
import tensorflow.keras
from PIL import Image, ImageOps
import numpy as np

#TESTING PROGRAM
"""
# Disable scientific notation for clarity
np.set_printoptions(suppress=True)

# Load the model
model = tensorflow.keras.models.load_model('keras_model.h5')

# Create the array of the right shape to feed into the keras model
# The 'length' or number of images you can put into the array is
# determined by the first position in the shape tuple, in this case 1.
data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)

# Replace this with the path to your image
image = Image.open('dog.jpg')

#resize the image to a 224x224 with the same strategy as in TM2:
#resizing the image to be at least 224x224 and then cropping from the center
size = (224, 224)
image = ImageOps.fit(image, size, Image.ANTIALIAS)

#turn the image into a numpy array
image_array = np.asarray(image)

# display the resized image
image.show()

# Normalize the image
normalized_image_array = (image_array.astype(np.float32) / 127.0) - 1

# Load the image into the array
data[0] = normalized_image_array

# run the inference
prediction = model.predict(data)
#[[0. 1. 0.]]
predictionList = list(str(prediction[0]))
print(predictionList)
#['[''0''.'' ''1''.'' ''0''.'']']
cat = predictionList[1]
dog = predictionList[4]
other = predictionList[7]
print(cat)
print(dog)
print(other)
"""

def CatDetector(imageLink):
    np.set_printoptions(suppress=True)
    model = tensorflow.keras.models.load_model('keras_model.h5')
    data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)
    image = Image.open(imageLink)
    size = (224, 224)
    image = ImageOps.fit(image, size, Image.ANTIALIAS)
    image_array = np.asarray(image)
    normalized_image_array = (image_array.astype(np.float32) / 127.0) - 1
    data[0] = normalized_image_array
    prediction = model.predict(data)
    #[[0. 1. 0.]]
    predictionList = list(str(prediction[0]))
    print(predictionList)
    #['[''0''.'' ''1''.'' ''0''.'']']
    cat = predictionList[1]
    dog = predictionList[4]
    other = predictionList[7]
    if  cat >= dog:
        return "https://preview.redd.it/ocak23sxji151.jpg?auto=webp&s=388f8d7a61d99d4c59d39d90e633259667997d9a"
    elif dog >= other:
        return ""
    else:
        return ""


    print(cat)
    print(dog)
    print(other)


