def main():
img_source = input_output.Source(photo_path + photo_file)
detector = detectors.Detector(
'/Users/elijah/Dropbox/Programming/detectors/configs/closest_obstacle.json'
)
while (True):
frame_ = img_source.get_frame()
#frame = cv2.cvtColor (frame_, cv2.COLOR_RGB2BGR)
frame = frame_
cv2.waitKey(1)
(obstacle_pixels, labels), _ = detector.detect(frame,
"obstacle detector")
#draw obstacles on the frame
result = frame.copy()
#os.system ("clear")
#print (obstacle_pixels)
#for i in range (len (obstacle_pixels)):
# x = i
# y = obstacle_pixels [i]
# type = labels [i]
# result = cv2.circle (result, (x, y), 5, (12 + type * 150, 250 - type * 120, 190 + type * 110), thickness = -1)
stages = detector.get_stages_picts("obstacle detector")
for i in range(len(stages)):
cv2.imshow(str(i), stages[i])
#cv2.imshow ("frame", result)
time.sleep(0.02)
keyb = cv2.waitKey(1) & 0xFF
if (keyb == ord('q')):
break
cv2.destroyAllWindows()
def __init__(self, stream, settings):
self.__settings = settings.getSettings()
self.__videocap = stream
self.__videowriter = writer
self.__detectors = {'original':detectors.Detector(self.__settings),
'colour': detectors.ColourDetector(self.__settings),
'colourdiff': detectors.ColourDiffDetector(self.__settings),
'difference':detectors.DiffDetector(self.__settings),
'background':detectors.BackgroundSubDetector(self.__settings),
'watershed': detectors.WatershedDetector(self.__settings),
}
self.__trackers = {'csrt': trackers.CSRTTracker(self.__settings),
}
self.__detector = self.detectors['original']
self.__isrunning = True
self.__istracking = False
self.__isrecording = False
#frame = cv2.cvtColor(frame, cv2.COLOR_YCrCb2RGB)
#frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
cv2.namedWindow('Colorbars')
#source = Source ("../images/2019_08_11_08h00m33s/00014.png")
#source = Source ("../images/00014.png")
#source = Source ("../images/obst_bottom.png")
source = Source("1")
#detector = detectors.Detector ('../configs/multiple_objects1.json')
#detector = detectors.Detector ('../configs/closest_obstacle.json')
low_th = (140, 70, 40)
high_th = (220, 130, 100)
detector = detectors.Detector()
detector.add_filter(detectors.colorspace_to_colorspace("RGB", "HSV"), "a",
"colorspace")
detector.add_filter(detectors.inrange(low_th, high_th), "a", "inrange")
#detector.add_filter (detectors.filter_connected_components (10), "a", "filter")
detector.add_filter(detectors.leave_max_area_cc(), "a", "max cc extraction")
detector.add_filter(detectors.bottom_cc_point(), "a",
"bottom point extraction")
#detector.add_filter (detectors.bottom_bbox_point (), "a", "desired point extraction")
cv2.createTrackbar("l1", "Colorbars", 0, 255, nothing)
cv2.createTrackbar("h1", "Colorbars", 255, 255, nothing)
def main():
detector = detectors.Detector(
'/Users/elijah/Dropbox/Programming/detectors/configs/object_tracking.json'
)
img_source = Source(photo_path + photo_file, "", True)
obstacle_source = Source(photo_path + obstacle_file)
target_tracker = tracker.Tracker()
img_sh = img_source.shape()
obst_sh = obstacle_source.shape()
print(img_sh, obst_sh)
x_obs_rot = int(img_sh[1] / 2)
y_obs_rot = int(img_sh[0] / 2)
obs_radius = int(x_obs_rot / 3)
#print (x_obs_rot, y_obs_rot, radius)
angle = 0
angular_speed = 0.231415234567654
turn_num = 0
while (True):
frame = img_source.get_frame()
obstacle = obstacle_source.get_frame()
x_obs = x_obs_rot + int(obs_radius * math.cos(angle))
y_obs = y_obs_rot + int(obs_radius * math.sin(angle))
angle += angular_speed
frame[y_obs:y_obs + obst_sh[0], x_obs:x_obs + obst_sh[1], :] = obstacle
#frame = frame_
cv2.waitKey(1)
os.system('clear')
(x, y), success = detector.detect(frame, "obstacle detector")
measurement_time = time.time()
#print (x, y, measurement_time)
target_tracker.add_measurement((x, y), measurement_time)
result = frame.copy()
if (turn_num > 10):
target_tracker.calc_cycle_parameters()
(center_x,
center_y) = target_tracker.cycle_parameters["circle center"]
radius = target_tracker.cycle_parameters["radius"]
lowest_x = int(center_x)
lowest_y = int(center_y + radius)
result = cv2.circle(result, (lowest_x, lowest_y),
9, (20, 150, 190),
thickness=-1)
time_to_approach = target_tracker.predict_time(
(lowest_x, lowest_y))
if (time_to_approach < 0.2):
result = cv2.circle(result, (lowest_x, lowest_y),
15, (220, 15, 90),
thickness=-1)
print(time_to_approach)
turn_num += 1
#draw circle on the frame
if (success == True):
#print ("detected")
result = cv2.circle(result, (x, y),
9, (120, 15, 190),
thickness=-1)
else:
print("not detected")
stages = detector.get_stages_picts("obstacle detector")
for i in range(2):
cv2.imshow(str(i), stages[i])
#processing_stages = detector.stages ()
#resultant_frame = form_images (processing_stages)
cv2.imshow("frame", result)
time.sleep(0.02)
#clear_output (wait=True)
keyb = cv2.waitKey(1) & 0xFF
if (keyb == ord('q')):
break
cam.release()
cv2.destroyAllWindows()
def main():
INPUT_SOURCE = PHOTO
#cam_num = max (get_available_cameras ())
#cam = cv2.VideoCapture (cam_num)
#if (INPUT_SOURCE != CAMERA):
# cam.release ()
#if (INPUT_SOURCE == VIDEO):
# cam = cv2.VideoCapture (video_path + video_file)
if (INPUT_SOURCE == PHOTO):
img = cv2.imread(photo_path + photo_file)
#cv2.namedWindow ("frame", cv2.WINDOW_NORMAL)
#cv2.namedWindow ("frame")
#cv2.resizeWindow ("frame", (640*2, 480*2))
#cv2.resizeWindow ("frame", (480, 640))
str_num = 0
low_th = (57, 150, 110)
high_th = (67, 160, 120)
detector = detectors.Detector()
detector.add_filter(detectors.inrange(low_th, high_th), "inrange")
detector.add_filter(detectors.max_area_cc_bbox(), "bbox extraction")
while (True):
#if (INPUT_SOURCE == CAMERA or INPUT_SOURCE == VIDEO):
# ret, frame_ = cam.read ()
if (INPUT_SOURCE == PHOTO):
frame_ = img.copy()
#frame = cv2.cvtColor (frame_, cv2.COLOR_RGB2BGR)
frame = frame_
cv2.waitKey(1)
#top left, bottom right
bbox_tl, bbox_br = detector.detect(frame)
#draw bbox on the frame
frame_with_bbox = cv2.rectangle(frame.copy(), bbox_tl, bbox_br,
(255, 0, 0), 5)
stages = detector.get_stages()
for i in range(2):
cv2.imshow(str(i), stages[i])
#processing_stages = detector.stages ()
#resultant_frame = form_images (processing_stages)
cv2.imshow("frame", frame_with_bbox)
time.sleep(0.02)
#clear_output (wait=True)
keyb = cv2.waitKey(1) & 0xFF
if (keyb == ord('q')):
break
cam.release()
cv2.destroyAllWindows()
def main():
INPUT_SOURCE = PHOTO
#cam_num = max (get_available_cameras ())
#cam = cv2.VideoCapture (cam_num)
#if (INPUT_SOURCE != CAMERA):
# cam.release ()
#if (INPUT_SOURCE == VIDEO):
# cam = cv2.VideoCapture (video_path + video_file)
if (INPUT_SOURCE == PHOTO):
img = cv2.imread(photo_path + photo_file)
str_num = 0
detector = detectors.Detector('multiple_objects.json')
while (True):
#if (INPUT_SOURCE == CAMERA or INPUT_SOURCE == VIDEO):
# ret, frame_ = cam.read ()
if (INPUT_SOURCE == PHOTO):
frame_ = img.copy()
#frame = cv2.cvtColor (frame_, cv2.COLOR_RGB2BGR)
frame = frame_
cv2.waitKey(1)
os.system('clear')
(bbox_tl, bbox_br), success = detector.detect(frame, "ball detector")
result = frame.copy()
if (success == True):
print("detected")
result = cv2.rectangle(frame.copy(), bbox_tl, bbox_br, (255, 0, 0),
5)
else:
print("not detected")
(x, y), success = detector.detect(frame, "obstacle detector")
#draw circle on the frame
if (success == True):
print("detected")
result = cv2.circle(result, (x, y),
9, (120, 15, 190),
thickness=-1)
else:
print("not detected")
stages = detector.get_stages()
for i in range(2):
cv2.imshow(str(i), stages[i])
#processing_stages = detector.stages ()
#resultant_frame = form_images (processing_stages)
cv2.imshow("frame", result)
time.sleep(0.02)
#clear_output (wait=True)
keyb = cv2.waitKey(1) & 0xFF
if (keyb == ord('q')):
break
cam.release()
cv2.destroyAllWindows()
def main():
INPUT_SOURCE = PHOTO
#cam_num = max (get_available_cameras ())
#cam = cv2.VideoCapture (cam_num)
#if (INPUT_SOURCE != CAMERA):
# cam.release ()
#if (INPUT_SOURCE == VIDEO):
# cam = cv2.VideoCapture (video_path + video_file)
if (INPUT_SOURCE == PHOTO):
img = cv2.imread(photo_path + photo_file)
obstacle = cv2.imread(photo_path + obstacle_file)
obstacle_sh = obstacle.shape
str_num = 0
detector = detectors.Detector(
'/Users/elijah/Dropbox/Programming/detectors/configs/object_tracking.json'
)
sh = img.shape
x_obs_rot = sh[1] // 2
y_obs_rot = sh[0] // 2
radius = x_obs_rot // 2
angle = 0
while (True):
#if (INPUT_SOURCE == CAMERA or INPUT_SOURCE == VIDEO):
# ret, frame_ = cam.read ()
if (INPUT_SOURCE == PHOTO):
frame_ = img.copy()
x_obs = x_obs_rot + radius * math.cos(angle)
y_obs = y_obs_rot + radius * math.sin(angle)
angle += 0.1
frame[x_obs:x_obs + obstacle_sh[1],
y_obs:y_obs + obstacle_sh[0], :] = obstacle
frame = frame_
cv2.waitKey(1)
os.system('clear')
(x, y), success = detector.detect(frame, "obstacle detector")
#draw circle on the frame
if (success == True):
print("detected")
result = cv2.circle(result, (x, y),
9, (120, 15, 190),
thickness=-1)
else:
print("not detected")
stages = detector.get_stages()
for i in range(2):
cv2.imshow(str(i), stages[i])
#processing_stages = detector.stages ()
#resultant_frame = form_images (processing_stages)
cv2.imshow("frame", result)
time.sleep(0.02)
#clear_output (wait=True)
keyb = cv2.waitKey(1) & 0xFF
if (keyb == ord('q')):
break
cam.release()
cv2.destroyAllWindows()
def main():
#detector = detectors.Detector ('/Users/elijah/Dropbox/Programming/detectors/configs/basketball.json')
detector = detectors.Detector(
'/Users/elijah/Dropbox/Programming/detectors/configs/closest_obstacle.json'
)
source = input_output.Source(
"/Users/elijah/Dropbox/Programming/detectors/images/2019_08_11_08h11m07s/"
)
#source = input_output.Source ("/Users/elijah/Dropbox/Programming/detectors/data/output.avi")
#source = input_output.Source ("-1")
#fourcc = cv2.VideoWriter_fourcc(*'XVID')
#out = cv2.VideoWriter('output.avi',fourcc, 20.0, (640,480))
#a = 0
while (True):
frame = source.get_frame()
#out.write(frame)
#print (a)
#a += 1
#if (a > 49):
# break
(x, y), success = detector.detect(frame, "obstacle detector")
#result = frame.copy ()
#draw circle on the frame
if (success == True):
print("detected")
#result = cv2.circle (result, (x, y), 9, (120, 15, 190), thickness = -1)
else:
print("not detected")
stages = detector.get_stages_picts("obstacle detector")
#for i in range (len (stages)):
# cv2.imshow (str (i), stages [i])
resultant_frame = input_output.form_grid(stages)
print(resultant_frame.shape)
#cv2.imshow ("frame", result)
cv2.imshow("frame", resultant_frame)
time.sleep(0.02)
keyb = cv2.waitKey(1) & 0xFF
if (keyb == ord('q')):
break
out.release()
#cam.release ()
cv2.destroyAllWindows()