tensorflow/models · error · ValueError

boxes.shape[1] is {:d}, but must be 4.

Error message

boxes.shape[1] is {:d}, but must be 4.

What it means

Error "boxes.shape[1] is {:d}, but must be 4." thrown in tensorflow/models.

Source

Thrown at official/vision/ops/box_ops.py:469

    boxes: a tensor whose last dimension is 4 representing the coordinates of
      boxes in ymin, xmin, ymax, xmax order.
    scores: a tensor whose shape is the same as tf.shape(boxes)[:-1]
      representing the original scores of the boxes.
    image_shape: a tensor whose shape is the same as, or `broadcastable` to
      `boxes` except the last dimension, which is 2, representing [height,
      width] of the scaled image.
    min_size_threshold: a float representing the minimal box size in each side
      (w.r.t. the scaled image). Boxes whose sides are smaller than it will be
      filtered out.

  Returns:
    filtered_boxes: a tensor whose shape is the same as `boxes` but with
      the position of the filtered boxes are filled with 0.
    filtered_scores: a tensor whose shape is the same as 'scores' but with
      the positinon of the filtered boxes filled with 0.
  """
  if boxes.shape[-1] != 4:
    raise ValueError(
        'boxes.shape[1] is {:d}, but must be 4.'.format(boxes.shape[-1]))

  with tf.name_scope('filter_boxes'):
    if isinstance(image_shape, list) or isinstance(image_shape, tuple):
      height, width = image_shape
    else:
      image_shape = tf.cast(image_shape, dtype=boxes.dtype)
      height = image_shape[..., 0]
      width = image_shape[..., 1]

    ymin = boxes[..., 0]
    xmin = boxes[..., 1]
    ymax = boxes[..., 2]
    xmax = boxes[..., 3]

    h = ymax - ymin
    w = xmax - xmin
    yc = ymin + 0.5 * h

View on GitHub (pinned to e006f5f0d5)

Solutions

1. Pass boxes with shape [batch, 4, ...] as required (dimension 1 must be 4).
2. Transpose or reshape the box tensor so axis 1 holds the 4 coordinates.

When it happens

Trigger: Thrown at official/vision/ops/box_ops.py:469 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24). Data as JSON: /api/errors/1c2851c24fbab96e. Report an issue: GitHub.