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