evaluate_model.py

import os
import tensorflow as tf
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.models import load_model

base_dir = 'data/chest_xray'
val_dir = os.path.join(base_dir, 'val')

val_datagen = ImageDataGenerator(rescale=1./255)
val_generator = val_datagen.flow_from_directory(
    val_dir,
    target_size=(150, 150),
    batch_size=32,
    class_mode='binary'
)

model = load_model('xray_image_classifier_model.keras')

loss, accuracy = model.evaluate(val_generator)
print(f'Validation Loss: {loss:.4f}')
print(f'Validation Accuracy: {accuracy:.4f}')