Edge detection (canny part)

AdaptiveThresholding/README.md

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+# Adaptive Thresholding Method

AffineTransformation/README.md

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+# Affine Transformation

BackgroundSubtraction/README.md

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+# Background Subtraction
+
+Implementation of Background subtraction from a video data using the algorithms implemented by OpenCV.

BriefAlgorithm/README.md

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+# BRIEF Algorithm
+
+A minimal implementation of BRIEF (Binary Robust Independent Elementary Features) algorithm.

BruteForceFeatureMatcher/README.md

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+# Brute Force Matcher
+
+Implementation of Brute Force matcher to match features in one image with others.

CODE_OF_CONDUCT.md

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+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+In the interest of fostering an open and welcoming environment, we as
+contributors and maintainers pledge to making participation in our project and
+our community a harassment-free experience for everyone, regardless of age, body
+size, disability, ethnicity, sex characteristics, gender identity and expression,
+level of experience, education, socio-economic status, nationality, personal
+appearance, race, religion, or sexual identity and orientation.
+
+## Our Standards
+
+Examples of behavior that contributes to creating a positive environment
+include:
+
+* Using welcoming and inclusive language
+* Being respectful of differing viewpoints and experiences
+* Gracefully accepting constructive criticism
+* Focusing on what is best for the community
+* Showing empathy towards other community members
+
+Examples of unacceptable behavior by participants include:
+
+* The use of sexualized language or imagery and unwelcome sexual attention or
+ advances
+* Trolling, insulting/derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or electronic
+ address, without explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+ professional setting
+
+## Our Responsibilities
+
+Project maintainers are responsible for clarifying the standards of acceptable
+behavior and are expected to take appropriate and fair corrective action in
+response to any instances of unacceptable behavior.
+
+Project maintainers have the right and responsibility to remove, edit, or
+reject comments, commits, code, wiki edits, issues, and other contributions
+that are not aligned to this Code of Conduct, or to ban temporarily or
+permanently any contributor for other behaviors that they deem inappropriate,
+threatening, offensive, or harmful.
+
+## Scope
+
+This Code of Conduct applies both within project spaces and in public spaces
+when an individual is representing the project or its community. Examples of
+representing a project or community include using an official project e-mail
+address, posting via an official social media account, or acting as an appointed
+representative at an online or offline event. Representation of a project may be
+further defined and clarified by project maintainers.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported by contacting the project team at [email protected]. All
+complaints will be reviewed and investigated and will result in a response that
+is deemed necessary and appropriate to the circumstances. The project team is
+obligated to maintain confidentiality with regard to the reporter of an incident.
+Further details of specific enforcement policies may be posted separately.
+
+Project maintainers who do not follow or enforce the Code of Conduct in good
+faith may face temporary or permanent repercussions as determined by other
+members of the project's leadership.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
+available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
+
+[homepage]: https://www.contributor-covenant.org
+
+For answers to common questions about this code of conduct, see
+https://www.contributor-covenant.org/faq

CONTRIBUTING.md

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+# Contributing guidelines
+
+## Before contributing
+
+Welcome to [geekquad/Image-Processing-OpenCV](https://github.com/geekquad/AlgoBook). Before sending your pull requests, make sure that you **read the whole guidelines**.
+
+
+* Make sure you do not copy codes from external sources because that work will not be considered. Plagiarism is strictly not allowed.
+* You can only work on issues that you have been assigned to you.
+* If you want to contribute for an existing algorithm, we prefer that you create an issue before making a PR and link your PR to that issue.
+* If you have modified/added code work, make sure the code compiles before submitting.
+
+### Contribution
+
+We appreciate any contribution, from fixing a grammar mistake in a comment to implementing complex algorithms. Please read this section if you are contributing your work.
+
+#### Coding Style
+
+We want your work to be readable by others; therefore, we encourage you to note the following:
+
+- Follow PEP8 guidelines. Read more about it <a href="https://pep8.org/"> here. </a>
+- Please write in Python 3.7+.  __print()__ is a function in Python 3 so __print "Hello"__ will _not_ work but __print("Hello")__ will.
+- Please focus hard on naming of functions, classes, and variables.  Help your reader by using __descriptive names__ that can help you to remove redundant comments.
+  - Please follow the [Python Naming Conventions](https://pep8.org/#prescriptive-naming-conventions) so variable_names and function_names should be lower_case, CONSTANTS in UPPERCASE, ClassNames should be CamelCase, etc.
+  - Expand acronyms because __gcf()__ is hard to understand but __greatest_common_factor()__ is not.
+
+- Using only OpenCV modules are highly recommended.
+- Avoid importing external libraries for basic algorithms. Only use those libraries for complicated algorithms.
+- If you need a third party module that is not in the file __requirements.txt__, please add it to that file as part of your submission.
+
+#### Other points to remember while submitting your work:
+- **We won't be accepting just the dataset in the form of PRs.** If you are using any of the dataset in the implementation, then only we'll accept it.
+- Jupyter notebook files should be there with proper step-wise implementation.
+- Each file should be added with a dedicated README.md so that it gets easier for people to know your approach and the logic behind.
+- File extension for code should be `.py`. 
+- Strictly use snake_case (underscore_separated) in your file_name, as it will be easy to parse in future using scripts.
+- Please avoid creating new directories if at all possible. Try to fit your work into the existing directory structure. If you want to. Please contact us on our <a href="https://join.slack.com/t/geekquad/shared_invite/zt-l3t67zvr-JMKbn57PpxjEi7uC2k0etg"> Slack </a> channel.
+- If you have modified/added code work, make sure the code compiles before submitting.
+- If you have modified/added documentation work, ensure your language is concise and contains no grammar errors.
+- Do not update the README.md and CONTRIBUTING.md.
+
+**Join our <a href="https://join.slack.com/t/geekquad/shared_invite/zt-l3t67zvr-JMKbn57PpxjEi7uC2k0etg"> Slack </a> channel now.**
+Happy Coding :)
+

Camshift/README.md

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+# Camshift Algorithm
+
+Implementation of Camshift to find and track objects in videos.

ConcatenateImages/Readme.md

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+Concatenating images vertically and horizontally.

DepthMap/README.md

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+# Depth Map
+
+A minimal implementation of creating Depth Map or Disparity Map.

EdgeDetection/README.md

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+
+
+
+
+<!DOCTYPE html>
+<html lang = "en">
+<head>
+    <meta charset="utf-8" />
+    <link rel="stylesheet" href="main.css">
+</head>
+
+
+# Edge Detection
+Implementation of the following Edge Detection methods:
+* Canny Edge Detection
+* Robert Edge Detection
+* Sobel Edge Detection
+* Prewitt Edge Detection
+<br>
+    Prewitt operator is used for Prewitt edge detection in an image. It detects two types of edges: Horizontal and 
+    Vertical. Edges are calculated by using difference between corresponding pixel intensities of an image. 
+    All the masks that are used for edge detection are also known as derivative masks. Because as we have stated 
+    many times before in this series of tutorials that image is also a signal so changes in a signal can only be 
+    calculated using differentiation. So that’s why these operators are also called as derivative operators or 
+    derivative masks.
+
+<body>
+  <h1>Canny Edge Detection </h1>
+<p title=Canny Edge Detection >
+<a href="https://imgbb.com/"><img src="https://i.ibb.co/bKFbFSq/Figure-1.png" alt="Figure-1" border="0" /></a>
+
+<h3>Library used</h3>
+<p title=Library used->
+<ul>
+<li>numpy </li>
+<li>opencv</li>
+<li>matplotlib</li>
+</ul>
+</p>
+<a href="https://docs.opencv.org/master/da/d22/tutorial_py_canny.html">For more details about Canny</a>
+
+
+
+</body>
+</html>
+

EdgeDetection/canny_code.py

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+import numpy as np
+import cv2 as cv
+from matplotlib import pyplot as plt
+img = cv.imread('p2.jpg',0)
+edges = cv.Canny(img,50,100)
+plt.subplot(121),plt.imshow(img,cmap = 'gray')
+plt.title('Original Image'), plt.xticks([]), plt.yticks([])
+plt.subplot(122),plt.imshow(edges,cmap = 'gray')
+plt.title('Canny Image'), plt.xticks([]), plt.yticks([])
+plt.show()

Face_Detection/Readme.md

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+[![forthebadge](https://forthebadge.com/images/badges/made-with-python.svg)](https://forthebadge.com)
+[![forthebadge](https://forthebadge.com/images/badges/check-it-out.svg)](https://forthebadge.com)
+# Detects faces using OpenCV.
+Face Recognisation
+Recognizes the face and how much a face is similar to a test image using SVM Classifier. 
+<!DOCTYPE html>
+<html lang = "en">
+<head>
+    <meta charset="utf-8" />
+    <link rel="stylesheet" href="main.css">
+</head>
+
+<h1>Tools used</h1>
+<p title=Tools used>
+<ul>
+    <li>Pycharm</li>
+  <li>Visual Studio(community version)</li>
+  <li>Histogram Of oriented Gradients method for package face-recognisation</li>
+</ul>
+</p>
+
+<h1>Follow these steps </h1>
+<p title=Follow these steps>
+<ul>
+  <li>Open pycharm and add libraries given below in sequential manner by File>Settings> (+ on top right)>search libraries by name and install one by one.</li>
+  <li>Copy the code.py code from repository.</li>
+    <li>Download the test images and add to your pycharm project path.</li>
+    <li>Run the code.</li>
+</ul>
+</p>
+
+<h1>library used</h1>
+<p title=Library used->
+<ul>
+    <li>cmake</li>
+  <li>dil</li>
+  <li>face-recognisation</li>
+  <li>numpy </li>
+    <li>opencv</li>
+
+</ul>
+</p>
+
+<body>
+  <h1> Objective and Output</h1>
+<p title=  Objective and Output>
+<ul>
+<li>Compares multiple images </li>
+<li>Checks how similar the images are</li>
+</ul>
+</p>
+<h1>Application in real life</h1>
+<p title=Application in real life>
+<ul>
+    <li>Facebook uses this type of models to recognize friends in photos.</li>
+  <li>Its extended version is used to monitor attendence.</li>
+</ul>
+</p>
+  <h1>Articles for more details about the backend.</h1>
+<p title=Articles for more details about the backend. >
+<ul>
+    <li>https://docs.opencv.org/master/d9/df8/tutorial_root.html>
+<li>https://github.com/davisking/dlib>
+<li>https://medium.com/@ageitgey/machine-learning-is-fun-part-4-modern-face-recognition-with-deep-learning-c3cffc121d78</li>
+</ul>
+</p>
+
+</body>
+</html>
+
+

Face_Detection/code.py

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+import cv2
+import face_recognition
+
+imgElon = face_recognition.load_image_file('ImagesBasic/Elon Musk.jpg')
+imgElon = cv2.cvtColor(imgElon,cv2.COLOR_BGR2RGB)
+imgTest = face_recognition.load_image_file('ImagesBasic/Bill gates.jpg')
+imgTest = cv2.cvtColor(imgTest,cv2.COLOR_BGR2RGB)
+
+faceLoc = face_recognition.face_locations(imgElon)[0]
+encodeElon = face_recognition.face_encodings(imgElon)[0]
+cv2.rectangle(imgElon,(faceLoc[3],faceLoc[0]),(faceLoc[1],faceLoc[2]),(255,0,255),2)
+
+faceLocTest = face_recognition.face_locations(imgTest)[0]
+encodeTest = face_recognition.face_encodings(imgTest)[0]
+cv2.rectangle(imgTest,(faceLocTest[3],faceLocTest[0]),(faceLocTest[1],faceLocTest[2]),(255,0,255),2)
+
+results = face_recognition.compare_faces([encodeElon],encodeTest)
+faceDis = face_recognition.face_distance([encodeElon],encodeTest)
+print(results,faceDis)
+cv2.putText(imgTest,f'{results} {round(faceDis[0],2)}',(50,50),cv2.FONT_HERSHEY_COMPLEX,1,(0,0,255),2)
+
+cv2.imshow('Elon Musk',imgElon)
+cv2.imshow('Elon Test',imgTest)
+cv2.waitKey(0)

Face_Detection/images/.gitkeep

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+

FastAlgorithm/README.md

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+# FAST Algorithm
+
+A basic implementation of FAST (Features from Accelerated Segment Test) algorithm for high-speed corner detection.

FlannFeatureMatcher/README.md

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+# FLANN Matcher
+
+Implementation of FLANN (Fast Library for Approximate Nearest Neighbors) to match features in one image with others.

FourierTransformation/README.md

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+# Fourier Transformation
+
+A minimal Implementation of Fourier Transformation.

GrabCutAlgorithm/README.md

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+# GrabCut Algorithm
+
+Implementation of Foreground Extraction using GrabCut Algorithm.

HarrisCornerDetection/README.md

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+# Harris Corner Detection
+
+Harris Corner Detector is a corner detection operator that is commonly used in computer vision algorithms to extract corners and infer features of an image.

Homography/README.md

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+# Homography
+
+A minimal implementation of Homograpgy with Feature Matching to find known objects in a complex image.

HoughTransformation/README.md

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+# Hough Transformation
+
+A minimal Iimplementation of the following:
+
+- Hough Line Transformation
+- Probabilistic Hough Line Transformation
+- Hough Circle Transformation

ImageBlending/README.md

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+# Image Blending
+
+Using Pyramids menthod to Blend Images. 

ImagePyramids/README.md

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+# Image Pyramids
+
+Implementation of Image Pyramiding upto 5 levels.

ImageResize/Readme.md

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+This function Resize the images.

ImageSmoothing/README.md

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+# Image Soothing
+
+Implementation of the following Imgae Soothing approaches:
+
+* Gaussian Filtering 
+* Median Filtering
+* Bilateral Filtering

Image_Cartoonification/Readme.md

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+ Implementing Cartoonifying the images.

LICENSE

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+MIT License
+
+Copyright (c) 2021 Aditya Kumar Gupta
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

Meanshift/README.md

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+# Meanshift Algorithm
+
+Implementation of Meanshift to find and track objects in videos.

OCR_HandwrittenAlphabet/Readme.md

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+Using OpenCV and kNN to build a basic OCR (Optical Character Recognition) application for hand-written Alphabets.

OCR_HandwrittenDigit/Readme.md

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+Using OpeCV and KNN to build a basic OCR (Optical Character Recognition) application for Hand-written Digits.