def main():
paused = False
while not paused:
#image_org = cv2.imread(file_paths[0])
image_org = grab_screen(region=(0, 30, 1250, 750))
#speed, speed_img = get_speed(image_org)
points = get_3_points(image_org)
image = process_image(image_org)
point_colour_value, image_org = get_point_data(image, points, 50)
#print(type(speed))
process_data(point_colour_value)
#
color = (0, 0, 0)
image_org = cv2.rectangle(image_org, (1120, 635), (1185, 670), color,
5)
#cv2.imshow("window", cv2.resize(image_org, (500, 300)))
#cv2.imshow("window", cv2.resize(speed_img, (500, 300)))
if cv2.waitKey(25) & 0xFF == ord('q'):
cv2.destroyAllWindows()
break
keys = key_check()
if 'T' in keys:
print("son")
if paused:
paused = False
print('unpaused!')
time.sleep(1)
else:
print('Pausing!')
paused = True
time.sleep(1)
def main(file_name, starting_value):
file_name = file_name
starting_value = starting_value
paused = False
timer = True
training_data = []
if timer:
for i in range(4)[::-1]:
print(i + 1, "sec left")
time.sleep(1)
print("Starting Rec")
last_time = time.time()
while True:
if not paused:
screen = grab_screen(region=(0,30,1250,750))
screen = cv2.cvtColor(screen, cv2.COLOR_BGR2GRAY)
screen = cv2.resize(screen, (500,288))
screen = roi(screen, [vertices])
screen = screen[110:270, 0:480]
#cv2.imshow("fens", screen)
#cv2.imshow("crop", crop)
keys = key_check()
output = keys_to_output(keys)
training_data.append([screen/255,output])
last_time = time.time()
#print(output)
if len(training_data) % 250 == 0:
print(len(training_data))
if len(training_data) == 4000:
np.save(file_name,training_data)
print('SAVED')
training_data = []
starting_value += 1
file_name = 'D:/Projects/self_driving_car/Final_data/training_data_9_final-{}.npy'.format(starting_value)
if cv2.waitKey(25) & 0xFF == ord('q'):
cv2.destroyAllWindows()
break
keys = key_check()
if 'T' in keys:
if paused:
paused = False
print('unpaused!')
time.sleep(1)
else:
print('Pausing!')
paused = True
time.sleep(1)
def main(file_name, starting_value):
"""
file_name = file_name
starting_value = starting_value
training_data = []
print("test 1")
'''
for i in list(range(4))[::-1]:
print(i+1)
time.sleep(1)
'''
print('STARTING!!!')
last_time = time.time()
"""
paused = False
ten_fps = True
while (True):
screen = grab_screen(region=(0, 30, 1010, 800))
screen = cv2.cvtColor(screen, cv2.COLOR_BGR2GRAY)
screen = cv2.resize(screen, (480, 270))
screen = roi(screen, [vertices])
cv2.imshow("fens", screen)
if not paused:
keys = key_check()
#print('loop took {} seconds'.format(time.time()-last_time))
'''
if (time.time() - last_time >= 0.1):
output = keys_to_output(keys)
training_data.append([screen,output])
last_time = time.time()
if len(training_data) % 100 == 0:
print(len(training_data))
if len(training_data) == 1000:
np.save(file_name,training_data)
print('SAVED')
training_data = []
starting_value += 1
file_name = 'D:/Projects/self_driving_car/Training_data/training_data-{}.npy'.format(starting_value)
#cv2.imshow('window',cv2.resize(screen,(640,360)))
#if cv2.waitKey(25) & 0xFF == ord('q'):
# cv2.destroyAllWindows()
# break
'''
keys = key_check()
if 'T' in keys:
if paused:
paused = False
print('unpaused!')
time.sleep(1)
else:
print('Pausing!')
paused = True
time.sleep(1)
def main():
while True:
img = grab_screen(region=(0,30,1250,750))
screen = cv2.resize(img, (500, 300))
R = 1
screen = cv2.cvtColor(screen, cv2.COLOR_BGR2GRAY)
#image = Image.fromarray(img.astype('uint8'), 'RGB')
screen = entropy(screen, disk(R))
cv2.imshow("sss",screen)
if cv2.waitKey(25) & 0xFF == ord('q'):
cv2.destroyAllWindows()
def main():
paused = False
while True:
if not paused:
screen = grab_screen(region=(0,30,1250,750))
screen = cv2.cvtColor(screen, cv2.COLOR_BGR2RGB)
org_image = screen
screen = cv2.resize(screen,(input_w, input_h))
screen = img_to_array(screen)
screen /= 255.0
screen = expand_dims(screen, 0)
#screen = cv2.resize(screen,(1, 416, 416, 3))
yhat = model.predict(screen)
boxes = list()
for i in range(len(yhat)):
boxes += decode_netout(yhat[i][0], anchors[i], class_threshold,nms_threshold, input_h, input_w)
correct_yolo_boxes(boxes, image_h, image_w, input_h, input_w)
do_nms(boxes, 0.5)
draw_boxes(org_image, boxes, labels, class_threshold)
cv2.imshow("fens", org_image)
#cv2.imshow("crop", crop)
#keys = key_check()
#output = keys_to_output(keys)
#training_data.append([screen/255,output])
#last_time = time.time()
#if len(training_data) % 250 == 0:
# print(len(training_data))
# if len(training_data) == 2500:
# np.save(file_name,training_data)
# print('SAVED')
# training_data = []
# starting_value += 1
# file_name = 'D:/Projects/self_driving_car/Training_data/training_data_final-{}.npy'.format(starting_value)
if cv2.waitKey(25) & 0xFF == ord('q'):
cv2.destroyAllWindows()
break
keys = key_check()
if 'T' in keys:
if paused:
paused = False
print('unpaused!')
time.sleep(1)
else:
print('Pausing!')
paused = True
time.sleep(1)
def main():
last_time = time.time()
for i in list(range(4))[::-1]:
print(i + 1)
time.sleep(1)
paused = False
#prob_output_normal_final = []
while (True):
if not paused:
# 800x600 windowed mode
#screen = np.array(ImageGrab.grab(bbox=(0,40,800,640)))
screen = grab_screen(region=(0, 30, 1250, 750))
screen = cv2.cvtColor(screen, cv2.COLOR_BGR2GRAY)
screen = cv2.resize(screen, (480, 270))
screen = roi(screen, [vertices])
screen = screen[110:270, 0:480]
screen = screen.reshape(WIDTH, HEIGHT, 1)
prediction = model.predict([screen])[0]
Drive(prediction)
keys = key_check()
#print("%.4f" % prediction[0], "%.4f" % prediction[1], "%.4f" % prediction[2], "%.4f" % prediction[3])
#prob_output_normal_final.append(prediction)
#if (len(prob_output_normal_final) % 250 == 0):
# print(len(prob_output_normal_final))
#if(len(prob_output_normal_final) % 5000 == 0):
# prob_output_normal_final = np.array(prob_output_normal_final)
# file_name = 'D:/Projects/self_driving_car/Training_data/output-probs-normal-{}.npy'.format(4)
# np.save(file_name,prob_output_normal_final)
# print("Saved")
keys = key_check()
# p pauses game and can get annoying.
if 'T' in keys:
if paused:
paused = False
time.sleep(1)
else:
paused = True
ReleaseKey(A)
ReleaseKey(W)
ReleaseKey(D)
ReleaseKey(S)
time.sleep(1)
break
def roi(img, vertices):
mask = np.zeros_like(img)
cv2.fillPoly(mask, vertices, 255)
masked = cv2.bitwise_and(img, mask)
return masked
vertices = np.array(
[[0, 120], [150, 110], [350, 110], [480, 120], [480, 270], [0, 270]],
np.int32)
while (True):
screen = grab_screen(region=(0, 30, 1010, 800))
screen = cv2.cvtColor(screen, cv2.COLOR_BGR2GRAY)
screen = cv2.resize(screen, (480, 270))
screen = roi(screen, [vertices])
cv2.imshow("fens", screen)
if cv2.waitKey(25) & 0xFF == ord('q'):
cv2.destroyAllWindows()
break
def main(file_name, starting_value):
"""
file_name = file_name
starting_value = starting_value
training_data = []
print("test 1")