--- Inspecting models/sam2_encoder.onnx ---
Inputs:
  Name: pixel_values, Shape: ['batch_size', 3, 1024, 1024], Type: tensor(float)
Outputs:
  Name: image_embeddings.0, Shape: ['batch_size', 32, 256, 256], Type: tensor(float)
  Name: image_embeddings.1, Shape: ['batch_size', 64, 128, 128], Type: tensor(float)
  Name: image_embeddings.2, Shape: ['batch_size', 'Reshapeimage_embeddings.2_dim_1', 'Reshapeimage_embeddings.2_dim_2', 'Reshapeimage_embeddings.2_dim_3'], Type: tensor(float)

--- Inspecting models/sam2_decoder.onnx ---
Inputs:
  Name: input_points, Shape: ['batch_size', 1, 'num_points_per_image', 2], Type: tensor(float)
  Name: input_labels, Shape: ['batch_size', 1, 'num_points_per_image'], Type: tensor(int64)
  Name: input_boxes, Shape: ['batch_size', 'num_boxes_per_image', 4], Type: tensor(float)
  Name: image_embeddings.0, Shape: ['batch_size', 32, 256, 256], Type: tensor(float)
  Name: image_embeddings.1, Shape: ['batch_size', 64, 128, 128], Type: tensor(float)
  Name: image_embeddings.2, Shape: ['batch_size', 256, 64, 64], Type: tensor(float)
Outputs:
  Name: iou_scores, Shape: ['batch_size', 'num_boxes_or_points', 3], Type: tensor(float)
  Name: pred_masks, Shape: ['batch_size', 'num_boxes_or_points', 'num_masks', 'Slicepred_masks_dim_3', 'Slicepred_masks_dim_4'], Type: tensor(float)
  Name: object_score_logits, Shape: ['batch_size', 'num_boxes_or_points', 1], Type: tensor(float)