Kriti ninjakx

## myknn.h
/* File knn.h */
#ifndef KNN_H
#define KNN_H
#include <stdio.h>
#include <vector>
#include <map>
/* Define function prototype */
std::map<int,std::vector<int> > distance_knn(const double* array,int m, int n);
std::vector<int> argsort(double* input_list, int length);
double edist(double* arr1, double* arr2, int n);

## build.sh
rm *.o myknn_wrap.cpp _myknn.so myknn.py
rm -rf __pycache__

g++ -O3 -march=native -fPIC -c myknn.cpp

# Invoke SWIG on the interface file 'knn.i' to produce C/C++ wrapper
# code ('knn_wrap.cpp'):

swig -python -c++ -o myknn_wrap.cpp myknn.i

## compute_swig_knn.py
from myknn import distance_knn
%%time
c = distance_knn(arr)

## hsv_masking.py
%%capture
%matplotlib inline
from ipywidgets import interact, widgets
from IPython.display import display
import cv2
from scipy import misc
import matplotlib.pyplot as plt
import numpy as np

def f(lower_H, lower_S, lower_V, upper_H, upper_S, upper_V, **kwargs):

## split_and_merge.py
import numpy as np
import matplotlib.pyplot as plt

# https://stackoverflow.com/a/55176783/6660373
# 20x20 image
img = im#np.random.randint(0,9,(512,512))

# List of 4 5x20 image slices
sliced = np.split(img,4,axis=0)

## .block
license: mit

## .block
license: mit

## .block
license: mit

## .block
license: mit

## .block
license: mit
	/* File knn.h */
	#ifndef KNN_H
	#define KNN_H
	#include <stdio.h>
	#include <vector>
	#include <map>
	/* Define function prototype */
	std::map<int,std::vector<int> > distance_knn(const double* array,int m, int n);
	std::vector<int> argsort(double* input_list, int length);
	double edist(double* arr1, double* arr2, int n);
	rm *.o myknn_wrap.cpp _myknn.so myknn.py
	rm -rf __pycache__

	g++ -O3 -march=native -fPIC -c myknn.cpp

	# Invoke SWIG on the interface file 'knn.i' to produce C/C++ wrapper
	# code ('knn_wrap.cpp'):

	swig -python -c++ -o myknn_wrap.cpp myknn.i
	%%capture
	%matplotlib inline
	from ipywidgets import interact, widgets
	from IPython.display import display
	import cv2
	from scipy import misc
	import matplotlib.pyplot as plt
	import numpy as np

	def f(lower_H, lower_S, lower_V, upper_H, upper_S, upper_V, **kwargs):
	import numpy as np
	import matplotlib.pyplot as plt

	# https://stackoverflow.com/a/55176783/6660373
	# 20x20 image
	img = im#np.random.randint(0,9,(512,512))

	# List of 4 5x20 image slices
	sliced = np.split(img,4,axis=0)