def setImageNumpy(self, img): vtkImg = vnp.numpyToImageData(img) self.setImage(vtkImg)
from director import imageview from director import consoleapp import director.vtkAll as vtk import director.vtkNumpy as vnp # create a vtkImageData object s = vtk.vtkRTAnalyticSource() s.SetWholeExtent(-100, 100, -100, 100, 0, 0) s.Update() image = s.GetOutput() # get image data as a numpy array w, h, _ = image.GetDimensions() img = vnp.getNumpyFromVtk(image, 'RTData').reshape(h, w, -1) # show numpy image data view = imageview.ImageView() view.showNumpyImage(img) view.show() # convert back to vtkImageData and show view2 = imageview.ImageView() view2.setImage(vnp.numpyToImageData(img)) view2.show() consoleapp.ConsoleApp.start()
from director import imageview from director import consoleapp import director.vtkAll as vtk import director.vtkNumpy as vnp # create a vtkImageData object s = vtk.vtkRTAnalyticSource() s.SetWholeExtent(-100, 100, -100, 100, 0, 0) s.Update() image = s.GetOutput() # get image data as a numpy array w,h,_ = image.GetDimensions() img = vnp.getNumpyFromVtk(image, 'RTData').reshape(h,w,-1) # show numpy image data view = imageview.ImageView() view.showNumpyImage(img) view.show() # convert back to vtkImageData and show view2 = imageview.ImageView() view2.setImage(vnp.numpyToImageData(img)) view2.show() consoleapp.ConsoleApp.start()
#simulate depth image model_path = "../models/net_depth_seg_v1.hdf5" model = network.load_trained_model(weights_path=model_path) threshold = .5 img_height, img_width = (480, 640) stack = np.zeros((1, img_height, img_width, 1)) vtk_array = scale.GetOutput().GetPointData().GetScalars() im = np.flip(numpy_support.vtk_to_numpy(vtk_array).reshape( img_height, 2 * img_width)[:, :640] / 3500., axis=0) stack[0, :, :, 0] = im predicted_prob_map = model.predict_on_batch(stack) network.apply_mask(predicted_prob_map, depthsim_source, threshold) im_depth_sim_vtk = vnp.numpyToImageData(np.reshape( depthsim_source, (480, 640, 1)), vtktype=vtk.VTK_FLOAT) #simulate real real_depth = misc.imread(depthFile) source_real[real_depth == 0] = 0 real_depth_vtk = vnp.numpyToImageData(np.reshape( source_real, (480, 640, 1)), vtktype=vtk.VTK_FLOAT) #simulate kunis normals = util.ratio_from_normal( util.convert_rgb_normal(misc.imread(normalFile))) source_kuni[normals < .3] = 0 kuni_depth_vtk = vnp.numpyToImageData(np.reshape( source_kuni, (480, 640, 1)),