def draw_instance_groundtruth(self, img_rgb, groundtruth):
visual = Visualizer(img_rgb, self.metadata, self.scale,
self.instance_mode)
instance = Instances(
image_size=groundtruth.image_size,
pred_boxes=groundtruth.gt_boxes,
pred_classes=groundtruth.gt_classes,
)
if groundtruth.has('gt_keypoints'):
instance.pred_keypoints = groundtruth.gt_keypoints
vis_img = visual.draw_instance_predictions(instance)
return vis_img.get_image()
def draw_instance_predictions(self, img_rgb, predictions, num_instance=20):
processed_results = self.postprocess(predictions, img_rgb.shape[0],
img_rgb.shape[1])
visual = Visualizer(img_rgb, self.metadata, self.scale,
self.instance_mode)
instance = Instances(
image_size=processed_results.image_size,
pred_boxes=processed_results.pred_boxes.tensor.detach().cpu(
).numpy()[:num_instance],
scores=processed_results.scores.detach().cpu().numpy()
[:num_instance],
pred_classes=processed_results.pred_classes.detach().cpu().int(
).numpy()[:num_instance],
)
if processed_results.has('pred_keypoints'):
instance.pred_keypoints = processed_results.pred_keypoints.detach(
).cpu().numpy()[:num_instance]
vis_img = visual.draw_instance_predictions(instance)
return vis_img.get_image()