def load_camera_data(file_name):
"""Loads the camera data using the sintel SDK and converts to torch.Tensor.
"""
assert os.path.isfile(file_name), "Invalid file {}".format(file_name)
import sintel_io
intrinsic, extrinsic = sintel_io.cam_read(file_name)
return intrinsic, extrinsic
def load_camera_data(file_name):
"""Load the camera data using the syntel SDK and converts to torch.Tensor."""
if not os.path.isfile(file_name):
raise AssertionError(f"Invalid file {file_name}")
import sintel_io
intrinsic, extrinsic = sintel_io.cam_read(file_name)
return intrinsic, extrinsic
import numpy as np
from matplotlib import pyplot as plt
import sys
sys.path.append('../')
import sintel_io as sio
# Test and display some real data
folder_name = 'alley_1'
frame_no = 1 #smaller than 10
DEPTHFILE = '/cluster/scratch/takmaza/CVL/MPI-Sintel-complete/training/depth/' + folder_name + '/frame_000' + str(
frame_no) + '.dpt'
CAMFILE = '/cluster/scratch/takmaza/CVL/MPI-Sintel-complete/training/camdata_left/' + folder_name + '/frame_0001.cam'
# Load data
depth = sio.depth_read(DEPTHFILE)
I, E = sio.cam_read(CAMFILE)
print(depth.shape)
# Display data
#plt.figure()
#plt.imshow(depth,cmap='gray')
#plt.title('depth')
print(I)
print(E)
#plt.show()
def get_K_Sintel(cam_folder, seq_folder, frame):
I, E = sio.cam_read(cam_folder + seq_folder +
'/frame_{:04d}.cam'.format(frame + 1))
return I