如何从源代码查看opencv方法中的枚举数?
How to view enumerator in opencv methods from source code?
想在OpenCV的源码中查找某个方法的关键字参数的枚举类型常量-python。例如,cv2 中的“插值”。 resize()在官网点击“interpolationflags”可以很容易找到,但是源码中好像找不到“interpolationflags”
enum InterpolationFlags{
/** nearest neighbor interpolation */
INTER_NEAREST = 0,
/** bilinear interpolation */
INTER_LINEAR = 1,
/** bicubic interpolation */
INTER_CUBIC = 2,
/* resampling using pixel area relation. It may be a preferred method for image decimation, as it gives moire-free results. But when the image is zoomed, it is similar to the INTER_NEAREST method. */
INTER_AREA = 3,
/** Lanczos interpolation over 8x8 neighborhood */
INTER_LANCZOS4 = 4,
/** Bit exact bilinear interpolation */
INTER_LINEAR_EXACT = 5,
/** Bit exact nearest neighbor interpolation. This will produce same results as
the nearest neighbor method in PIL, scikit-image or Matlab. */
INTER_NEAREST_EXACT = 6,
/** mask for interpolation codes */
INTER_MAX = 7,
/** flag, fills all of the destination image pixels. If some of them correspond to outliers in the
source image, they are set to zero */
WARP_FILL_OUTLIERS = 8,
/** flag, inverse transformation
For example, #linearPolar or #logPolar transforms:
- flag is __not__ set: \f$dst( \rho , \phi ) = src(x,y)\f$
- flag is set: \f$dst(x,y) = src( \rho , \phi )\f$
*/
WARP_INVERSE_MAP = 16
};
想在OpenCV的源码中查找某个方法的关键字参数的枚举类型常量-python。例如,cv2 中的“插值”。 resize()在官网点击“interpolationflags”可以很容易找到,但是源码中好像找不到“interpolationflags”
enum InterpolationFlags{
/** nearest neighbor interpolation */
INTER_NEAREST = 0,
/** bilinear interpolation */
INTER_LINEAR = 1,
/** bicubic interpolation */
INTER_CUBIC = 2,
/* resampling using pixel area relation. It may be a preferred method for image decimation, as it gives moire-free results. But when the image is zoomed, it is similar to the INTER_NEAREST method. */
INTER_AREA = 3,
/** Lanczos interpolation over 8x8 neighborhood */
INTER_LANCZOS4 = 4,
/** Bit exact bilinear interpolation */
INTER_LINEAR_EXACT = 5,
/** Bit exact nearest neighbor interpolation. This will produce same results as
the nearest neighbor method in PIL, scikit-image or Matlab. */
INTER_NEAREST_EXACT = 6,
/** mask for interpolation codes */
INTER_MAX = 7,
/** flag, fills all of the destination image pixels. If some of them correspond to outliers in the
source image, they are set to zero */
WARP_FILL_OUTLIERS = 8,
/** flag, inverse transformation
For example, #linearPolar or #logPolar transforms:
- flag is __not__ set: \f$dst( \rho , \phi ) = src(x,y)\f$
- flag is set: \f$dst(x,y) = src( \rho , \phi )\f$
*/
WARP_INVERSE_MAP = 16
};