Open RobeSafe-UAH opened 3 years ago
Hi folks,
I have observed this part of the source code:
""" det.type in self.classes and det.score > self.score_thres):
intrinsics = ros_intrinsics(self.camera_info.P) input_tensor,theta_ray = preprocessing(image,det,intrinsics) [orient, conf, dim] = self.model(input_tensor) #Apply the model to get the estimation orient = orient.cpu().data.numpy()[0, :, :] conf = conf.cpu().data.numpy()[0, :] dim = dim.cpu().data.numpy()[0, :] # print("Conf:{}".format(conf)) dim += self.averages.get_item(det.type) argmax = np.argmax(conf) orient = orient[argmax, :] cos = orient[0] sin = orient[1] alpha = np.arctan2(sin, cos) alpha += self.angle_bins[argmax] alpha -= np.pi
"""
But that conf is a tuple of two numbers, which is used to determine the best orientation, like this:
""" Conf:[ 6.3896847 -6.5501723] Conf:[ 6.496025 -6.7066655] Conf:[ 5.410366 -5.5474744] Conf:[ 7.092432 -7.3124714] Conf:[ 9.061753 -9.251386] Conf:[ 7.587371 -7.831802] Conf:[ 2.149212 -2.1235662] Conf:[-0.84504336 0.89392436] Conf:[ 4.436549 -4.5268965] Conf:[ 1.2938225 -1.4327605] """
How can I get the score of the final 3D Bounding Box? (0 to 1 value, like in every 2D or 3D object detector)
Thanks in advance.
you solve it? @RobeSafe-UAH
Why don't you normalize the confidence array?
Hi folks,
I have observed this part of the source code:
""" det.type in self.classes and det.score > self.score_thres):
"""
But that conf is a tuple of two numbers, which is used to determine the best orientation, like this:
""" Conf:[ 6.3896847 -6.5501723] Conf:[ 6.496025 -6.7066655] Conf:[ 5.410366 -5.5474744] Conf:[ 7.092432 -7.3124714] Conf:[ 9.061753 -9.251386] Conf:[ 7.587371 -7.831802] Conf:[ 2.149212 -2.1235662] Conf:[-0.84504336 0.89392436] Conf:[ 4.436549 -4.5268965] Conf:[ 1.2938225 -1.4327605] """
How can I get the score of the final 3D Bounding Box? (0 to 1 value, like in every 2D or 3D object detector)
Thanks in advance.