コード例 #1
0
    def update_mask(self):
        """
        Regenerate the masks for MaskRCNN and free-hand added (in case they are changed), and show in imageview.
        
        !!!ISSUE: getLocalHandlePositions: moving handles changes the position read out, dragging roi as a whole doesn't.
        """

        # Binary mask from ML detection
        if len(self.selected_ML_Index) > 0:
            # Delete items in dictionary that are not roi items
            roi_dict = self.selected_cells_infor_dict.copy()
            del_key_list = []
            for key in roi_dict:
                print(key)
                if 'ROIitem' not in key:
                    del_key_list.append(key)
            for key in del_key_list:
                del roi_dict[key]

            self.MLmask = ProcessImage.ROIitem2Mask(
                roi_dict,
                mask_resolution=(self.MLtargetedImg.shape[0],
                                 self.MLtargetedImg.shape[1]))
        # Binary mask of added rois
        self.addedROIitemMask = ProcessImage.ROIitem2Mask(
            self.roi_list_freehandl_added,
            mask_resolution=(self.MLtargetedImg.shape[0],
                             self.MLtargetedImg.shape[1]))

        self.intergrate_into_final_mask()
コード例 #2
0
    def intergrate_into_final_mask(self):
        # Binary mask of added rois
        self.addedROIitemMask = ProcessImage.ROIitem2Mask(
            self.roi_list_freehandl_added,
            mask_resolution=(self.MLtargetedImg.shape[0],
                             self.MLtargetedImg.shape[1]))
        #Display the RGB mask, ML mask plus free-hand added.
        self.Mask_edit_viewItem.setImage(gray2rgb(self.addedROIitemMask) * self.mask_color_multiplier + \
                                         gray2rgb(self.MLmask) * self.mask_color_multiplier + gray2rgb(self.MLtargetedImg))

        self.final_mask = self.MLmask + self.addedROIitemMask

        # In case the input image is 2048*2048, and it is resized to fit in MaskRCNN, need to convert back to original size for DMD tranformation.
        if self.final_mask.shape[0] != self.Rawimage.shape[
                0] or self.final_mask.shape[1] != self.Rawimage.shape[1]:
            self.final_mask = resize(
                self.final_mask,
                [self.Rawimage.shape[0], self.Rawimage.shape[1]],
                preserve_range=True).astype(self.final_mask.dtype)
#        self.final_mask = np.where(self.final_mask <= 1, self.final_mask, int(1))

        plt.figure()
        plt.imshow(self.final_mask)
        plt.show()