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#!/usr/bin/env python3
import numpy as np
import os
import sys
import json
import shutil
# cameras = json.load(open('./kai_cameras_offsetnorm.json'))
# cameras = json.load(open('./kai_cameras.json'))
cameras = json.load(open('./kai_cameras_normalized.json'))
def convert_pose(C2W):
flip_yz = np.eye(4)
flip_yz[1, 1] = -1
flip_yz[2, 2] = -1
C2W = np.matmul(C2W, flip_yz)
return C2W
def w2c_to_c2w(w2c):
w2c = np.reshape(w2c, (4, 4))
c2w = np.linalg.inv(w2c)
#c2w = convert_pose(c2w)
return c2w.reshape(-1)
for base in ['train', 'test', 'validation']:
obj = dict()
os.makedirs(os.path.join(base, 'intrinsics'), exist_ok=True)
os.makedirs(os.path.join(base, 'pose'), exist_ok=True)
os.makedirs(os.path.join(base, 'mask'), exist_ok=True)
for c in cameras:
fn = '.'.join(c.split('.')[:-1])+'.txt'
if os.path.exists(os.path.join(base, 'rgb', c)):
print(base, fn)
with open(os.path.join(base, 'intrinsics', fn), 'w') as f:
print(*cameras[c]['K'], file=f)
with open(os.path.join(base, 'pose', fn), 'w') as f:
w2c = cameras[c]['W2C']
c2w = w2c_to_c2w(w2c)
print(*c2w, file=f)
maskfn = os.path.join('mask', '.'.join(c.split('.')[:-1])+'.png')
shutil.copyfile(maskfn, os.path.join(base, maskfn))
obj[c] = cameras[c]
with open(os.path.join(base, 'cam_dict_norm.json'), 'w') as f:
json.dump(obj, f)
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