Jian Shi shijianjian

## OCT_data_ROI_seg.py
"""Cirrus OCT ROI segmentation.

Author: Jian Shi
Email: sj8716643@126.com
"""

import numpy as np
import pandas as pd
import os
import cv2

## visual_3d.py
""" Visualize 3D objects in a video manner.
Current config is for Cirrus OCT only.

Author: Jian Shi
Email: sj8716643@126.com
"""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

## Heidelberg_dcm_to_png.py
"""
Image extractor for Heidelberg OCT B-SCANS.

Author: Jian Shi
Date created: 28/08/2020
"""

from multiprocessing import Pool
import matplotlib.pyplot as plt
import pydicom

## np_tile_implementation.py
import types
import numpy as np

def test_tile(x, multiplier):
    x = np.array(x)
    if isinstance(multiplier, list):
        raise ValueError("multiplier must be a List or numpy array")

    multiplier = np.array(multiplier)
    if len(multiplier.shape) > 1:

## WirelessLogging.swift
// Enable logging as:
// if (WirelessLogging.DEBUG_MODE){
//     WirelessLogging.shared.initRemoteLogging()
// }
// Logging as:
// WirelessLogging.log(message: "Success", log: "sensor", type: .debug)

import Foundation
import os.log

## hdf5_to_TFRecords.py
'''
This converter is used to convert hdf5 file to TFRecords.

Dataset used:
This is designed for the point cloud hdf5 data of pointnet,
which can be downloaded from https://github.com/charlesq34/pointnet/sem_seg

The sample data shape is
    h5py {
        'data': (1000, 4096, 9), # (number_of_data, points, channels)

## sobel_filter.py
import numpy as np
import cv2
import matplotlib.pyplot as plt
%matplotlib inline

'''
Read in image
'''
img = cv2.imread('./fruit_img.jpg', cv2.IMREAD_COLOR)
gray_img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) # use black and white for demostration

## tensorflow_self_check.py
# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
	"""Cirrus OCT ROI segmentation.

	Author: Jian Shi
	Email: sj8716643@126.com
	"""

	import numpy as np
	import pandas as pd
	import os
	import cv2
	""" Visualize 3D objects in a video manner.
	Current config is for Cirrus OCT only.

	Author: Jian Shi
	Email: sj8716643@126.com
	"""

	from __future__ import absolute_import
	from __future__ import division
	from __future__ import print_function
	"""
	Image extractor for Heidelberg OCT B-SCANS.

	Author: Jian Shi
	Date created: 28/08/2020
	"""

	from multiprocessing import Pool
	import matplotlib.pyplot as plt
	import pydicom
	import types
	import numpy as np

	def test_tile(x, multiplier):
	x = np.array(x)
	if isinstance(multiplier, list):
	raise ValueError("multiplier must be a List or numpy array")

	multiplier = np.array(multiplier)
	if len(multiplier.shape) > 1:
	// Enable logging as:
	// if (WirelessLogging.DEBUG_MODE){
	// WirelessLogging.shared.initRemoteLogging()
	// }
	// Logging as:
	// WirelessLogging.log(message: "Success", log: "sensor", type: .debug)

	import Foundation
	import os.log
	'''
	This converter is used to convert hdf5 file to TFRecords.

	Dataset used:
	This is designed for the point cloud hdf5 data of pointnet,
	which can be downloaded from https://github.com/charlesq34/pointnet/sem_seg

	The sample data shape is
	h5py {
	'data': (1000, 4096, 9), # (number_of_data, points, channels)
	# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,