Prediction

import os
import cv2
import random
import tensorflow as tf
import numpy as np

images = []
for path, subdirs, files in os.walk("C:\\Users\\Krakkus\\Desktop\\flower_images"):
    for name in files:
        fn = os.path.join(path, name)
        images.append(fn)

fn = random.choice(images)
print(fn)

org_img = cv2.imread(fn)
tf_image = cv2.resize(org_img, (224, 224))
tf_image = cv2.cvtColor(tf_image, cv2.COLOR_BGR2RGB)
tf_image = np.expand_dims(tf_image, axis=0)

model = tf.keras.models.load_model('my_model_224.keras')
prediction = model.predict([tf_image])
print(prediction[0])
predicted_class = np.argmax(prediction[0])
print(predicted_class)

cv2.imshow('Image classification', org_img)
cv2.waitKey(0)