|
import cv2 |
|
import numpy as np |
|
|
|
|
|
|
|
|
|
|
|
def get_perspective(img, FOV, THETA, PHI, height, width): |
|
|
|
|
|
|
|
[orig_width, orig_height, _] = img.shape |
|
equ_h = orig_height |
|
equ_w = orig_width |
|
equ_cx = (equ_w - 1) / 2.0 |
|
equ_cy = (equ_h - 1) / 2.0 |
|
|
|
wFOV = FOV |
|
hFOV = float(height) / width * wFOV |
|
|
|
w_len = np.tan(np.radians(wFOV / 2.0)) |
|
h_len = np.tan(np.radians(hFOV / 2.0)) |
|
|
|
x_map = np.ones([height, width], np.float32) |
|
y_map = np.tile(np.linspace(-w_len, w_len, width), [height, 1]) |
|
z_map = -np.tile(np.linspace(-h_len, h_len, height), [width, 1]).T |
|
|
|
D = np.sqrt(x_map**2 + y_map**2 + z_map**2) |
|
xyz = np.stack((x_map, y_map, z_map), axis=2) / np.repeat( |
|
D[:, :, np.newaxis], 3, axis=2 |
|
) |
|
|
|
y_axis = np.array([0.0, 1.0, 0.0], np.float32) |
|
z_axis = np.array([0.0, 0.0, 1.0], np.float32) |
|
[R1, _] = cv2.Rodrigues(z_axis * np.radians(THETA)) |
|
[R2, _] = cv2.Rodrigues(np.dot(R1, y_axis) * np.radians(-PHI)) |
|
|
|
xyz = xyz.reshape([height * width, 3]).T |
|
xyz = np.dot(R1, xyz) |
|
xyz = np.dot(R2, xyz).T |
|
lat = np.arcsin(xyz[:, 2]) |
|
lon = np.arctan2(xyz[:, 1], xyz[:, 0]) |
|
|
|
lon = lon.reshape([height, width]) / np.pi * 180 |
|
lat = -lat.reshape([height, width]) / np.pi * 180 |
|
|
|
lon = lon / 180 * equ_cx + equ_cx |
|
lat = lat / 90 * equ_cy + equ_cy |
|
|
|
persp = cv2.remap( |
|
img, |
|
lon.astype(np.float32), |
|
lat.astype(np.float32), |
|
cv2.INTER_CUBIC, |
|
borderMode=cv2.BORDER_WRAP, |
|
) |
|
return persp |
|
|
