def test_to_from_bytes(image): net = Network.load('tiny-yolo') data = net.to_bytes() results = net(image) loaded = Network().from_bytes(data) results2 = net(image) assert results == results2
def test_evaluate(image, box_labels): net = Network.load("tiny-yolo") acc = net.evaluate([image], [box_labels]) assert 'fp' in acc assert 'fn' in acc assert 'tp' in acc assert 'r' in acc assert 'p' in acc assert 'f' in acc
def test_update(image, box_labels): net = Network.load("tiny-yolo") for i in range(10): loss = net.update([image], [box_labels]) print(loss)
def test_detection_data(image, box_labels): net = Network.load("tiny-yolo") data = DetectionData([image], [box_labels], net.width, net.height, net.max_boxes, net.num_classes)
def test_detect(image): net = Network.load("tiny-yolo") result = net(image)
def test_load(): net = Network.load("tiny-yolo")
def test_init(): nn = Network()
def test_from_disk(image): net = Network().from_disk(Path('lightnet/data/tiny-yolo').resolve()) results = net(image) assert results is not None