keras-team/keras · error · ValueError
start_points and end_points must have the same shape. Receiv
Error message
start_points and end_points must have the same shape. Received start_points.shape={start_points.shape}, end_points.shape={end_points.shape} What it means
Error "start_points and end_points must have the same shape. Received start_points.shape={start_points.shape}, end_points.shape={end_points.shape}" thrown in keras-team/keras.
Source
Thrown at keras/src/backend/tensorflow/image.py:441
"or rank 4 (batch of images). Received input with shape: "
f"images.shape={images.shape}"
)
if start_points.shape.rank not in (2, 3) or start_points.shape[-2:] != (
4,
2,
):
raise ValueError(
"Invalid start_points shape: expected (4,2) for a single image"
f" or (N,4,2) for a batch. Received shape: {start_points.shape}"
)
if end_points.shape.rank not in (2, 3) or end_points.shape[-2:] != (4, 2):
raise ValueError(
"Invalid end_points shape: expected (4,2) for a single image"
f" or (N,4,2) for a batch. Received shape: {end_points.shape}"
)
if start_points.shape != end_points.shape:
raise ValueError(
"start_points and end_points must have the same shape."
f" Received start_points.shape={start_points.shape}, "
f"end_points.shape={end_points.shape}"
)
need_squeeze = False
if len(images.shape) == 3:
images = tf.expand_dims(images, axis=0)
need_squeeze = True
if len(start_points.shape) == 2:
start_points = tf.expand_dims(start_points, axis=0)
if len(end_points.shape) == 2:
end_points = tf.expand_dims(end_points, axis=0)
if data_format == "channels_first":
images = tf.transpose(images, (0, 2, 3, 1))
View on GitHub (pinned to 7a34a03db6)
When it happens
Trigger: Thrown at keras/src/backend/tensorflow/image.py:441 when the library encounters an invalid state.
Common situations: See trigger scenarios.
AI-assisted analysis of keras-team/keras@7a34a03db6 (2026-08-25).
Data as JSON: /api/errors/51d59054edf2dcb3.
Report an issue: GitHub.