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import os
import sys
import cv2
import numpy as np
class Perspective:
def __init__(self, img_name , FOV, THETA, PHI ):
if isinstance(img_name, str):
self._img = cv2.imread(img_name, cv2.IMREAD_COLOR)
else:
self._img = img_name
[self._height, self._width, _] = self._img.shape
self.wFOV = FOV
self.THETA = THETA
self.PHI = PHI
self.hFOV = float(self._height) / self._width * FOV
self.w_len = np.tan(np.radians(self.wFOV / 2.0))
self.h_len = np.tan(np.radians(self.hFOV / 2.0))
def GetEquirec(self,height,width):
#
# THETA is left/right angle, PHI is up/down angle, both in degree
#
x,y = np.meshgrid(np.linspace(-180, 180,width),np.linspace(90,-90,height))
x_map = np.cos(np.radians(x)) * np.cos(np.radians(y))
y_map = np.sin(np.radians(x)) * np.cos(np.radians(y))
z_map = np.sin(np.radians(y))
xyz = np.stack((x_map,y_map,z_map),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(self.THETA))
[R2, _] = cv2.Rodrigues(np.dot(R1, y_axis) * np.radians(-self.PHI))
R1 = np.linalg.inv(R1)
R2 = np.linalg.inv(R2)
xyz = xyz.reshape([height * width, 3]).T
xyz = np.dot(R2, xyz)
xyz = np.dot(R1, xyz).T
xyz = xyz.reshape([height , width, 3])
inverse_mask = np.where(xyz[:,:,0]>0,1,0)
xyz[:,:] = xyz[:,:]/np.repeat(xyz[:,:,0][:, :, np.newaxis], 3, axis=2)
lon_map = np.where((-self.w_len<xyz[:,:,1])&(xyz[:,:,1]<self.w_len)&(-self.h_len<xyz[:,:,2])
&(xyz[:,:,2]<self.h_len),(xyz[:,:,1]+self.w_len)/2/self.w_len*self._width,0)
lat_map = np.where((-self.w_len<xyz[:,:,1])&(xyz[:,:,1]<self.w_len)&(-self.h_len<xyz[:,:,2])
&(xyz[:,:,2]<self.h_len),(-xyz[:,:,2]+self.h_len)/2/self.h_len*self._height,0)
mask = np.where((-self.w_len<xyz[:,:,1])&(xyz[:,:,1]<self.w_len)&(-self.h_len<xyz[:,:,2])
&(xyz[:,:,2]<self.h_len),1,0)
persp = cv2.remap(self._img, lon_map.astype(np.float32), lat_map.astype(np.float32), cv2.INTER_CUBIC, borderMode=cv2.BORDER_WRAP)
mask = mask * inverse_mask
mask = np.repeat(mask[:, :, np.newaxis], 3, axis=2)
persp = persp * mask
return persp , mask
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