pokazuje zdjecie o jakie pytasz
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@ -6,6 +6,7 @@ from neural_network import NeuralNetwork
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from torchvision.io import read_image, ImageReadMode
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import torch.nn as nn
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from torch.optim import Adam
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import matplotlib.pyplot as plt
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CNN = NeuralNetwork().to(device)
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@ -64,8 +65,11 @@ def check_accuracy(loader):
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print(f"Got {num_correct}/{num_samples} with accuracy {float(num_correct)/float(num_samples)*100:.2f}")
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def what_is_it(img_path):
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def what_is_it(img_path, show_img=False):
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image = read_image(img_path, mode=ImageReadMode.RGB)
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if show_img:
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plt.imshow(plt.imread(img_path))
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plt.show()
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image = setup_photos(image).unsqueeze(0)
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model = NeuralNetwork()
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@ -79,4 +83,4 @@ def what_is_it(img_path):
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return id_to_class[idx]
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print(what_is_it('./data/test/water/water.png'))
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print(what_is_it('./data/test/sand/sand.png', True))
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