def get_prediction(image, info, display=True):
'''
predict on the model and return the prediction containing masks and bounding boxes.
'''
vis = Visualizer()
info["transforms"] = build_transforms(info["cfg"],
min_image_size=min(image.shape[:-1]),
max_image_size=max(image.shape[:-1]))
prediction = vis.compute_prediction(info["cfg"], image, info["transforms"],
info["device"], info["model"],
info["cpu_device"], info["masker"])
prediction = vis.select_top_predictions(prediction,
info["confidence_threshold"])
print(prediction)
if display:
vis.display_instances(image[:, :, ::-1],
prediction.bbox,
prediction.get_field("mask"),
prediction.get_field("labels"),
info["CATEGORIES"],
prediction.get_field("scores"),
show_mask=False)
return prediction
