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"""
drawlines using kmeans to group
"""
import cv2
import numpy as np
from grabscreen import grab_screen
from sklearn.cluster import KMeans
import pyautogui
import time
BOX = (0, 40, 800, 640)
hood_y = 410
horizon_y = 270
VERTICES = np.array([[4, horizon_y], [800, horizon_y], [800, hood_y], [4, hood_y]])
def draw_lines(img, lines):
try:
for coords in lines:
coords = np.array(coords, dtype='uint32')
cv2.line(img,
(coords[0], coords[1]),
(coords[2], coords[3]),
[255, 255, 255], 5)
except (TypeError, IndexError):
pass
def roi(img, vertices):
mask = np.zeros_like(img)
cv2.fillPoly(mask, vertices, 255)
masked = cv2.bitwise_and(img, mask)
return masked
def process_img(processed_img):
processed_img = cv2.Canny(processed_img, threshold1=100, threshold2=300)
processed_img = roi(processed_img, [VERTICES])
processed_img = cv2.GaussianBlur(processed_img, (5, 5), 0)
lines = cv2.HoughLinesP(processed_img, 1, np.pi / 180, 180, np.array([]), 140, 20)
try:
nlines = np.array([l[0] for l in lines])
kmeans = KMeans(n_clusters=2, random_state=0).fit(nlines)
draw_lines(processed_img, kmeans.cluster_centers_)
except TypeError:
pass
finally:
return processed_img
def main():
while True:
ti = time.time()
screen = grab_screen(region=BOX)
new_screen = process_img(screen)
print('{:.2f} FPS'.format(1 / (time.time() - ti)))
cv2.imshow('window', new_screen)
if cv2.waitKey(25) & 0xFF == ord('q'):
cv2.destroyAllWindows()
break
if __name__ == '__main__':
main()
