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- from model import ModelCT
- from matplotlib import pyplot as plt
- import numpy as np
- import torch
- import os
- device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
- model_folder = "trained_models/testrun123" # mapa naucenega modela
- model = ModelCT()
- model.to(device)
- model.load_state_dict(torch.load(os.path.join(model_folder, "trained_model_weights.pth")))
- model.eval()
- # Nalozimo npr. filtre iz prve konvolucijske plasti backbone.conv1
- weights = model.backbone.conv1.weight.data.cpu().numpy()
- # weights.shape = (64,1,7,7) -> 64 filtrov, z 1 kanalom, velikosti 7x7
- # Vizualizacija 21. filtra iz prve plasti (backbone.conv1)
- plt.imshow(weights[20,0,:,:], cmap='gray')
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