from sample.model import MyModel
from visualizer import Visualizer
import pickle
import numpy as np
import torch
from imglib.image_io import imshow
img_np = np.random.randint(0, 256, (100, 100, 3)) / 255
img = torch.tensor(img_np)
model = MyModel()
visualizer = Visualizer(model)
visualizer.separate_layers()
visualizer.describe_layers()
output = visualizer.check_output(input("Please input layer name >>> "), img)
output = np.array(output).astype(np.uint8)
print(img_np.shape, output.shape)
# imshow(img_np * 255, "hoge")
# imshow(output * 255, "hoge")
