def detect(self, color_im, depth_im, cfg, camera_intr=None,
               T_camera_world=None, segmask=None):
        """
        Detects all relevant objects in an rgbd image pair using foreground masking.

        Parameters
        ----------
        color_im : :obj:`ColorImage`
            color image for detection
        depth_im : :obj:`DepthImage`
            depth image for detection (corresponds to color image)
        cfg : :obj:`YamlConfig`
            parameters of detection function
        camera_intr : :obj:`CameraIntrinsics`
            intrinsics of the camera
        T_camera_world : :obj:`autolab_core.RigidTransform`
            registration of the camera to world frame
        segmask : :obj:`BinaryImage`
            optional segmask of invalid pixels

        Returns
        ------
        :obj:`list` of :obj:`RgbdDetection`
            all detections in the image
        """
        # read params
        foreground_mask_tolerance = cfg['foreground_mask_tolerance']
        min_contour_area = cfg['min_contour_area']
        max_contour_area = cfg['max_contour_area']
        w = cfg['filter_dim']

        # mask image using background detection
        bgmodel = color_im.background_model()
        binary_im = color_im.foreground_mask(foreground_mask_tolerance, bgmodel=bgmodel)

        # filter the image
        y, x = np.ogrid[-w/2+1:w/2+1, -w/2+1:w/2+1]
        mask = x*x + y*y <= w/2*w/2
        filter_struct = np.zeros([w,w]).astype(np.uint8)
        filter_struct[mask] = 1
        binary_im_filtered = binary_im.apply(snm.grey_closing, structure=filter_struct)

        visualize = False
        if visualize:
            plt.figure()
            plt.imshow(binary_im_filtered.data, cmap=plt.cm.gray)
            plt.axis('off')
            plt.show()

        # find all contours
        contours = binary_im_filtered.find_contours(min_area=min_contour_area, max_area=max_contour_area)

        # convert contours to detections
        detections = []
        for contour in contours:
            box = contour.bounding_box
            color_thumbnail = color_im.crop(box.height, box.width, box.ci, box.cj)
            depth_thumbnail = depth_im.crop(box.height, box.width, box.ci, box.cj)
            binary_thumbnail = binary_im_filtered.crop(box.height, box.width, box.ci, box.cj)
            thumbnail_intr = camera_intr
            if camera_intr is not None:
                thumbnail_intr = camera_intr.crop(box.height, box.width, box.ci, box.cj)
            detections.append(RgbdDetection(color_thumbnail,
                                            depth_thumbnail,
                                            box,
                                            binary_thumbnail=binary_thumbnail,
                                            contour=contour,
                                            camera_intr=thumbnail_intr))
        return detections
def detect ( self , color_im , depth_im , cfg , camera_intr = None , T_camera_world = None , segmask = None ) : foreground_mask_tolerance = cfg [ 'foreground_mask_tolerance' ] min_contour_area = cfg [ 'min_contour_area' ] max_contour_area = cfg [ 'max_contour_area' ] w = cfg [ 'filter_dim' ] bgmodel = color_im . background_model ( ) binary_im = color_im . foreground_mask ( foreground_mask_tolerance , bgmodel = bgmodel ) y , x = np . ogrid [ - w / 2 + 1 : w / 2 + 1 , - w / 2 + 1 : w / 2 + 1 ] mask = x * x + y * y <= w / 2 * w / 2 filter_struct = np . zeros ( [ w , w ] ) . astype ( np . uint8 ) filter_struct [ mask ] = 1 binary_im_filtered = binary_im . apply ( snm . grey_closing , structure = filter_struct ) visualize = False if visualize : plt . figure ( ) plt . imshow ( binary_im_filtered . data , cmap = plt . cm . gray ) plt . axis ( 'off' ) plt . show ( ) contours = binary_im_filtered . find_contours ( min_area = min_contour_area , max_area = max_contour_area ) detections = [ ] for contour in contours : box = contour . bounding_box color_thumbnail = color_im . crop ( box . height , box . width , box . ci , box . cj ) depth_thumbnail = depth_im . crop ( box . height , box . width , box . ci , box . cj ) binary_thumbnail = binary_im_filtered . crop ( box . height , box . width , box . ci , box . cj ) thumbnail_intr = camera_intr if camera_intr is not None : thumbnail_intr = camera_intr . crop ( box . height , box . width , box . ci , box . cj ) detections . append ( RgbdDetection ( color_thumbnail , depth_thumbnail , box , binary_thumbnail = binary_thumbnail , contour = contour , camera_intr = thumbnail_intr ) ) return detections
Detects all relevant objects in an rgbd image pair using foreground masking.

        Parameters
        ----------
        color_im : :obj:`ColorImage`
            color image for detection
        depth_im : :obj:`DepthImage`
            depth image for detection (corresponds to color image)
        cfg : :obj:`YamlConfig`
            parameters of detection function
        camera_intr : :obj:`CameraIntrinsics`
            intrinsics of the camera
        T_camera_world : :obj:`autolab_core.RigidTransform`
            registration of the camera to world frame
        segmask : :obj:`BinaryImage`
            optional segmask of invalid pixels

        Returns
        ------
        :obj:`list` of :obj:`RgbdDetection`
            all detections in the image