import cv2
import os
import tensorflow as tf


model1 = tf.keras.models.load_model('VDSR.keras', custom_objects={'VDSR': VDSR}) # load each model

directory='Unreadable Scanned QR Codes'
readable=0
unreadable=0
for filename in os.listdir(directory):
    file_path = os.path.join(directory, filename)
    if os.path.isfile(file_path):
        test_image = cv2.imread(file_path,cv2.IMREAD_GRAYSCALE) 
        test_image = test_image.astype('float32') / 255.0
        test_image = np.expand_dims(test_image, axis=-1)  # (224, 224) -> (224, 224, 1)
        test_image = np.expand_dims(test_image, axis=0)
        
        # Predict
        predicted_image = model1.predict(test_image,verbose=0)
        predicted_image = np.clip(predicted_image[0], 0, 1)  # Sonucu 0-1 arası değerlere çek 
        predicted_image_uint8 = (predicted_image * 255).astype(np.uint8)
        detector = cv2.QRCodeDetector()
        try:
            data, points, _ = detector.detectAndDecode(predicted_image_uint8) 
            if data:
                readable=readable+1
            else:
                unreadable=unreadable+1
        except:
            unreadable=unreadable+1
        
    if okunmayan>0:
        print(readable,okunmayan, (readable/(unreadable+readable))*100) # Print score