How to Resolve cv2.detail.SphericalWarper AttributeError in OpenCV Python and Use PyRotationWarper for Spherical Projection

Getting AttributeError: cv2.detail.SphericalWarper in OpenCV Python? Learn why it’s not bound and how to use PyRotationWarper for spherical stitching.

When you set out to implement spherical warping for image stitching in Python and reach for cv2.detail.SphericalWarper, you quickly hit a wall. Even on recent setups like Python 3.11 with opencv-contrib-python 4.12.0.88, the symbol simply isn’t there in the Python API. The result is a predictable AttributeError and a fair bit of confusion, because search results point to a class that does exist in OpenCV—just not in the Python bindings.

The failing path

The following snippet demonstrates the dead end. The class is documented on the C++ side, but calling it from Python raises an attribute error, and simple introspection confirms it isn’t exposed via cv2 or cv2.detail.

import cv2

try:
    cv2.detail.SphericalWarper()
except AttributeError as err:
    print("AttributeError:", err)

print("SphericalWarper" in repr(dir(cv2)))
print("SphericalWarper" in repr(dir(cv2.detail)))

What’s actually going on

OpenCV provides a SphericalWarper class on the C++ side, and its documentation is easy to find. However, that class is not available through OpenCV’s Python bindings. Python exposure in OpenCV requires explicit binding annotations in the C++ source, and while parts of the stitching module are wrapped, this particular class isn’t accessible from Python. That’s why importing or referencing it fails, even though the C++ API exists and is documented.

The way forward in Python is to use PyRotationWarper and request the spherical projection via its type argument. Internally, that projection type is mapped to the spherical warper implementation, so you get the behavior you need without calling SphericalWarper directly. This pattern is also used in OpenCV’s stitching_detailed.py sample and in community code that builds on the stitching module.

The working solution

Instantiate a rotation warper with the spherical projection. Provide a scale (often related to focal length or desired output scale) as the second argument. For example:

import cv2

proj_engine = cv2.PyRotationWarper("spherical", 1000)

This resolves the AttributeError by avoiding the unavailable symbol and using the Python-exposed entry point that maps to the same projection logic.

Why this mismatch exists

The short version is that Python APIs in OpenCV exist only where the C++ code has been explicitly annotated for bindings. Some parts of the stitching module are exposed, but not all classes. If direct access to SphericalWarper in Python is important to your workflow, filing an issue and requesting bindings is the right channel. There is documentation on how Python bindings are created in OpenCV, and depending on the C++ code, adding bindings can be more involved than adding a one-liner.

Context for “warping” in stitching

In image stitching, warping refers to projections that follow well-defined geometric equations, such as spherical projection. This is different from free-form or artistic image warping in photo editing, which does not need to conform to these geometric constraints. When you select "spherical" for the warper type, you are opting into that specific projection model used by stitching pipelines.

Practical pointers

If you want a reference for how the warper is typically initialized in Python, OpenCV’s stitching_detailed.py shows the intended use of the wrappers, and community projects such as OpenStitching/stitching demonstrate the same approach in real codebases. In short, select the warp type as a string, and let PyRotationWarper handle projection selection under the hood.

Takeaways

If you hit AttributeError: module 'cv2.detail' has no attribute 'SphericalWarper' in Python, you are not missing a package or a version. The class exists in C++, but isn’t exposed via Python. Use cv2.PyRotationWarper("spherical", scale) to get spherical projection in stitching tasks, following the same pattern as OpenCV’s own sample code. If direct Python bindings for SphericalWarper are important for your project, consider requesting them upstream.