def detect(self):
""" Performs object detection and publishes coordinates. """
# Initialize detector
self.send_message(Color.GREEN, "[INFO] Initializing TinyYOLOv3 detector.")
det = Detector("/home/nvidia/catkin_ws/src/boat/scripts/vantec-config/tiny3.cfg", "/home/nvidia/catkin_ws/src/boat/scripts/vantec-config/tiny3_68000.weights", "/home/nvidia/catkin_ws/src/boat/scripts/vantec-config/obj.names")
(H, W) = (None, None)
# Load model
self.send_message(Color.GREEN, "[INFO] Loading network model.")
net = det.load_model()
print(net)
# Initilialize Video Stream
self.send_message(Color.GREEN, "[INFO] Starting video stream.")
counter = 0
dets = 0
nondets = 0
detect = True
fps = FPS().start()
boxes, confidences, indices, cls_ids, colors, ids, distances = [], [], [], [], [], [], []
zed_cam_size = 1280
ret = True
while not rospy.is_shutdown():
# Grab next frame
#ret, frame = video.read()
frame = self.image
#cap = cv2.VideoCapture("/home/nvidia/opencv_install/pajarito/bird.jpg")
#hasFrame, frame = cap.read()
color = ""
diststring = ""
##AQUI SE MODIFICA EL VIDEO
#frame = add_brightness(frame)
#frame = add_darkness(frame)
if cv2.waitKey(1) & 0xFF == ord ('q'):
self.send_message(Color.RED, "[DONE] Quitting program.")
break
frame = imutils.resize(frame, width=1000)
(H, W) = frame.shape[:2]
if det.get_w() is None or det.get_h() is None:
det.set_h(H)
det.set_w(W)
# Perform detection
detect = True
dets += 1
# Get bounding boxes, condifences, indices and class IDs
boxes, confidences, indices, cls_ids = det.get_detections(net, frame)
# Publish detections
# If there were any previous detections, draw them
colors = []
distances = []
obj_list = ObjDetectedList()
len_list = 0
for ix in indices:
i = ix[0]
box = boxes[i]
x, y, w, h = box
x, y, w, h = int(x), int(y), int(w), int(h)
if detect == True:
color = self.calculate_color(frame,x,y,h,w)
depth = self.img_depth[y:y+h,x:x+w]
d_list = []
for j in depth:
if str(j[1]) != 'nan' and str(j[1]) != 'inf':
d_list.append(j[1])
if len(d_list) != 0:
dist = np.mean(d_list)
else:
dist = 'nan'
if (dist < .30):
diststring = "OUT OF RANGE"
else:
diststring = str(dist) + " m"
color = str(color.color)
colors.append(color)
distances.append(dist)
if str(dist) != 'nan':
obj = ObjDetected()
#print(p1,p2)
obj.x = x
obj.y = y
obj.h = h
obj.w = w
obj.X = dist
obj.Y = 0
obj.color = color
obj.clase = 'bouy' if cls_ids[i] == 0 else 'marker'
len_list += 1
obj_list.objects.append(obj)
det.draw_prediction(frame, cls_ids[i], confidences[i], color,diststring, x, y, x+w, y+h)
det_str = "Det: {}, BBoxes {}, Colors {}, Distance {}".format(dets, boxes, colors, distances)
self.send_message(Color.BLUE, det_str)
fps.update()
obj_list.len = len_list
self.detector_pub.publish(obj_list)
cv2.line(frame, (500,560), (500,0), (255,0,0))
fps.stop()
info = [
("Detects: ", dets),
("No detects: ", nondets),
("FPS", "{:.2F}".format(fps.fps())),
]
for (i, (k, v)) in enumerate(info):
text = "{}: {}".format(k, v)
cv2.putText(frame, text, (10, det.get_h() - ((i * 20) + 20)), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
# Show current frame
#cv2.imshow("Frame", frame)
#print(self.depth)
#cv2.waitKey(3)
rate.sleep()
def detect():
""" Performs object detection and publishes coordinates. """
#global image and depth frames from ZED camera
global image
global points_list
points_list = [[0, 0, 0]] * 921600
image = np.zeros((560, 1000, 3), np.uint8)
# Initialize detector
send_message(Color.GREEN, "[INFO] Initializing TinyYOLOv3 detector.")
det = Detector(
"/home/nvidia/catkin_ws/src/boat/scripts/vantec-config/tiny3.cfg",
"/home/nvidia/catkin_ws/src/boat/scripts/vantec-config/tiny3_68000.weights",
"/home/nvidia/catkin_ws/src/boat/scripts/vantec-config/obj.names")
(H, W) = (None, None)
# Load model
send_message(Color.GREEN, "[INFO] Loading network model.")
net = det.load_model()
# Initilialize Video Stream
send_message(Color.GREEN, "[INFO] Starting video stream.")
counter = 0
dets = 0
nondets = 0
detect = True
fps = FPS().start()
boxes, confidences, indices, cls_ids, colors, ids, distances = [], [], [], [], [], [], []
ret = True
while not rospy.is_shutdown():
# Grab next frame
#ret, frame = video.read()
frame = image
color = ""
diststring = ""
##AQUI SE MODIFICA EL VIDEO
#frame = add_brightness(frame)
#frame = add_darkness(frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
send_message(Color.RED, "[DONE] Quitting program.")
break
print(frame.shape)
frame = imutils.resize(frame, width=1000)
(H, W) = frame.shape[:2]
if det.get_w() is None or det.get_h() is None:
det.set_h(H)
det.set_w(W)
# Perform detection
detect = True
dets += 1
# Get bounding boxes, condifences, indices and class IDs
boxes, confidences, indices, cls_ids = det.get_detections(net, frame)
# Publish detections
det_str = "Det: {}, BBoxes {}, Colors {}, Distance {}".format(
dets, boxes, colors, distances)
send_message(Color.BLUE, det_str)
# If there were any previous detections, draw them
colors = []
distances = []
obj_list = ObjDetectedList()
len_list = 0
for ix in indices:
i = ix[0]
box = boxes[i]
x, y, w, h = box
x, y, w, h = int(x), int(y), int(w), int(h)
if detect == True:
color = calculate_color(frame, x, y, h, w)
p1 = int((x + w / 2) * 1.28)
p2 = int((y + h / 2) * 1.28)
dist = points_list[(p1 + p2 * 1280)][0]
if (dist < .30):
diststring = "OUT OF RANGE"
else:
diststring = str(dist) + " m"
color = str(color.color)
colors.append(color)
distances.append(dist)
obj = ObjDetected()
print(p1, p2)
obj.x = x
obj.y = y
obj.h = h
obj.w = w
obj.X = points_list[(p1 + p2 * 1280)][0]
obj.Y = points_list[(p1 + p2 * 1280)][1]
obj.color = color
obj.clase = 'bouy' if cls_ids[i] == 0 else 'marker'
len_list += 1
obj_list.objects.append(obj)
det.draw_prediction(frame, cls_ids[i], confidences[i], color,
diststring, x, y, x + w, y + h)
fps.update()
obj_list.len = len_list
detector_pub.publish(obj_list)
cv2.line(frame, (500, 560), (500, 0), (255, 0, 0))
fps.stop()
info = [
("Detects: ", dets),
("No detects: ", nondets),
("FPS", "{:.2F}".format(fps.fps())),
]
for (i, (k, v)) in enumerate(info):
text = "{}: {}".format(k, v)
cv2.putText(frame, text, (10, det.get_h() - ((i * 20) + 20)),
cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
# Show current frame
#cv2.imshow("depth", depth_frame)
cv2.imshow("Frame", frame)
#while cv2.waitKey(0) and 0xFF == ord('q'):
rate.sleep()
