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import tensorflow as tf
from fastapi import FastAPI
from PIL import Image
import numpy as np
class BrainTumorDetector:
def __init__(self, model_path):
self.model = tf.keras.models.load_model(model_path)
def predict(self, image: Image.Image):
image = image.resize((128, 128)) # Adjust size as per your model
image_array = np.array(image) / 255.0 # Normalize
image_array = np.expand_dims(image_array, axis=0) # Add batch dimension
predictions = self.model.predict(image_array)
return predictions
# Initialize the model detector (this path will be relative to your model repository)
detector = BrainTumorDetector("Brain_tumor_pred.h5")
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