docs: add project features to README.md

Romaisaa · Sep 19, 2023 · 8ee058b · 8ee058b
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-# CV Toolbox
+# Computer-Vision-Toolkit
+
+## Table of contents:
+
+- [Introduction](#introduction)
+- [Full Project Features](#project-features)
+- [Project Structure](#project-structure)
+- [How to Run The Project](#run-the-project)
+- [Team](#team)
+
+### Introduction
+
+Computer Vision Toolkit Application is a software solution designed to leverage the power of computer vision algorithms through an intuitive and user-friendly graphical user interface (GUI) developed using the Qt framework. This application aims to provide users with a versatile toolset for image analysis, making it suitable for a wide range of applications, including image processing, object detection,image features extraction, and more.
+
+### Project Features:
+
+This application mainly consists of 11 tabs (pages) to provide user with all needed CV algorithms, each page has certain features that are related to each other as follows:
+
+1. Filters, Noise and Edge Detectors page:<br />
+   Includes 3 types of noise that user can add to gray/coloured images:
+
+   |         Uniform Noise          |         Guassian Noise          |        Salt & Pepper Noise         |
+   | :----------------------------: | :-----------------------------: | :--------------------------------: |
+   | ![](samples\uniform-noise.png) | ![](samples\guassian-noise.png) | ![](samples\salt-pepper-noise.png) |
+
+   Includes 4 edge detectors types with the ability to control kernal size and any additional option for detector:
+   | Sobel | Roberts | Perwitt | Canny |
+   | :----------------------------: | :-----------------------------: | :--------------------------------: | :--------------------------------: |
+   | ![](samples\sobel-detector.png) | ![](samples\roberts-detector.png) | ![](samples\perwitt-detector.png) | ![](samples\canny-detector.png) |
+
+   Includes 3 types of filter enanling user to control kernal size:
+
+   |         Average Filter          |         Guassian Filter          |         Median Filter          |
+   | :-----------------------------: | :------------------------------: | :----------------------------: |
+   | ![](samples\average-filter.png) | ![](samples\guassian-filter.png) | ![](samples\median-filter.png) |
+
+   for more details about this page and results check [Report 1](docs\Report%201.pdf)
+
+2. Normalization, Equalization and Thresholding page:<br />
+   Shows images histogram with options to normalize or equalize:
+   | Histogram | Normalization | Equalization |  
+   | :----------------------------: | :-----------------------------: | :-----------------------------: |
+   | ![](samples\histogram.png) | ![](samples\normalization.png) | ![](samples\equalizer.png) |
+
+   Apply both global or local thresholding on uploaded image:
+   | Local | Global |  
+   | :----------------------------: | :-----------------------------: |
+   | ![](samples\local-thresh.png) | ![](samples\global-thresh.png) |
+
+   for more details about this page and results check [Report 1](docs\Report%201.pdf)
+
+3. Frequency Domain Filters and Hybird Image:
+   User upload 2 different images and determine the raduis for each filter type(high pass or low pass) and then can combine the output to get hybird image.
+   ![](samples\hybird.png)
+   for more details about this page and results check [Report 1](docs\Report%201.pdf)
+
+4. Hough Transform Page:
+   This page enbles user to apply Line/ Circle / Ellipse hough transform:
+   | Line | Circle | Ellipse |  
+   | :----------------------------: | :-----------------------------: | :-----------------------------: |
+   | ![](samples\hough-line.png) | ![](samples\hough-circle.png) | ![](samples\hough-ellipse.png) |
+
+   for more details about this page and results check [Report 2](docs\Report%202.pdf)
+
+5. Active Contour Page:
+   User has the ability to select cirlce fro image and tune paramters to contour objects.
+   | Example 1 | Example 2 |  
+   | :----------------------------: | :-----------------------------: |
+   | ![](samples\active-contour.png) | ![](samples\active-contour-2.png) |
+
+   for more details about this page and results check [Report 2](docs\Report%202.pdf)
+
+6. Harris and Lambda Corner detector page:
+   User can detect corners by harris or lambda methods and change kernal size and threshold.
+   | Harris | Lambda |  
+   | :----------------------------: | :-----------------------------: |
+   | ![](samples\harris.png) | ![](samples\lambda.png) |
+
+   for more details about this page and results check [Report 3](docs\Report%203.pdf)
+
+7. Image Matching Methods page:
+   User can match between image template and full image with 2 methods:
+   | Square Sum of Differences method | Cross Correlation Method |  
+   | :----------------------------: | :-----------------------------: |
+   | ![](samples\match-ssd.png) | ![](samples\match-ncc.png) |
+
+   for more details about this page and results check [Report 3](docs\Report%203.pdf)
+
+8. Sift Descriptors Page:
+   User can upload one or two image to get SIFT Keypoints with options to tune, and then compute keypoints matching between images.
+   <p align="center">
+     <img src="samples\sift-match.png" />
+   </p>
+
+   for more details about this page and results check [Report 3](docs\Report%203.pdf)
+
+9. Advanced Thresholding Page:
+   Includes Global Thresholding with 2 methods:
+   |Ostu Thresholding| Optimal Thresholding |  
+   | :----------------------------: | :-----------------------------: |
+   | ![](samples\ostu-thresh.png) | ![](samples\optimal-thres.png) |
+
+   Includes Local Thresholding and Multi-level Thresholding:
+   |Local Thresholding| Multi-level Thresholding |  
+   | :----------------------------: | :-----------------------------: |
+   | ![](samples\local-thresh-2.png) | ![](samples\multi-thresh.png) |
+
+   for more details about this page and results check [Report 4](docs\Report%204.pdf)
+
+10. Segmentation Methods Page:
+    User can segment RGB images with 4 types of segmentation:
+    | K-Means Segmentation | Mean Shift Segmentation | Agglomerative Segmentation | Region Growing |
+    | :----------------------------: | :-----------------------------: | :--------------------------------: | :--------------------------------: |
+    | ![](samples\k-means.png) | ![](samples\mean-shift-seg.png) | ![](samples\agg-seg.png) | ![](samples\region-growing.png) |
+
+for more details about this page and results check [Report 4](docs\Report%204.pdf)
+
+11. Face Recognition and detection page:
+
+- User can upload person or multi persons images and detect faces in images.
+- User can upload training folder includes images named with its label.
+- Once training finishes, User can upload new image to predict person in the image
+- if model already exists, Then user can work dirctley without training
+- For new training, user can determin number of PCA compenets to train a nearest neigbour model.
+- User can upload test folder to visulaize ROC for each label.
diff --git a/samples/active-contour-2.png b/samples/active-contour-2.png
diff --git a/samples/active-contour.png b/samples/active-contour.png
diff --git a/samples/agg-seg.png b/samples/agg-seg.png
diff --git a/samples/average-filter.png b/samples/average-filter.png
diff --git a/samples/canny-detector.png b/samples/canny-detector.png
diff --git a/samples/equalizer.png b/samples/equalizer.png
diff --git a/samples/global-thresh.png b/samples/global-thresh.png
diff --git a/samples/guassian-filter.png b/samples/guassian-filter.png
diff --git a/samples/guassian-noise.png b/samples/guassian-noise.png
diff --git a/samples/harris.png b/samples/harris.png
diff --git a/samples/high-pass.png b/samples/high-pass.png
diff --git a/samples/histogram.png b/samples/histogram.png
diff --git a/samples/hough-circle.png b/samples/hough-circle.png
diff --git a/samples/hough-ellipse.png b/samples/hough-ellipse.png
diff --git a/samples/hough-line.png b/samples/hough-line.png
diff --git a/samples/hybird.png b/samples/hybird.png
diff --git a/samples/k-means.png b/samples/k-means.png
diff --git a/samples/lambda.png b/samples/lambda.png
diff --git a/samples/local-thresh-2.png b/samples/local-thresh-2.png
diff --git a/samples/local-thresh.png b/samples/local-thresh.png
diff --git a/samples/low-pass.png b/samples/low-pass.png
diff --git a/samples/match-ncc.png b/samples/match-ncc.png
diff --git a/samples/match-ssd.png b/samples/match-ssd.png
diff --git a/samples/mean-shift-seg.png b/samples/mean-shift-seg.png
diff --git a/samples/median-filter.png b/samples/median-filter.png
diff --git a/samples/multi-thresh.png b/samples/multi-thresh.png
diff --git a/samples/normalization.png b/samples/normalization.png
diff --git a/samples/optimal-thres.png b/samples/optimal-thres.png
diff --git a/samples/ostu-thresh.png b/samples/ostu-thresh.png
diff --git a/samples/perwitt-detector.png b/samples/perwitt-detector.png
diff --git a/samples/region-growing.png b/samples/region-growing.png
diff --git a/samples/roberts-detector.png b/samples/roberts-detector.png
diff --git a/samples/salt-pepper-noise.png b/samples/salt-pepper-noise.png
diff --git a/samples/sift-feat.png b/samples/sift-feat.png
diff --git a/samples/sift-match.png b/samples/sift-match.png
diff --git a/samples/sobel-detector.png b/samples/sobel-detector.png
diff --git a/samples/uniform-noise.png b/samples/uniform-noise.png