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
Locally Differentially Private Distributed Deep Learning via Knowledge Distillation (LDP-DL)

Locally Differentially Private Distributed Deep Learning via Knowledge Distillation (LDP-DL) A preprint version of our paper: Link here This is a samp

Di Zhuang 3 Jan 08, 2023
Tensorflow 2.x implementation of Vision-Transformer model

Vision Transformer Unofficial Tensorflow 2.x implementation of the Transformer based Image Classification model proposed by the paper AN IMAGE IS WORT

Soumik Rakshit 16 Jul 20, 2022
GLM (General Language Model)

GLM GLM is a General Language Model pretrained with an autoregressive blank-filling objective and can be finetuned on various natural language underst

THUDM 421 Jan 04, 2023
Repo for paper "Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information"

Repo for paper "Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information" Notes I probabl

Berkeley Expert System Technologies Lab 0 Jul 01, 2021
Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"

On the Bottleneck of Graph Neural Networks and its Practical Implications This is the official implementation of the paper: On the Bottleneck of Graph

75 Dec 22, 2022
Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization

FAC-Net Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization Linjiang Huang (CUHK), Liang Wang (CASIA), Hongsheng

21 Nov 22, 2022
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l

Microsoft 244 Jan 06, 2023
Metrics to evaluate quality and efficacy of synthetic datasets.

An Open Source Project from the Data to AI Lab, at MIT Metrics for Synthetic Data Generation Projects Website: https://sdv.dev Documentation: https://

The Synthetic Data Vault Project 129 Jan 03, 2023
PyTorch implementation of TSception V2 using DEAP dataset

TSception This is the PyTorch implementation of TSception V2 using DEAP dataset in our paper: Yi Ding, Neethu Robinson, Su Zhang, Qiuhao Zeng, Cuntai

Yi Ding 27 Dec 15, 2022
[ArXiv 2021] Data-Efficient Instance Generation from Instance Discrimination

InsGen - Data-Efficient Instance Generation from Instance Discrimination Data-Efficient Instance Generation from Instance Discrimination Ceyuan Yang,

GenForce: May Generative Force Be with You 93 Dec 25, 2022
Official PyTorch Code of GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection (CVPR 2021)

GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Mo

Abhinav Kumar 76 Jan 02, 2023
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Model This repository is the official PyTorch implementation of GraphRNN, a graph gene

Jiaxuan 568 Dec 29, 2022
PyTorch code of paper "LiVLR: A Lightweight Visual-Linguistic Reasoning Framework for Video Question Answering"

LiVLR-VideoQA We propose a Lightweight Visual-Linguistic Reasoning framework (LiVLR) for VideoQA. The overview of LiVLR: Evaluation on MSRVTT-QA Datas

JJ Jiang 7 Dec 30, 2022
Christmas face app for Decathlon xmas coding party!

Christmas Face Application Use this library to create the perfect picture for your christmas cards! Done by Hasib Zunair, Guillaume Brassard and Samue

Hasib Zunair 4 Dec 20, 2021
[peer review] An Arbitrary Scale Super-Resolution Approach for 3D MR Images using Implicit Neural Representation

ArSSR This repository is the pytorch implementation of our manuscript "An Arbitrary Scale Super-Resolution Approach for 3-Dimensional Magnetic Resonan

Qing Wu 19 Dec 12, 2022
PartImageNet is a large, high-quality dataset with part segmentation annotations

PartImageNet: A Large, High-Quality Dataset of Parts We will release our dataset and scripts soon after cleaning and approval. Introduction PartImageN

Ju He 77 Nov 30, 2022
Understanding the Generalization Benefit of Model Invariance from a Data Perspective

Understanding the Generalization Benefit of Model Invariance from a Data Perspective This is the code for our NeurIPS2021 paper "Understanding the Gen

1 Jan 15, 2022
Official code repository for the work: "The Implicit Values of A Good Hand Shake: Handheld Multi-Frame Neural Depth Refinement"

Handheld Multi-Frame Neural Depth Refinement This is the official code repository for the work: The Implicit Values of A Good Hand Shake: Handheld Mul

55 Dec 14, 2022
Open-source code for Generic Grouping Network (GGN, CVPR 2022)

Open-World Instance Segmentation: Exploiting Pseudo Ground Truth From Learned Pairwise Affinity Pytorch implementation for "Open-World Instance Segmen

Meta Research 99 Dec 06, 2022
Dynamic Attentive Graph Learning for Image Restoration, ICCV2021 [PyTorch Code]

Dynamic Attentive Graph Learning for Image Restoration This repository is for GATIR introduced in the following paper: Chong Mou, Jian Zhang, Zhuoyuan

Jian Zhang 84 Dec 09, 2022