encoder decoder.py

def encoder(labels):
    train_labels = np.zeros((labels.shape[0], 10))
    dic = {'Bacterial_spot':0, 'Early_blight':1, 'Late_blight':2, 'Leaf_Mold':3, 'Septoria_leaf_spot':4, 'Spider_mites Two-spotted_spider_mite':5,
          'Target_Spot':6, 'Tomato_Yellow_Leaf_Curl_Virus':7, 'Tomato_mosaic_virus':8, 'healthy':9}
    for i in range(len(labels)):
        train_labels[i, dic[labels[i]]] = 1
    return train_labels

def decoder(labels):
    preds = np.argmax(labels, axis=1)
    test_labels = []
    dic = {0:'Bacterial_spot', 1:'Early_blight', 2:'Late_blight', 3:'Leaf_Mold', 4:'Septoria_leaf_spot', 5:'Spider_mites Two-spotted_spider_mite',
          6:'Target_Spot', 7:'Tomato_Yellow_Leaf_Curl_Virus', 8:'Tomato_mosaic_virus', 9:'healthy'}
    
    for i in preds:
        test_labels.append(dic[i])
    return np.array(test_labels)