Ahmed Nassar nassarofficial

## matching_sift.cpp
#include <opencv2/opencv.hpp>
#include <opencv2/nonfree/nonfree.hpp>
#include <iostream>
#include <vector>
#include <cmath>

using namespace std;
using namespace cv;

const double THRESHOLD = 400;

## Kmeans Readme.md

      
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                umbertogriffo
                / Kmeans Readme.md
            
            
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              March 8, 2024 13:40
            
              
                Step by step Code Tutorial on implementing a basic k-means in Spark in order to cluster a geo-located devices
              
          
    DATASET


Download dataset here

CODE

* Follow the well-comented code kmeans.scala


## classifier_from_little_data_script_3.py
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats
	#include <opencv2/opencv.hpp>
	#include <opencv2/nonfree/nonfree.hpp>
	#include <iostream>
	#include <vector>
	#include <cmath>

	using namespace std;
	using namespace cv;

	const double THRESHOLD = 400;
	'''This script goes along the blog post
	"Building powerful image classification models using very little data"
	from blog.keras.io.
	It uses data that can be downloaded at:
	https://www.kaggle.com/c/dogs-vs-cats/data
	In our setup, we:
	- created a data/ folder
	- created train/ and validation/ subfolders inside data/
	- created cats/ and dogs/ subfolders inside train/ and validation/
	- put the cat pictures index 0-999 in data/train/cats