playing.png')
result = cv2.matchTemplate(small_image, large_image,
cv2.TM_SQDIFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
# print('ImageCoordinate::coords => ' + this + ' ' + str(min_val))
mn, _, mn_loc, _ = cv2.minMaxLoc(result)
mp_x, mp_y = mn_loc
# pyautogui.moveTo(mp_x, mp_y)
if min_val > 0.25:
return [0, 0, min_val]
mn, _, mn_loc, _ = cv2.minMaxLoc(result)
mp_x, mp_y = mn_loc
location = [mp_x + w / 2, mp_y + h / 2, min_val]
return location
def is_on_screen(this, accuracy=0.14):
this = this + '.png'
Screenshot.shot()
small_image = cv2.imread(this)
h, w, c = small_image.shape
large_image = cv2.imread('playing.png')
result = cv2.matchTemplate(
small_image, large_image, cv2.TM_SQDIFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
#print('ImageCoordinate::is_on_screen => ' + this + ' ' + str(min_val))
mn, _, mn_loc, mx_loc = cv2.minMaxLoc(result)
mp_x, mp_y = mn_loc
m_x, m_y = mx_loc
# print(mn_loc)
# top_left = mn_loc
# mx_right = mx_loc
bt_rt = (mn_loc[0], mn_loc[1])
bt_rtw = (mn_loc[0]+w, mn_loc[1]+h)
# cv2.rectangle(large_image,top_left,bt_rt,255,2)
# bt_rt =(mx_right[0]+h,mx_right[1]+w)
# cv2.rectangle(large_image,mx_right,bt_rt,255,2)
# cv2.imwrite('result_'+this.replace('images/',''), large_image)
# print('saved')
#pyautogui.moveTo(mp_x, mp_y)
print(min_val)
if min_val > accuracy:
return False
else:
mn, _, mn_loc, _ = cv2.minMaxLoc(result)
mp_x, mp_y = mn_loc
ordinal = random.randrange(1, 15)
a = random.randrange(-ordinal, ordinal)
b = random.randrange(-ordinal, ordinal)
location = [mp_x + w / 2+a, mp_y + h / 2+b, bt_rt, bt_rtw, min_val]
return location
def take_screenshot(self):
Screenshot.shot('default.png')