codexsys-7 Goto Github PK

4-1-project

5x5-tic-tac-toe

age-related-macular-disease-detection-using-cnn

Age Related Macular Degeneration is a type of eye disease which normally affects the central vision of a person. This Disease might sometimes lead to permanent vision loss in some persons and mostly this might affect the people who are aged above 50. This disease doesn’t lead to permanent vision loss but it will definitely impact the peripheral vision. So, basically there are 2 different types of ARMD i.e., Dry and Wet, Dry ARMD will generate a tiny amount of protein deposits called drusen, whereas Wet ARMD occurs whenever any abnormal blood vessel is developed under the retina, so sometimes this blood vessels might leak blood fluid, this type of ARMD is very severe and can even lead to severe permanent central vision loss.

audio-books

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

baby-behavior-monitoring-iot

Embedded Vision for Baby Behavior Monitoring in IoT

brain-stroke-analysis

classifying-brain-tumor-using-cnn

In the recent times, we have been seeing a massive raise in brain stroke cases all over the world. Stroke is one of the leading causes of the death worldwide these days. About 1/5th of patients with an acute stroke dies within a month of event and at least 1/2 of those who survive are left with physical disability. So, we have developed a model to predict whether a person is affected with brain stroke or not. so, on top of this we have also created a Front End framework with Tkinter GUI where we can input the image and the model will try to predict the output and display it on the window.

click-the-image-smartly-using-opencv

Smart Selfie using OpenCV is an Interface which allows us to click selfies without touching our mobiles or any photo capturing devices. So, in this project we have used OpenCV to do the trick for us, where using the OpenCV’s video capture fucntion and some haarcascade files integrated with flask web framework we have made a smart selfie web application where you can click images without touching any keys on your laptop. The photos are later saved on your device specified directory for later use.

codecademy-learn-sql-from-scratch

coding-questions-practise

A complete computer science study plan to become a software engineer.

color-identification-in-an-image-using-machine-learning

Color Recognition through OpenCV is a Simple but very effective Project which involves in identifying color on a particular thing, this is useful in various applications, especially for the people who are having difficulty in recognizing colors and for the blind people, if we add Text to Speech Library. In order to identify the colors, the model is trained on various colored images using KNN Classifier which is a popular Machine Learning Algorithm and whenever we pass a new image to the model it will try to predict that particular color by comparing the color code within its database whcih the model is trained and then it displays it on the Screen.

complete-feature-selection

credit-card-fraud-

dataanalysisprojects

This contains data analysis projects

deep-fake-video-detection-using-deep-learning-and-tkinter-gui

Deep Fake Video/Image has been around since last decade where we are trying to mimic the behaviour, expression, lip and eye movement made by another person on top of another person, which is then synced to each other. These are then used for some illegal and legal activities by people like border crossing, financial thefts etc. So, in order to solve this problem, we can use the model above, where it helps us to identify whether a particular video fake or not using Transfer Learning and LSTM.

demo_price_deployment

don-t-break-traffic-rules-automatic-detection-of-helmet-and-number-plate-extraction-from-videos-or-i

Don’t Break Traffic Rules is basically a small yet massive background application model, which allows the users to detect and even capture the riders riding their vehicle without wearing helmet. So obviously yolo has been used to perform this type of task, since due to its scalability and efficiency it detects the objects in an image or video accurately, since it was manually trained on 1000’s of images to perform this task. Along with yolo we have also used OpenCV and Tkinter gui to build a front-end framework.

employee-retention

f.r.i.e.n.d.s-scripts-analysis

hey there lobsters, this is for ya'll.

free-algorithm-books

freecodecamp

freeCodeCamp.org's open-source codebase and curriculum. Learn to code for free.

friends

The Entire Transcript from Friends in Tidy Format

gaussian-trnasformaion

gfpgan

GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

git_upload

housing---linear-regression-model

identifying-defects-in-the-various-fabrics-using-convolutional-neural-networks

The main objective of this project is to identify whether there is any fault in the fabrics or not, this is done using convolutional neural networks where the model is trained on both defected and non-defect fabric dataset. The dataset was obtained from private data repository and some pre-processing has been performed to make sure the data is clean for modelling.

identifying-the-lane-the-vehicle-is-travelling

Lane detection is a very vast area to work on, since a lot of efforts are being put on to avoid even minute error and making a safe self-driving environment sustainable and efficient. So, there are a lot of methods where we can implement this lane detection while driving, one method we have used is through OpenCV where using its in built functions such as Sobel operator, perspective transformation and edge detection we have done rather a basic lane detection model, which identifies the lane the vehicle is travelling.

identifying_music_genre

How many times we have wondered, what might have been a songs genre, sometimes it might be easy and sometimes it might make our brains go wild, so this is it, this program allows us to predict the genre of the music using Transfer learning. The flow is as follows first we load the music file, split the songs into chunks, then load the model using load model (), using the loaded model, predict on the music which you ahve loaded earlier and since the output will be in the form of array, we use argmax() to extract the highest probability of the music genre the model has predicted.