import tensorflow as tf
from pathlib import Path
import numpy as np
from PIL import Image

model_path = 'saved_model_age_regressor'
img_path = Path('data/UTKFace/53_1_1_20170110122449716.jpg.chip.jpg')
print('Model path:', model_path, flush=True)
print('Image path:', img_path, flush=True)

m = tf.keras.models.load_model(model_path, compile=False)
print('Loaded model type:', type(m), flush=True)
try:
    m.summary()
except Exception as e:
    print('model.summary failed:', e, flush=True)

img = Image.open(img_path).convert('RGB').resize((224,224))
arr = np.array(img, dtype=np.float32)/255.0
x = np.expand_dims(arr, 0)
print('Input shape:', x.shape, flush=True)
pred = m.predict(x)
print('Raw prediction output:', pred, 'shape:', getattr(pred, 'shape', None), flush=True)
try:
    print('Predicted age:', float(pred.flatten()[0]), flush=True)
except Exception as e:
    print('Error converting prediction to float:', e, flush=True)