model.py

model.py

@@ -1,20 +0,0 @@
-from keras.models import load_model
-import numpy as np
-
-labels = ['Chalky Soil', 'Mary Soil', 'Sand', 'Slit SOil', 'Alluvial Soil', 'Black Soil', 'Clay Soil', 'Red Soil']
-MODEL_PATH = r"DenseNet121v2_95.h5"
-
-def load_CNN_model():
-    model = load_model(MODEL_PATH)
-    print("model loaded")
-    return model
-
-def classify_image(img):
-    model = load_CNN_model()
-    prediction = model.predict(img)
-    predicted_class = np.argmax(prediction)
-
-    predicted_label = labels[predicted_class]
-    accuracy = prediction[0][predicted_class]
-
-    return predicted_label, accuracy