Keras/Tensorflow: model.predict() returns a list. How do I match the output with my class names? I have a CNN built in Keras. I have saved it and am now using the model.predict() function to make predictions from it. Whenever I run the following code,
def prediction(path):
    import keras
    from keras.preprocessing.image import load_img, img_to_array 
    from keras.models import load_model
    import PIL
    import numpy as np
    
    img = load_img(path)
    img = img.resize((224, 224))
    img = img_to_array(img) 

    img = img.reshape( -1,224, 224,3)

    model = load_model('model1.h5')
    pred = model.predict(img)

    return pred

print(prediction('/path/to/image/')

I get an output like this:
[[7.578206e-37 1.000000e+00 0.000000e+00 0.000000e+00]]
I am doing transfer learning using resnet50 with imagenet weights and here is the model.summary().
I have 4 classes. How do I find out where each prediction belongs?
I have looked here as well but it doesn't seem to help me.
Thanks
Model prediction output is a bunch of probabilities. In order to get category name you need use following snippet. It calculates the argmax of predicions and give it to CLASSES list:
print(CLASSES[np.argmax(predictions)])