😎 Finding duplicate images made easy!
📖 This guide is to help you understand the basics of the computerized image and develop computer vision projects with OpenCV. Includes Python, Java, JavaScript, C# and C++ examples.
Keras implementation of the Yahoo Open-NSFW model
[NeurIPS 2020] Cross-Scale Internal Graph Neural Network for Image Super-Resolution
A simpler way of reading and augmenting image segmentation data into TensorFlow
Designing and Training of A Dual CNN for Image Denoising (Knowledge-based Systems, 2021)
Face Recognition/Detection (image/video) using skin tone threshold algorithm, haar cascade for face detection and LBPH for face recognition. It also implements the concept of multithreaded server with multiple clients.
Algorithm to segment pectoral muscles in breast mammograms
Intensity normalization of structural MRIs using RAVEL
image filtering techniques in python with examples
A python library for automated exploratory data analysis
A GUI for Image Processing
The binary classification problem focused on first IEEE Image forensics challenge-phase 1, to predict the given image is pristine or manipulated/edited/fake. Comparing CNN & Transfer Learning models for the problem and boosting the performance by feature extraction
Edge-preserving image smoothing algorithm
This repository contains all my exercises and projects for computer vision.
Generic Image Sorter Interface for Streamlit
Preprocessing the images and saving them in a specific directory with python
This program enables real-time face recognition for attendance marking. It uses a webcam or video input to detect and recognize faces in real-time. When a recognized face is identified with sufficient accuracy, the corresponding name is recorded in an attendance file named Attendance.csv, along with the timestamp of the recognition.
⛏️ Contains 4 python modules. Basic OCR using Google's Tesseract on single image and pdf. Auto orientation correction for scanned docs. Auto noise type detection and reduction. Watermark and stain removal on scanned docs. These modules act as preprocessing tools for the best OCR results.
CenOTAPH: COlour and Texture Analysis toolbox for PytHon
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