model.load_state_dict(weights['model'].state_dict()) print("=> model successfully loaded") else: print("=> no model found at '{}'".format(weights_location)) if cuda: model = model.cuda() model.eval() for name in INPORT_LIST: if not name in self.inports: self.addInport(ImageInport(name)) if not "outport" in self.outports: self.addOutport(ImageOutport("outport")) if not "sample" in self.outports: self.addOutport(ImageOutport("sample")) if not "off" in self.properties: self.addProperty( BoolProperty("off", "Off", True)) if not "display_input" in self.properties: self.addProperty( BoolProperty("display_input", "Show Input", True)) if not "sample_num" in self.properties: self.addProperty( IntProperty("sample_num", "Sample Number", 0)
""" Takes in two images from inviwo and outputs the difference between them """ import inviwopy from inviwopy.data import ImageOutport, ImageInport from inviwopy.data import Image import numpy as np INPORT_LIST = ["im_inport1", "im_inport2"] for name in INPORT_LIST: if not name in self.inports: self.addInport(ImageInport(name)) if not "outport" in self.outports: self.addOutport(ImageOutport("outport")) def process(self): im_data = [] for name in INPORT_LIST: im_data.append(self.getInport(name).getData()) if len(im_data) < 2: print("Not enough images input") print("Images input is {} expected {}".format(len(im_data), 2)) return -1 if not (im_data[0].dimensions == im_data[1].dimensions): print("Operation is incompatible with images of different size") print("Size 1: ", im_data[0].dimensions) print("Size 2: ", im_data[1].dimensions) return -1