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import numpy as np |
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from tensorflow.keras.models import load_model |
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from tensorflow.keras.preprocessing import image |
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import os |
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class Prediction: |
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def __init__(self,filename): |
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self.filename =filename |
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def predict(self): |
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model = load_model("model.h5") |
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imagename = self.filename |
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test_image = image.load_img(imagename, target_size = (224,224)) |
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test_image = image.img_to_array(test_image) |
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test_image = np.expand_dims(test_image, axis = 0) |
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result = np.argmax(model.predict(test_image), axis=1) |
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print(result) |
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if result[0] == 1: |
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prediction = 'Healthy' |
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else: |
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prediction = 'Coccidiosis' |
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return prediction |
