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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}')
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