This project uses Template Matching technique for object detecting by detection of template image over base image.

Overview

Object Detection Project Using OpenCV

projectLogo

This project uses Template Matching technique for object detecting by detection the template image over base image.

REQUIREMENTS

  • Python python  

  • OpenCV   

pip install opencv-python
pip install Tkinter

📝 CODE EXPLANATION

Importing Differnt Libraries
import cv2
import tkinter as tk 
from tkinter import filedialog,messagebox
import os
import sys

Taking Image input using Tkinter

Base Image Input Template Image Input
Base Image Input Template Image Input

Taking User Input using TKinter

root = tk.Tk() 
root.withdraw() 
file_path_base = filedialog.askopenfilename(initialdir= os.getcwd(),title="Select Base Image: ")
file_path_temp= filedialog.askopenfilename(initialdir= os.getcwd(),title="Select Template Image: ")

Loading base image and template image using cv2.imread()

Input Image Template Image Result Image
Input Image
Template Image
Result Image
Input Image
Template Image
Result Image
Input Image
Template Image
Result Image
Input Image
Template Image
Result Image
try:
    img = cv2.imread(file_path_base)

cv2.cvtColor()method is used to convert an image from one color space to another. There are more than 150 color-space conversion methods available in OpenCV.

Syntax: cv2.cvtColor(image, code, dst, dstCn)

    img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    template = cv2.imread(file_path_temp,0)

Getting the height and width of the template image using .shape method.

    h ,w = template.shape

Error dialogue box using Tkinter

error

except cv2.error:
   messagebox.showinfo("Warning!","No Image Found!")
   sys.exit(0)

cv2.matchTemplate is used to comapare images. It gives a 2D-array as output.

match = cv2.matchTemplate(img_gray,template,cv2.TM_CCOEFF_NORMED)
threshold = 0.99

cv2.minMaxLoc returns the top-left corner of the template position for the best match.

min_val, max_val, min_location, max_location = cv2.minMaxLoc(match)
location = max_location
font = cv2.FONT_HERSHEY_PLAIN

cv2.rectangle() method is used to draw a rectangle on any image.

Syntax: cv2.rectangle(image, start_point, end_point, color, thickness)

cv2.rectangle(img, location, (location[0] + w, location[1] + h), (0,0,255), 2)

cv2.putText() method is used to draw a text string on any image.

Syntax: cv2.putText(image, text, start_point, font, fontScale, color, thickness, lineType, bottomLeftOrigin)

cv2.putText(img,"Object Spotted.", (location[0]-40,location[1]-5),font , 1, (0,0,0),2)

  • cv2.imwrite() method is used to save an image to any storage device. This will save the image according to the specified format in current working directory.
  • cv2.imshow method is used to display an image in a window. The window automatically fits to the image size.

Syntax: cv2.imwrite(filename, image)

Syntax: cv2.imshow(window_name, image)

cv2.imwrite('images/result.jpg',img)
cv2.imshow('Results.jpg',img)

cv2.waitkey() allows you to wait for a specific time in milliseconds until you press any button on the keyword.

cv2.waitKey(0)

cv2.destroyAllWindows() method destroys all windows whenever any key is pressed.

cv2.destroyAllWindows()

📬 Contact

If you want to contact me, you can reach me through below handles.

@prrthamm   Pratham Bhatnagar

Owner
Pratham Bhatnagar
Computer Science Engineering student at SRM University. || Blockchain || ML Enthusiast || Open Source || Team member @srm-kzilla || Associate @NextTechLab
Pratham Bhatnagar
[CVPR 2021] Generative Hierarchical Features from Synthesizing Images

[CVPR 2021] Generative Hierarchical Features from Synthesizing Images

GenForce: May Generative Force Be with You 148 Dec 09, 2022
Official PyTorch implementation of the ICRA 2021 paper: Adversarial Differentiable Data Augmentation for Autonomous Systems.

Adversarial Differentiable Data Augmentation This repository provides the official PyTorch implementation of the ICRA 2021 paper: Adversarial Differen

Manli 3 Oct 15, 2022
S2s2net - Sentinel-2 Super-Resolution Segmentation Network

S2S2Net Sentinel-2 Super-Resolution Segmentation Network Getting started Install

Wei Ji 10 Nov 10, 2022
Official repository for Natural Image Matting via Guided Contextual Attention

GCA-Matting: Natural Image Matting via Guided Contextual Attention The source codes and models of Natural Image Matting via Guided Contextual Attentio

Li Yaoyi 349 Dec 26, 2022
First-Order Probabilistic Programming Language

FOPPL: A First-Order Probabilistic Programming Language This is an implementation of FOPPL, an S-expression based probabilistic programming language d

Renato Costa 23 Dec 20, 2022
Python script that analyses the given datasets and comes up with the best polynomial regression representation with the smallest polynomial degree possible

Python script that analyses the given datasets and comes up with the best polynomial regression representation with the smallest polynomial degree possible, to be the most reliable with the least com

Nikolas B Virionis 2 Aug 01, 2022
Contrastive Language-Image Pretraining

CLIP [Blog] [Paper] [Model Card] [Colab] CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pair

OpenAI 11.5k Jan 08, 2023
A facial recognition doorbell system using a Raspberry Pi

Facial Recognition Doorbell This project expands on the person-detecting doorbell system to allow it to identify faces, and announce names accordingly

rydercalmdown 22 Apr 15, 2022
HandTailor: Towards High-Precision Monocular 3D Hand Recovery

HandTailor This repository is the implementation code and model of the paper "HandTailor: Towards High-Precision Monocular 3D Hand Recovery" (arXiv) G

Lv Jun 113 Jan 06, 2023
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. List of Algorithms

Mayur 119 Nov 24, 2022
TLDR; Train custom adaptive filter optimizers without hand tuning or extra labels.

AutoDSP TLDR; Train custom adaptive filter optimizers without hand tuning or extra labels. About Adaptive filtering algorithms are commonplace in sign

Jonah Casebeer 48 Sep 19, 2022
Fibonacci Method Gradient Descent

An implementation of the Fibonacci method for gradient descent, featuring a TKinter GUI for inputting the function / parameters to be examined and a matplotlib plot of the function and results.

Emma 1 Jan 28, 2022
g2o: A General Framework for Graph Optimization

g2o - General Graph Optimization Linux: Windows: g2o is an open-source C++ framework for optimizing graph-based nonlinear error functions. g2o has bee

Rainer Kümmerle 2.5k Dec 30, 2022
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (Local-Lip)

Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (Local-Lip) Introduction TL;DR: We propose an efficient and trainabl

17 Dec 01, 2022
Curated list of awesome GAN applications and demo

gans-awesome-applications Curated list of awesome GAN applications and demonstrations. Note: General GAN papers targeting simple image generation such

Minchul Shin 4.5k Jan 07, 2023
A symbolic-model-guided fuzzer for TLS

tlspuffin TLS Protocol Under FuzzINg A symbolic-model-guided fuzzer for TLS Master Thesis | Thesis Presentation | Documentation Disclaimer: The term "

69 Dec 20, 2022
A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.

collie_recs Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Coll

ShopRunner 97 Jan 03, 2023
This code implements constituency parse tree aggregation

README This code implements constituency parse tree aggregation. Folder details code: This folder contains the code that implements constituency parse

Adithya Kulkarni 0 Oct 11, 2021
Step by Step on how to create an vision recognition model using LOBE.ai, export the model and run the model in an Azure Function

Step by Step on how to create an vision recognition model using LOBE.ai, export the model and run the model in an Azure Function

El Bruno 3 Mar 30, 2022