def run_nn(img, input_queue, width, height):
frameNn = dai.ImgFrame()
frameNn.setType(dai.ImgFrame.Type.BGR888p)
frameNn.setWidth(width)
frameNn.setHeight(height)
frameNn.setData(toPlanar(img, (height, width)))
input_queue.send(frameNn)
def run_face(self):
# img, scale, top, left = resize_padding(self.frame, 300, 300)
if not self.camera:
nn_data = run_nn(
self.face_in,
self.face_nn,
{"data": toPlanar(self.frame, (300, 300))},
)
else:
nn_data = self.face_nn.tryGet()
if nn_data is None:
return False
bboxes = nn_data.detections
self.number_of_people = len(bboxes)
for bbox in bboxes:
face_coord = frameNorm(
self.debug_frame, [bbox.xmin, bbox.ymin, bbox.xmax, bbox.ymax])
# face_coord = restore_point(face_coord, scale, top, left).astype(int)
face_coord = scale_bbox(face_coord)
self.face_frames.put(self.frame[face_coord[1]:face_coord[3],
face_coord[0]:face_coord[2]])
self.face_coords.put(face_coord)
self.draw_bbox(face_coord, (10, 245, 10))
return True
def run_mask(self):
masked = 0
while self.face_frames.qsize():
face_frame = self.face_frames.get()
face_coord = self.face_coords.get()
nn_data = run_nn(
self.mask_in,
self.mask_nn,
{"data": toPlanar(face_frame, (224, 224))},
)
if nn_data is None:
return
self.fps_handler.tick("NN")
out = softmax(to_nn_result(nn_data))
mask = np.argmax(out) > 0.5
color = (0, 255, 0) if mask else (0, 0, 255)
self.draw_bbox(face_coord, color)
self.put_text(f"{out[1]:.2%}", face_coord, color)
if mask:
masked += 1
self.put_text(
f"masks: {masked / self.number_of_people:.2%} ",
(10, 30),
(255, 0, 0),
0.75,
)
def run_nn(x_in, frame, w, h):
nn_data = dai.ImgFrame()
nn_data.setData(toPlanar(frame, (w, h)))
nn_data.setType(dai.RawImgFrame.Type.BGR888p)
nn_data.setTimestamp(monotonic())
nn_data.setWidth(w)
nn_data.setHeight(h)
x_in.send(nn_data)
def run_nn(img, input_queue, width, height):
"""
It takes an image, converts it to a planar image, and sends it to the input queue
:param img: The image to be processed
:param input_queue: The input queue to the neural network
:param width: The width of the image in pixels
:param height: The height of the image in pixels
"""
frameNn = dai.ImgFrame()
frameNn.setType(dai.ImgFrame.Type.BGR888p)
frameNn.setWidth(width)
frameNn.setHeight(height)
frameNn.setData(toPlanar(img, (height, width)))
input_queue.send(frameNn)