Add docstring to the transform module (#6797)

Co-authored-by: Marianne Corvellec <marianne.corvellec@ens-lyon.org>
Co-authored-by: Lars Grüter <lagru+github@mailbox.org>

skimage/transform/__init__.py

@@ -1,3 +1,37 @@
+"""This module includes tools to transform images and volumetric data.
+
+- Geometric transformation:
+  These transforms change the shape or position of an image.
+  They are useful for tasks such as image registration,
+  alignment, and geometric correction.
+  Examples: :class:`~skimage.transform.AffineTransform`,
+  :class:`~skimage.transform.ProjectiveTransform`,
+  :class:`~skimage.transform.EuclideanTransform`.
+
+- Image resizing and rescaling:
+  These transforms change the size or resolution of an image.
+  They are useful for tasks such as down-sampling an image to
+  reduce its size or up-sampling an image to increase its resolution.
+  Examples: :func:`~skimage.transform.resize`,
+  :func:`~skimage.transform.rescale`.
+
+- Feature detection and extraction:
+  These transforms identify and extract specific features or
+  patterns in an image. They are useful for tasks such as object
+  detection, image segmentation, and  feature matching.
+  Examples: :func:`~skimage.transform.hough_circle`,
+  :func:`~skimage.transform.pyramid_expand`,
+  :func:`~skimage.transform.radon`.
+
+- Image transformation:
+  These transforms change the appearance of an image without changing its
+  content. They are useful for tasks such a creating image mosaics,
+  applying artistic effects, and visualizing image data.
+  Examples: :func:`~skimage.transform.warp`,
+  :func:`~skimage.transform.iradon`.
+
+"""
+
 from .hough_transform import (hough_line, hough_line_peaks,
                               probabilistic_hough_line, hough_circle,
                               hough_circle_peaks, hough_ellipse)