Bad results when undistorting points using OpenCV in Python

Question

I'm having trouble undistorting points on an image taken with a calibrated camera using the Python bindings for OpenCV. The undistorted points have entirely different coordinates than the original points detected in the image. Here's the offending call: ``` undistorted = cv2.undistortPoints(image_points, camera_matrix, distortion_coefficients) ``` where `image_points` is a numpy array of detected chessboard corners returned by `cv2.findChessboardCorners` and reshaped to match the dimensional requirements of `cv2.undistortPoints`, and `camera_matrix` and `distortion_coefficients` were returned by `cv2.calibrateCamera`. `camera_matrix` and `distortion_coefficients` seem to me to be okay, and so do `image_points`. Nevertheless, `distorted` seems to have no relationship to `image_points`. Here's a summary of the values: ``` >>> image_points array([[[ 186.95303345, 163.25502014]], [[ 209.54478455, 164.62690735]], [[ 232.26443481, 166.10734558]], ..., [[ 339.03695679, 385.97784424]], [[ 339…

Accepted Answer

I think you forgot to specify the new camera matrix in your call to `undistortPoints`. If you look at the documentation of the function, it says that the signature is:

```
Python: cv.UndistortPoints(src, dst, cameraMatrix, distCoeffs, R=None, P=None) → None
```

where `dst` is the array of points after undistortion and "if `P` is identity or omitted, then it contains normalized point coordinates", meaning before projection in the image using the calibration matrix.

The function should do what you expect if you set `P` to your `cameraMatrix`.

Bad results when undistorting points using OpenCV in Python

Solution

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