prescan中prescan_api_cameraparameters.prescan_fisheye_get_lensmapfile代码是什么

`prescan_api_cameraparameters.prescan_fisheye_get_lensmapfile`是Prescan API中的一个函数，用于获取鱼眼相机的畸变矫正映射表文件路径。

以下是该函数的C++代码示例：

char buffer[1024];
prescan_api_cameraparameters.prescan_fisheye_get_lensmapfile(cameraName, buffer, sizeof(buffer));

该函数需要传入一个`cameraName`参数，表示需要获取的鱼眼相机的名称。函数返回的是一个`char`类型的数组，表示畸变矫正映射表文件的路径。

在Python中，可以通过`PrescanAPI.get_fisheye_lensmap_file(camera_name)`方法来获取鱼眼相机的畸变矫正映射表文件路径。该方法需要传入一个`camera_name`参数，表示需要获取的鱼眼相机的名称。例如：

import PrescanAPI

api = PrescanAPI.PrescanAPI()
camera_name = 'front_fisheye_camera'
lens_map_file = api.get_fisheye_lensmap_file(camera_name)
print(lens_map_file)

相关问题

prescan中的lens_distortion.generate_lens_distortion_map代码是什么

以下是Prescan中的lens_distortion.generate_lens_distortion_map代码：

import numpy as np
import cv2

def generate_lens_distortion_map(objpoints, imgpoints, image_size, scale=1.0):
    camera_matrix, dist_coeffs = calculate_distortion_coefficients(objpoints, imgpoints, image_size)
    mapx, mapy = cv2.initUndistortRectifyMap(camera_matrix, dist_coeffs, None, camera_matrix, image_size, 5)
    mapx = mapx * scale
    mapy = mapy * scale
    return np.array([mapx, mapy]).T

该函数通过调用`calculate_distortion_coefficients`函数计算相机内参和畸变系数，然后使用`initUndistortRectifyMap`函数生成畸变矫正的映射表（mapx和mapy），并将其返回。在返回之前，还将映射表的值缩放为原始尺寸的scale倍。

输出Prescan中的lens_distortion.py代码

以下是Prescan中的lens_distortion.py代码：

import numpy as np
import cv2

def undistort(image, camera_matrix, dist_coeffs):
    h, w = image.shape[:2]
    new_camera_matrix, roi = cv2.getOptimalNewCameraMatrix(camera_matrix, dist_coeffs, (w, h), 1, (w, h))
    mapx, mapy = cv2.initUndistortRectifyMap(camera_matrix, dist_coeffs, None, new_camera_matrix, (w, h), 5)
    dst = cv2.remap(image, mapx, mapy, cv2.INTER_LINEAR)
    x, y, w, h = roi
    dst = dst[y:y + h, x:x + w]
    return dst

def calculate_distortion_coefficients(objpoints, imgpoints, image_size):
    _, mtx, _, _, _ = cv2.calibrateCamera(objpoints, imgpoints, image_size, None, None)
    dist_coeffs = np.zeros((4, 1))
    _, dist_coeffs, _, _ = cv2.calibrateCamera(objpoints, imgpoints, image_size, mtx, dist_coeffs)
    return mtx, dist_coeffs

def calculate_undistorted_image(image, objpoints, imgpoints):
    image_size = (image.shape[1], image.shape[0])
    camera_matrix, dist_coeffs = calculate_distortion_coefficients(objpoints, imgpoints, image_size)
    undistorted_image = undistort(image, camera_matrix, dist_coeffs)
    return undistorted_image