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import cv2
import sys
import math
import numpy as np
from matplotlib import pyplot as plt
def main():
print("OpenCV Version: " + str(cv2.__version__) + "\n")
import cv2
import sys
import math
import numpy as np
from matplotlib import pyplot as plt
def main():
print("OpenCV Version: " + str(cv2.__version__) + "\n")
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.examples.tutorials.mnist import input_data
import tensorflow as tf
# Mnistに使うデータセットをインポートする
mnist = input_data.read_data_sets('/tmp/tensorflow/mnist/input_data',
import cv2
import sys
import math
import numpy as np
from matplotlib import pyplot as plt
def main():
print("OpenCV Version: " + str(cv2.__version__) + "\n")
import open3d as o3d
import numpy as np
if __name__ == "__main__":
# Loading mesh data
print("Loading mesh data")
Mesh = o3d.io.read_triangle_mesh("bunny.ply")
# Calculation of normal vector
import open3d as o3d
import numpy as np
if __name__ == "__main__":
# Loading mesh data
print("Loading mesh data")
Mesh = o3d.io.read_triangle_mesh("bunny.ply")
# Confirmation
import open3d as o3d
import numpy as np
if __name__ == "__main__":
# Loading point cloud
print("Loading point cloud")
ptCloud = o3d.io.read_point_cloud("G-PCD\dragon.ply")
# Normal estimation
import numpy as np
import open3d as o3d
if __name__ == "__main__":
# Loading point cloud
print("Loading point cloud")
ptCloud = o3d.io.read_point_cloud("G-PCD\dragon.ply")
# Estimation of normal vector of points
import cv2
import sys
def main():
print("OpenCV Version: " + str(cv2.__version__) + "\n")
# Loading image data (COLOR)
filename1 = "data/gt_image.png"
filename2 = "data/noisy_image.png"
import numpy as np
import cv2
import sys
def main():
print("OpenCV Version: " + str(cv2.__version__) + "\n")
# Loading image data (COLOR)
filename = "data/lenna.png"