Testing

random_test.py

# Import OpenCV
import cv2
# Utility
import itertools
import random
from collections import Counter
from glob import iglob
def load_image(filename):
    img = cv2.imread(os.path.join(data_dir, validation_dir, filename))
    img = cv2.resize(img, (IMAGE_SIZE[0], IMAGE_SIZE[1]) )
    img = img /255
    
    return img
def predict(image):
    probabilities = model.predict(np.asarray([img]))[0]
    class_idx = np.argmax(probabilities)
    
    return {classes[class_idx]: probabilities[class_idx]}
for idx, filename in enumerate(random.sample(validation_generator.filenames, 5)):
    print("SOURCE: class: %s, file: %s" % (os.path.split(filename)[0], filename))
    
    img = load_image(filename)
    prediction = predict(img)
    print("PREDICTED: class: %s, confidence: %f" % (list(prediction.keys())[0], list(prediction.values())[0]))
    plt.imshow(img)
    plt.figure(idx)    
    plt.show()