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import os
import sys
import cv2
import numpy as np
import lib.Perspec2Equirec as P2E
class Perspective:
def __init__(self, img_array , F_T_P_array ):
assert len(img_array)==len(F_T_P_array)
self.img_array = img_array
self.F_T_P_array = F_T_P_array
def GetEquirec(self,height,width):
#
# THETA is left/right angle, PHI is up/down angle, both in degree
#
merge_image = np.zeros((height,width,3))
merge_mask = np.zeros((height,width,3))
for img_dir,[F,T,P] in zip (self.img_array,self.F_T_P_array):
per = P2E.Perspective(img_dir,F,T,P) # Load equirectangular image
img , mask = per.GetEquirec(height,width) # Specify parameters(FOV, theta, phi, height, width)
mask = mask.astype(np.float32)
img = img.astype(np.float32)
weight_mask = np.zeros((img_dir.shape[0],img_dir.shape[1], 3))
w = img_dir.shape[1]
weight_mask[:,0:w//2,:] = np.linspace(0,1,w//2)[...,None]
weight_mask[:,w//2:,:] = np.linspace(1,0,w//2)[...,None]
weight_mask = P2E.Perspective(weight_mask,F,T,P)
weight_mask, _ = weight_mask.GetEquirec(height,width)
blur = cv2.blur(mask,(5,5))
blur = blur * mask
mask = (blur == 1) * blur + (blur != 1) * blur * 0.05
merge_image += img * weight_mask
merge_mask += weight_mask
merge_image[merge_mask==0] = 255.
merge_mask = np.where(merge_mask==0,1,merge_mask)
merge_image = (np.divide(merge_image,merge_mask))
return merge_image
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