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")