Feature Detection Based Template Matching

Overview

Feature Detection Based Template Matching

The classification of the photos was made using the OpenCv template Matching method.

Installation

Use the package manager pip to install OpenCV and Matplotlib

pip install opencv-python
pip install matplotlib

Code Review

Loading Images

'''Taking all images that we want to classify for them'''
path= "..\\FeatureBasedTemplateMatching\\Class\\"
images = []
classname = []
image_list = os.listdir(path)

Creating Classes

'''Creating classes via image names'''
for clss in image_list:
    imgCurrent = cv2.imread(f'{path}{clss}',0)
    images.append(imgCurrent)
    classname.append(os.path.splitext(clss)[0])

Creating ORB Object

About ORB

'''Creating ORB object'''#Fast and Free to use
orb = cv2.ORB_create()

Finding all Decriptors

Computed descriptors. Output concatenated vectors of descriptors. Each descriptor is a 32-element vector, as returned by cv.ORB.descriptorSize, so the total size of descriptors will be numel(keypoints) * obj.descriptorSize(), i.e a matrix of size N-by-32 of class uint8, one row per keypoint.

'''Finding All Descriptors'''
def findDesc(images):
    descList = []
    for image in images:
        kp,desc = orb.detectAndCompute(image,None)
        descList.append(desc)
    return descList

Finding Detection Image ID

'''Finding image id via using descritor list'''
def findID(img, descList):
    kp2, desc2 = orb.detectAndCompute(img,None)
    bf = cv2.BFMatcher()
    matchList = []
    finalval = -1
    try:
        for des in descList:
            matches = bf.knnMatch(des,desc2,k=2)
            goodmatches = []
            for m, n in matches:
                if m.distance < 0.75 * n.distance:
                    goodmatches.append([m])
            matchList.append(len(goodmatches))
    except:
        pass
    if matchList:
        if max(matchList) > TRESHOLD:
            finalval = matchList.index(max(matchList))
    return finalval

Detection

'''Image that we want to detect'''
detection_image = cv2.imread("..\\FeatureBasedTemplateMatching\\10kmmatch.jpg")
img_gray = cv2.cvtColor(detection_image,cv2.COLOR_BGR2GRAY)


descList = findDesc(images)
id =findID(img_gray,descList)

if id != -1:
    cv2.putText(detection_image,classname[id],(50,50),cv2.FONT_HERSHEY_PLAIN,5,(255,0,0),3)

Output

alt text

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT

Owner
Muhammet Erem
Muhammet Erem
CS50 pset9: Using flask API to create a web application to exchange stocks' shares.

C$50 Finance In this guide we want to implement a website via which users can “register”, “login” “buy” and “sell” stocks, like below: Background If y

1 Jan 24, 2022
Randomisation-based inference in Python based on data resampling and permutation.

Randomisation-based inference in Python based on data resampling and permutation.

67 Dec 27, 2022
MotorcycleParts DataAnalysis python

We work with the accounting department of a company that sells motorcycle parts. The company operates three warehouses in a large metropolitan area.

NASEEM A P 1 Jan 12, 2022
VevestaX is an open source Python package for ML Engineers and Data Scientists.

VevestaX Track failed and successful experiments as well as features. VevestaX is an open source Python package for ML Engineers and Data Scientists.

Vevesta 24 Dec 14, 2022
MIR Cheatsheet - Survival Guidebook for MIR Researchers in the Lab

MIR Cheatsheet - Survival Guidebook for MIR Researchers in the Lab

SeungHeonDoh 3 Jul 02, 2022
Synthetic Data Generation for tabular, relational and time series data.

An Open Source Project from the Data to AI Lab, at MIT Website: https://sdv.dev Documentation: https://sdv.dev/SDV User Guides Developer Guides Github

The Synthetic Data Vault Project 1.2k Jan 07, 2023
Full automated data pipeline using docker images

Create postgres tables from CSV files This first section is only relate to creating tables from CSV files using postgres container alone. Just one of

1 Nov 21, 2021
Find exposed data in Azure with this public blob scanner

BlobHunter A tool for scanning Azure blob storage accounts for publicly opened blobs. BlobHunter is a part of "Hunting Azure Blobs Exposes Millions of

CyberArk 250 Jan 03, 2023
Udacity-api-reporting-pipeline - Udacity api reporting pipeline

udacity-api-reporting-pipeline In this exercise, you'll use portions of each of

Fabio Barbazza 1 Feb 15, 2022
Data-sets from the survey and analysis

bachelor-thesis "Umfragewerte.xlsx" contains the orginal survey results. "umfrage_alle.csv" contains the survey results but one participant is cancele

1 Jan 26, 2022
vartests is a Python library to perform some statistic tests to evaluate Value at Risk (VaR) Models

gg I wasn't satisfied with any of the other available Gemini clients, so I wrote my own. Requires Python 3.9 (maybe older, I haven't checked) and opti

RAFAEL RODRIGUES 5 Jan 03, 2023
Desafio proposto pela IGTI em seu bootcamp de Cloud Data Engineer

Desafio Modulo 4 - Cloud Data Engineer Bootcamp - IGTI Objetivos Criar infraestrutura como código Utuilizando um cluster Kubernetes na Azure Ingestão

Otacilio Filho 4 Jan 23, 2022
In this tutorial, raster models of soil depth and soil water holding capacity for the United States will be sampled at random geographic coordinates within the state of Colorado.

Raster_Sampling_Demo (Resulting graph of this demo) Background Sampling values of a raster at specific geographic coordinates can be done with a numbe

2 Dec 13, 2022
Probabilistic reasoning and statistical analysis in TensorFlow

TensorFlow Probability TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFl

3.8k Jan 05, 2023
Analytical view of olist e-commerce in Brazil

Analysis of E-Commerce Public Dataset by Olist The objective of this project is to propose an analytical view of olist e-commerce in Brazil. For this

Gurpreet Singh 1 Jan 11, 2022
Exploring the Top ML and DL GitHub Repositories

This repository contains my work related to my project where I scraped data on the most popular machine learning and deep learning GitHub repositories in order to further visualize and analyze it.

Nico Van den Hooff 17 Aug 21, 2022
This program analyzes a DNA sequence and outputs snippets of DNA that are likely to be protein-coding genes.

This program analyzes a DNA sequence and outputs snippets of DNA that are likely to be protein-coding genes.

1 Dec 28, 2021
PyNHD is a part of HyRiver software stack that is designed to aid in watershed analysis through web services.

A part of HyRiver software stack that provides access to NHD+ V2 data through NLDI and WaterData web services

Taher Chegini 23 Dec 14, 2022
A collection of robust and fast processing tools for parsing and analyzing web archive data.

ChatNoir Resiliparse A collection of robust and fast processing tools for parsing and analyzing web archive data. Resiliparse is part of the ChatNoir

ChatNoir 24 Nov 29, 2022
Option Pricing Calculator using the Binomial Pricing Method (No Libraries Required)

Binomial Option Pricing Calculator Option Pricing Calculator using the Binomial Pricing Method (No Libraries Required) Background A derivative is a fi

sammuhrai 1 Nov 29, 2021