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
