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/legacy/detection/utils/box_utils.py:540
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 + 1.0
w = xmax - xmin + 1.0
yc = ymin + 0.5 * hView on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/legacy/detection/utils/box_utils.py:540 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/a5bcdac98cc5827f.
Report an issue: GitHub.