kushalvyas

import cv2
import numpy as np 
from glob import glob 
import argparse
from helpers import *

class BOV:
    def __init__(self, no_clusters):
        self.no_clusters = no_clusters
        self.train_path = None

kushalvyas

n_samples = 1000
n_features = 5;
n_clusters = 3;

# aint this sweet 
X, y = make_blobs(n_samples, n_features) 
# X => array of shape [nsamples,nfeatures] ;;; y => array of shape[nsamples]

# X : generated samples, y : integer labels for cluster membership of each sample

kushalvyas

"""
Using SKLearns API for performing Kmeans clustering.
Using sklearn.datasets.make_blobs for generating randomized gaussians
for clustering.

"""

import numpy as np 
from matplotlib import pyplot as plt 
from sklearn.cluster import KMeans

kushalvyas

"""
Template matching using opencv

Run : python file.py <templateImage> <actualImage>


"""

import sys, cv2
import numpy as np

kushalvyas

/*
Author : Kushal Vyas
Code for template matching as implemented by opencv.

*/
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/opencv.hpp"
#include "iostream"
#include "cmath"