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import tensorflow as tf
from fastapi import UploadFile
import numpy as np
from PIL import Image
from io import BytesIO
# Load your pre-trained model
MODEL_PATH = "./projects/DL_CatDog/model_catdog1.h5"
model_DL_CatDog = tf.keras.models.load_model(MODEL_PATH)
# Helper function to read and convert the uploaded image
def read_image(file: UploadFile) -> Image.Image:
image = Image.open(BytesIO(file.file.read())).convert('RGB')
return image
# Helper function to preprocess the image
def preprocess_image(image: Image.Image):
image = image.resize((128, 128)) # Adjust to the size expected by your model
image = np.array(image) / 255.0 # Normalize the image
image = np.expand_dims(image, axis=0) # Add batch dimension
return image
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