| 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((224, 224)) # 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") | |