def example_test(model,
images_dir="./data/images",
annotations_dir="./data/annotations",
demo_dir="./examples",
name="example01.png"):
if not (os.path.exists(demo_dir)):
os.mkdir(demo_dir)
dataset = Dataset(training=False,
images_dir=images_dir,
annotations_dir=annotations_dir)
image_name = np.random.choice(dataset.get_images_list())
image_path = os.path.join(images_dir, image_name + ".jpg")
mask_path = os.path.join(annotations_dir, "trimaps", image_name + ".png")
orig_img = cv2.imread(image_path)[..., ::-1]
true_mask = (cv2.imread(mask_path) * 100)[..., ::-1]
pred_mask = process(image_path, model)
labels = ["Original Image", "True Mask", "Predicted Mask"]
collection = [orig_img, true_mask, pred_mask]
creat_example(collection, labels, demo_dir, name, 3)
