Roy Shilkrot royshil

## AndroidCamera2TouchToFocus.java
    //Override in your touch-enabled view (this can be differen than the view you use for displaying the cam preview)
    @Override
    public boolean onTouch(View view, MotionEvent motionEvent) {
        final int actionMasked = motionEvent.getActionMasked();
        if (actionMasked != MotionEvent.ACTION_DOWN) {
            return false;
        }
        if (mManualFocusEngaged) {
            Log.d(TAG, "Manual focus already engaged");
            return true;

## circle_of_deadlines.html
<!DOCTYPE html>
<html>
<meta charset="utf-8">
<head>
    <script src="http://cdnjs.cloudflare.com/ajax/libs/babel-standalone/6.23.1/babel.min.js"></script>
    <script src="http://cdnjs.cloudflare.com/ajax/libs/d3/4.6.0/d3.min.js"></script>
    <script src="http://unpkg.com/d3-radial-axis@1.5/dist/d3-radial-axis.min.js"></script>
    <script src="https://npmcdn.com/d3fc-rebind@4.0.1/build/d3fc-rebind.js"></script>
    <script src="https://npmcdn.com/d3fc-data-join@2.0.0/build/d3fc-data-join.js"></script>
    <script src="https://npmcdn.com/d3fc-label-layout@4.0.0/build/d3fc-label-layout.js"></script>

## lap_pyr.py
# adapted from http://docs.opencv.org/3.0-beta/doc/py_tutorials/py_imgproc/py_pyramids/py_pyramids.html

import cv2
import numpy as np

def Laplacian_Pyramid_Blending_with_mask(A, B, m, num_levels = 6):
    # assume mask is float32 [0,1]

    # generate Gaussian pyramid for A,B and mask
    GA = A.copy()

## segmentation_graphcut_superpixels.py
import cv2
import numpy as np
import matplotlib.pyplot as plt
from skimage.segmentation import slic
from skimage.segmentation import mark_boundaries
from skimage.data import astronaut
from skimage.util import img_as_float
import maxflow
from scipy.spatial import Delaunay

## setup.sh
#!/bin/bash

# First you must install the 4.4.0 kernel:
# $ sudo apt-get install linux-image-4.4.0-112-generic
# find all the other kernels and remove them:
# $ sudo apt-get purge linux-image-4.13.0-1008-gcp
# $ sudo update-grub
# $ sudo reboot

sudo apt-get update && sudo apt-get install -y \

## BUILD
package(default_visibility = ["//visibility:public"])

cc_toolchain_suite(
    name = "toolchain",
    toolchains = {
        "armeabi-v7a|compiler": ":cc-compiler-armeabi",
        "k8|compiler": ":cc-compiler-local",
    },
)

## copy_tf_headers.sh
#!/bin/bash
# inspired by a part of: https://github.com/cjweeks/tensorflow-cmake/blob/master/build.sh
#
# Assumes Tensorflow libraries libtensorflow_framework.so and libtensorflow_cc.so were built with Bazel,
# and the ${TF_ROOT}/tensorflow/contrib/makefile/download_dependencies.sh script was executed.

set -o nounset
set -o errexit
set -o pipefail

## cylindricalWarping.py
import cv2
import numpy as np

def cylindricalWarp(img, K):
    """This function returns the cylindrical warp for a given image and intrinsics matrix K"""
    h_,w_ = img.shape[:2]
    # pixel coordinates
    y_i, x_i = np.indices((h_,w_))
    X = np.stack([x_i,y_i,np.ones_like(x_i)],axis=-1).reshape(h_*w_,3) # to homog
    Kinv = np.linalg.inv(K)

## ffmpeg_concat_xfade.py
#!/usr/local/bin/python3

import argparse
import subprocess
import itertools


parser = argparse.ArgumentParser(description='Concatenate videos with FFMPEG, add "xfade" between segments.')
parser.add_argument('--segments_file', '-f', metavar='Segments file', type=str, nargs=1,
                    help='Segments text file for concatenating. e.g. "segments.txt"')

## google_cloud_speech_json_to_srt.py
#!/usr/local/bin/python3

import os
import json
import sys
import argparse
import math
import subprocess
from tqdm import tqdm
	//Override in your touch-enabled view (this can be differen than the view you use for displaying the cam preview)
	@Override
	public boolean onTouch(View view, MotionEvent motionEvent) {
	final int actionMasked = motionEvent.getActionMasked();
	if (actionMasked != MotionEvent.ACTION_DOWN) {
	return false;
	}
	if (mManualFocusEngaged) {
	Log.d(TAG, "Manual focus already engaged");
	return true;
	<!DOCTYPE html>
	<html>
	<meta charset="utf-8">
	<head>
	<script src="http://cdnjs.cloudflare.com/ajax/libs/babel-standalone/6.23.1/babel.min.js"></script>
	<script src="http://cdnjs.cloudflare.com/ajax/libs/d3/4.6.0/d3.min.js"></script>
	<script src="http://unpkg.com/d3-radial-axis@1.5/dist/d3-radial-axis.min.js"></script>
	<script src="https://npmcdn.com/d3fc-rebind@4.0.1/build/d3fc-rebind.js"></script>
	<script src="https://npmcdn.com/d3fc-data-join@2.0.0/build/d3fc-data-join.js"></script>
	<script src="https://npmcdn.com/d3fc-label-layout@4.0.0/build/d3fc-label-layout.js"></script>
	# adapted from http://docs.opencv.org/3.0-beta/doc/py_tutorials/py_imgproc/py_pyramids/py_pyramids.html

	import cv2
	import numpy as np

	def Laplacian_Pyramid_Blending_with_mask(A, B, m, num_levels = 6):
	# assume mask is float32 [0,1]

	# generate Gaussian pyramid for A,B and mask
	GA = A.copy()
	import cv2
	import numpy as np
	import matplotlib.pyplot as plt
	from skimage.segmentation import slic
	from skimage.segmentation import mark_boundaries
	from skimage.data import astronaut
	from skimage.util import img_as_float
	import maxflow
	from scipy.spatial import Delaunay
	#!/bin/bash

	# First you must install the 4.4.0 kernel:
	# $ sudo apt-get install linux-image-4.4.0-112-generic
	# find all the other kernels and remove them:
	# $ sudo apt-get purge linux-image-4.13.0-1008-gcp
	# $ sudo update-grub
	# $ sudo reboot

	sudo apt-get update && sudo apt-get install -y \
	package(default_visibility = ["//visibility:public"])

	cc_toolchain_suite(
	name = "toolchain",
	toolchains = {
	"armeabi-v7a\|compiler": ":cc-compiler-armeabi",
	"k8\|compiler": ":cc-compiler-local",
	},
	)
	#!/bin/bash
	# inspired by a part of: https://github.com/cjweeks/tensorflow-cmake/blob/master/build.sh
	#
	# Assumes Tensorflow libraries libtensorflow_framework.so and libtensorflow_cc.so were built with Bazel,
	# and the ${TF_ROOT}/tensorflow/contrib/makefile/download_dependencies.sh script was executed.

	set -o nounset
	set -o errexit
	set -o pipefail
	import cv2
	import numpy as np

	def cylindricalWarp(img, K):
	"""This function returns the cylindrical warp for a given image and intrinsics matrix K"""
	h_,w_ = img.shape[:2]
	# pixel coordinates
	y_i, x_i = np.indices((h_,w_))
	X = np.stack([x_i,y_i,np.ones_like(x_i)],axis=-1).reshape(h_*w_,3) # to homog
	Kinv = np.linalg.inv(K)
	#!/usr/local/bin/python3

	import argparse
	import subprocess
	import itertools


	parser = argparse.ArgumentParser(description='Concatenate videos with FFMPEG, add "xfade" between segments.')
	parser.add_argument('--segments_file', '-f', metavar='Segments file', type=str, nargs=1,
	help='Segments text file for concatenating. e.g. "segments.txt"')
	#!/usr/local/bin/python3

	import os
	import json
	import sys
	import argparse
	import math
	import subprocess
	from tqdm import tqdm