def classify(image: PILImage, learner: Learner) -> Tuple[AnimalType, float]: with learner.no_bar(): results = learner.predict(image) _, category, probabilities = results is_a_cat = category == 1 animal_type = AnimalType.cat if is_a_cat else AnimalType.dog percent = np.round(100 * probabilities) return animal_type, percent[category]
def predict(pdf_tiles: list, learner: Learner): # Get predicted labels and confidences for the given image tiles predictions = [learner.predict(tile) for tile in pdf_tiles] labels = [prediction[0] for prediction in predictions] confidences = [ float(prediction[2][prediction[1]].numpy()) for prediction in predictions ] return labels, confidences