This: -added trained model for 2 crops -added way to choose which model should we use
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model_2_crops.pth
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model_2_crops.pth
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@ -9,12 +9,14 @@ from PIL import Image
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import random
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imageSize = (128, 128)
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labels = ['carrot','corn', 'potato', 'tomato'] # musi być w kolejności alfabetycznej
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labels = ['carrot','corn', 'potato', 'tomato'] # musi być w kolejności alfabetycznej
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fertilizer = {labels[0]: 'kompost', labels[1]: 'saletra amonowa', labels[2]: 'superfosfat', labels[3]:'obornik kurzy'}
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#labels = ['corn','tomato'] #uncomment this two lines for 2 crops only
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#fertilizer = {labels[0]: 'kompost', labels[1]: 'saletra amonowa'}
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torch.manual_seed(42)
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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#device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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device = torch.device("cpu")
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# device = torch.device("mps") if torch.backends.mps.is_available() else torch.device('cpu')
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# print(device)
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