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.
Pratham Bhatnagar
Kaggle Feedback Prize - Evaluating Student Writing 15th solution

Kaggle Feedback Prize - Evaluating Student Writing 15th solution First of all, I would like to thank the excellent notebooks and discussions from http

Lingyuan Zhang 6 Mar 24, 2022
Pytorch implementation for the Temporal and Object Quantification Networks (TOQ-Nets).

TOQ-Nets-PyTorch-Release Pytorch implementation for the Temporal and Object Quantification Networks (TOQ-Nets). Temporal and Object Quantification Net

Zhezheng Luo 9 Jun 30, 2022
Code for the paper "Adversarially Regularized Autoencoders (ICML 2018)" by Zhao, Kim, Zhang, Rush and LeCun

ARAE Code for the paper "Adversarially Regularized Autoencoders (ICML 2018)" by Zhao, Kim, Zhang, Rush and LeCun https://arxiv.org/abs/1706.04223 Disc

Junbo (Jake) Zhao 399 Jan 02, 2023
Code for NeurIPS 2021 paper "Curriculum Offline Imitation Learning"

README The code is based on the ILswiss. To run the code, use python run_experiment.py --nosrun -e your YAML file -g gpu id Generally, run_experim

ApexRL 12 Mar 19, 2022
HAR-stacked-residual-bidir-LSTMs - Deep stacked residual bidirectional LSTMs for HAR

HAR-stacked-residual-bidir-LSTM The project is based on this repository which is presented as a tutorial. It consists of Human Activity Recognition (H

Guillaume Chevalier 287 Dec 27, 2022
Code Release for the paper "TriBERT: Full-body Human-centric Audio-visual Representation Learning for Visual Sound Separation"

TriBERT This repository contains the code for the NeurIPS 2021 paper titled "TriBERT: Full-body Human-centric Audio-visual Representation Learning for

UBC Computer Vision Group 8 Aug 31, 2022
VOneNet: CNNs with a Primary Visual Cortex Front-End

VOneNet: CNNs with a Primary Visual Cortex Front-End A family of biologically-inspired Convolutional Neural Networks (CNNs). VOneNets have the followi

The DiCarlo Lab at MIT 99 Dec 22, 2022
PyTorch implementation of the implicit Q-learning algorithm (IQL)

Implicit-Q-Learning (IQL) PyTorch implementation of the implicit Q-learning algorithm IQL (Paper) Currently only implemented for online learning. Offl

Sebastian Dittert 27 Dec 30, 2022
PyTorch implementation of Soft-DTW: a Differentiable Loss Function for Time-Series in CUDA

Soft DTW Loss Function for PyTorch in CUDA This is a Pytorch Implementation of Soft-DTW: a Differentiable Loss Function for Time-Series which is batch

Keon Lee 76 Dec 20, 2022
Pytorch implementation of MLP-Mixer with loading pre-trained models.

MLP-Mixer-Pytorch PyTorch implementation of MLP-Mixer: An all-MLP Architecture for Vision with the function of loading official ImageNet pre-trained p

Qiushi Yang 2 Sep 29, 2022
Boostcamp AI Tech 3rd / Basic Paper reading w.r.t Embedding

Boostcamp AI Tech 3rd : Basic Paper Reading w.r.t Embedding TL;DR 1992년부터 2018년도까지 이루어진 word/sentence embedding의 중요한 줄기를 이루는 기초 논문 스터디를 진행하고자 합니다. 논

Soyeon Kim 14 Nov 14, 2022
Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's algorithm.

Bayes-Newton Bayes-Newton is a library for approximate inference in Gaussian processes (GPs) in JAX (with objax), built and actively maintained by Wil

AaltoML 165 Nov 27, 2022
Prototypical python implementation of the trust-region algorithm presented in Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints by Larson, Leyffer, Kirches, and Manns.

Prototypical python implementation of the trust-region algorithm presented in Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints by Larson, L

3 Dec 02, 2022
Lunar is a neural network aimbot that uses real-time object detection accelerated with CUDA on Nvidia GPUs.

Lunar Lunar is a neural network aimbot that uses real-time object detection accelerated with CUDA on Nvidia GPUs. About Lunar can be modified to work

Zeyad Mansour 276 Jan 07, 2023
This is the repository for our paper SimpleTrack: Understanding and Rethinking 3D Multi-object Tracking

SimpleTrack This is the repository for our paper SimpleTrack: Understanding and Rethinking 3D Multi-object Tracking. We are still working on writing t

TuSimple 189 Dec 26, 2022
scalingscattering

Scaling The Scattering Transform : Deep Hybrid Networks This repository contains the experiments found in the paper: https://arxiv.org/abs/1703.08961

Edouard Oyallon 78 Dec 21, 2022
Discord Multi Tool that focuses on design and easy usage

Multi-Tool-v1.0 Discord Multi Tool that focuses on design and easy usage Delete webhook Block all friends Spam webhook Modify webhook Webhook info Tok

Lodi#0001 24 May 23, 2022
Official implementation of ACTION-Net: Multipath Excitation for Action Recognition (CVPR'21).

ACTION-Net Official implementation of ACTION-Net: Multipath Excitation for Action Recognition (CVPR'21). Getting Started EgoGesture data folder struct

V-Sense 171 Dec 26, 2022
DaReCzech is a dataset for text relevance ranking in Czech

Dataset DaReCzech is a dataset for text relevance ranking in Czech. The dataset consists of more than 1.6M annotated query-documents pairs,

Seznam.cz a.s. 8 Jul 26, 2022
Exploring the Dual-task Correlation for Pose Guided Person Image Generation

Dual-task Pose Transformer Network The source code for our paper "Exploring Dual-task Correlation for Pose Guided Person Image Generation“ (CVPR2022)

63 Dec 15, 2022