def run_object_detection(config):
# Set variables
camera_width = 320
camera_height = 240
window_name = "Object Detection Demo"
input_width = config.IMAGE_SIZE[1]
input_height = config.IMAGE_SIZE[0]
vc = cv2.VideoCapture(0)
vc.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, camera_width)
vc.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, camera_height)
vc.set(cv2.cv.CV_CAP_PROP_FPS, 15)
pool = Pool(processes=1)
result = False
fps = 1.0
q_save = Queue()
q_show = Queue()
grabbed, camera_img = vc.read()
q_show.put(camera_img.copy())
input_img = camera_img.copy()
# ----------- Beginning of Main Loop ---------------
while True:
m1 = MyTime("1 loop of while(1) of main()")
pool_result = pool.apply_async(run_inference, (input_img, ))
is_first = True
while True:
sleep(0.01)
grabbed, camera_img = vc.read()
if is_first:
input_img = camera_img.copy()
is_first = False
q_save.put(camera_img.copy())
if not q_show.empty():
window_img = q_show.get()
if result:
window_img = add_rectangle(config.CLASSES, window_img,
result,
(input_height, input_width))
window_img = add_fps(window_img, fps)
# ---------- END of if result != False -----------------
cv2.imshow(window_name, window_img)
key = cv2.waitKey(2) # Wait for 2ms
if key == 27: # ESC to quit
return
if pool_result.ready():
break
# -------------- END of wait loop ----------------------
q_show = clear_queue(q_show)
q_save, q_show = swap_queue(q_save, q_show)
result, fps = pool_result.get()
m1.show()
def show_object_detection(img, result, fps, window_height, window_width,
config):
window_img = resize(img, size=[window_height, window_width])
input_width = config.IMAGE_SIZE[1]
input_height = config.IMAGE_SIZE[0]
window_img = add_rectangle(config.CLASSES, window_img, result,
(input_height, input_width))
img = add_fps(window_img, fps)
window_name = "Object Detection Demo"
cv2.imshow(window_name, window_img)
