Mini Projects for CSE with Source Code in Python

This article about Mini Projects for CSE with Source Code in Python will give you a list of the Best Python Projects With Source code for this year.

Main Objectives

My objective is to provide a real world project topics and project idea for a Computer Science Engineers and software developer.

These cse mini projects contains practical knowledge applicable for your Final Year Projects.

Best Mini Projects for CSE Students with Source Code in Python

Here are the list of CSE Mini Projects Students with Source Code, These are the Best Projects Ideas for Computer Engineering.

1. Real-Time Eye Detection

The Eye Detection you will learn about detecting a human eye with the feature mappers knows as haar cascades.

Here in the project, we will use the python language along with the OpenCV library for the algorithm execution and image processing respectively.

2. Face Recognition

The Face Recognition is a machine learning based approach where a cascade function is trained with a set of input data.

A Face Detection Algorithm Python can detect faces of people in an images, faces contains a list of coordinates for the rectangular regions where faces were found.

3. Color Detection

This Color Detection is necessary to recognize objects, it is also used as a tool in various image editing and drawing apps.

Color Detection is the process of detecting the name of any color. Simple isn’t it? Well, for human resource this is an extremely easy task but for computers, it is not straightforward.

4. Real-Time Human Body Detection

The Real-Time Human Body Detection will show how to build your own “smart” video camera.

A Human Body Detection Python OpenCV is an intermediate level deep learning project on computer vision, which will help you to master the concepts and make you an expert in the field of Data Science. Let’s build an exciting project.

In this Full Body Detection OpenCV Python, we are going to build the Human Detection and Counting System through Webcam or you can give your own video or images.

5. Real-Time Student Attendance Management System

This Student Attendance Management System Project provides a valuable attendance service for both teachers and students.

A Attendance Management System is a simple python script that recognizes faces and mark attendance for the recognized faces in an excel sheet.

We seek to provide a valuable attendance service for both teachers and students. Reduce manual process errors by provide automated and a reliable attendance system uses face recognition technology.

6. Holistic Detection

The Holistic Detection We are going to detect left and right hand, face mesh, and pose detection.

MediaPipe has a lot of built-in customizable Machine Learning Solutions. MediaPipe is the newest and fastest within machine learning solutions and can be run on common hardware which we are going to see throughout this article.

7. Real-Time Face Blur

The Face Blur we are going to learn to Realtime videos using OpenCV and try to learn with existing tools like Haar cascades and build Realtime Face Detection and Face blur.

8. Volume Control With Hand Detection

We first look into hand tracking and then we will use the hand landmarks to find gesture of our hand to change the volume. This project is module based which means we will be using a previously created hand module which makes the hand tracking very easy.

9. Brightness Control With Hand Detection

Building a Brightness Controller can be accomplished in just 3 simple steps:

• Step 1. Detect Hand landmarks
• Step 2. Calculate the distance between thumb tip and index finger tip.
• Step 3. Map the distance of thumb tip and index finger tip with volume range. For my case, distance between thumb tip and index finger tip was within the range of 15 – 220 and the volume range was from 0 – 100.

10. Extract Faces From Image

This 2022 Extract Faces From Image Images make up a large amount of the data that gets generated each day, which makes the ability to process these images important.

One method of processing images is via face detection. Face detection is a branch of image processing that uses machine learning to detect faces in images.

11. Eye Blink Counting Detection

The Eye Blink Detection focused solely on using the eye aspect ratio as a quantitative metric to determine if a person has blinked in a video stream.

However, due to noise in a video stream, subpar facial landmark detections, or fast changes in viewing angle, a simple threshold on the eye aspect ratio could produce a false-positive detection, reporting that a blink had taken place when in reality the person had not blinked.

12. Human Pose Estimation

The Human Pose Estimation will focus on human pose estimation, where it is required to detect and localize the major parts/joints of the body ( e.g. shoulders, ankle, knee, wrist etc. ).

13. Hand Landmark Detection

A Hand Landmark Detection, We will be using OpenCV to read the image and displaying it and MediaPipe to perform the hand detection and landmark estimation.

In short, MediaPipe is a free and open-source framework that offers cross-platform, customizable Machine Learning solutions for live and streaming media.

14. Document Scanner

The Document Scanner  takes a poorly scanned image, finds the corners of the document, applies the perspective transformation to get a top-down view of the document, sharpens the image, and applies an adaptive color threshold to clean up the image.

15. Screen Recorder

The Screen Recorder allows performing a variety of tasks. One of them can be recording a video. It provides a module named pyautogui which can be used for the same.

This module along with NumPy and OpenCV provides the way to manipulate and save the images (screenshot in this case).

A OpenCV Python Screen Recording enables you to create demonstration videos, record gaming achievements and create videos that can be shared online on social media.

16. Pixel Picker

The Pixel Picker will be helpful in learning OpenCV using Python Programming. The goal of this Simple Project is to make you understand how to access Image Pixel to get RGB color values.

An Pixel Picker can check pixel value on the image by mouse left click. and also This Project can check pixel value(BGR, HSV, LAB, etc.) on the image.

17. Warp Perspective

This warp perspective will show you how to apply warping transformations to obtain a “birds-eye-view” of given cards image. From there, we will be able to crop out the selected card.

18. Angle Finder

The Angle Finder will first define two lines using mouse clicks and then find the angle between these lines using simple mathematics.

19. Gender and Age Detection

To build a gender and age detector that can approximately guess the gender and age of the person (face) in a picture using Python Deep Learning on the Adience dataset.

The predicted gender may be one of ‘Male’ and ‘Female’, and the predicted age may be one of the following ranges- (0 – 2), (4 – 6), (8 – 12), (15 – 20), (25 – 32), (38 – 43), (48 – 53), (60 – 100) (8 nodes in the final softmax layer).

20. Canny Edge Detection

The Canny Edge Detection is a multi-step algorithm used to detect a wide range of edges in images.

Canny edge detector is arguably the most well known and the most used edge detector in all of computer vision and image processing.

A Canny Edge Detection uses a filter based on the derivative of a Gaussian in order to compute the intensity of the gradients. The Gaussian reduces the effect of noise present in the image.

21. Lane Detection

Self Driving Cars use lane detection OpenCV features to detect lane of the roads and they are trained not to drive outside of the lane.

22. TrackBar

Trackbar is a GUI element that let the user to select a specific color value within a range of values by sliding a slider linearly.

It’s similar to scrolling but it limits the user to select a specific value with its minimum and maximum limits.

A trackbar in OpenCV provides cv2.createTrackbar() function, to read the current position of the trackbar slider you can use cv2.getTrackbarPos() function to change the position of trackbar use cv2.setTrackbarPos().

23. Shapes Detection

The Shape Detection taking an image that contains shapes like triangle, square, rectangle, and circle. The image is then converted to grayscale using the cvtColor() function.

24. Live Sketch

The Live Sketch is an application which will show a live sketch of your webcam feed. In this project we’ll be using NumPy and OpenCV. We will also make use of Numpy and Matplotlib to make this live sketch app.

25. Image Blending

There are many designing tools out there, but our goal is to create a beautiful design without using any of those software in this project.

After working on this project, you will also have an idea on how to work with the OpenCV package. It is a great skill to have, especially if you like computer vision. You can follow a similar structure when working on similar OpenCV projects.

26. Clicked Event

The Mouse Events OpenCV Algorithm Computer Vision for reading and showing images and image manipulation. Matplotlib for data visualization Read and Show Image for Mouse Events OpenCV.

27. Motion Detection

The Motion Detection OpenCV Python Algorithm Capture Video, in which you have to detect movement using OpenCV in Python.

In many applications based on machine vision, motion detection is used. For example, when we want to count the people who pass by a certain place. In all these cases, the first thing we have to do is extract the people that are at the scene.

28. Traffic Signs Recognition

Traffic signs classification is the process of identifying which class a traffic sign belongs to.

A Traffic Signs Recognition build a deep neural network model that can classify traffic signs present in the image into different categories.

With this model, we are able to read and understand traffic signs which are a very important task for all autonomous vehicles.

29. Cartoonify an Image

The Cartoonify an Image will build a python application that will transform an image into its cartoon using OpenCV.

30. Handwritten Digit Recognition

The Handwritten Digit Recognition In Python was developed using Python Deep Learning, this we are going to implement a handwritten digit recognition app using the MNIST dataset.

We will be using a special type of deep neural network which is Convolutional Neural Network.

In the end, we are going to build a GUI in which you can draw the digit and recognize it straight away.

Handwritten Digit Recognition s the ability of computers to recognize human handwritten digits.

It is a hard task for the machine because handwritten digits are not perfect and can be made with many different flavors.

The handwritten digit recognition is the solution to this problem which uses the image of a digit and recognizes the digit present in the image.

Final Year Projects for CSE Students with Source Code Below

• Check it out and Download here the list of the Final Year Projects for CSE Students with Source Code.
• If you want more to know about HTML and CSS for creating a web based or web application and database management, Also I have here the List of the Best Web Development Projects with Source Code for free.
• If you want also Java Project, I have here the Best Java Projects With Source Code For Beginners Free Download.

Summary

We have successfully compiled the list of the Best Final Year Mini Projects for CSE with Source Code for this year.

In this article, you can learn more and enhance your programming skills, especially Python Programming Language.

If you want to explore your knowledge in different programming languages, just type your keyword in our site search engine, I hope you can build a better project or be a member of full-stack development team for the future that can help in our daily living.