From 80f868fba060a44ed9b216436c579766d67730b2 Mon Sep 17 00:00:00 2001 From: Srimonti Dutta Date: Mon, 29 Mar 2021 00:05:48 +0530 Subject: [PATCH 1/2] Added Jupyter, image and readme files for hole detection --- Hole_Detection/Hole_Detection.ipynb | 213 ++++++++++++++++++++++++++++ Hole_Detection/Images/sample1.jpg | Bin 0 -> 238119 bytes Hole_Detection/Images/sample2.jpg | Bin 0 -> 48520 bytes Hole_Detection/Images/sample3.jpg | Bin 0 -> 44711 bytes Hole_Detection/README.md | 21 +++ 5 files changed, 234 insertions(+) create mode 100644 Hole_Detection/Hole_Detection.ipynb create mode 100644 Hole_Detection/Images/sample1.jpg create mode 100644 Hole_Detection/Images/sample2.jpg create mode 100644 Hole_Detection/Images/sample3.jpg create mode 100644 Hole_Detection/README.md diff --git a/Hole_Detection/Hole_Detection.ipynb b/Hole_Detection/Hole_Detection.ipynb new file mode 100644 index 00000000..5b21799c --- /dev/null +++ b/Hole_Detection/Hole_Detection.ipynb @@ -0,0 +1,213 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Importing Libraries" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import cv2\n", + "import numpy as np" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Reading Input Images" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "img1 = cv2.imread(\"C:\\\\Users\\\\Srimonti\\\\Documents\\GSSoC21\\\\Hole_Detection\\\\sample1.jpg\",1);\n", + "img2 = cv2.imread(\"C:\\\\Users\\\\Srimonti\\\\Documents\\GSSoC21\\\\Hole_Detection\\\\sample2.jpg\",1);\n", + "img3 = cv2.imread(\"C:\\\\Users\\\\Srimonti\\\\Documents\\GSSoC21\\\\Hole_Detection\\\\sample3.jpg\",1);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Converting Input Images to Grayscale" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "grey1 = cv2.cvtColor(img1,cv2.COLOR_BGR2GRAY)\n", + "grey2 = cv2.cvtColor(img2,cv2.COLOR_BGR2GRAY)\n", + "grey3 = cv2.cvtColor(img3,cv2.COLOR_BGR2GRAY)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Performing Gaussian Blurring" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "gauss1 = cv2.GaussianBlur(img1,(5,5),200)\n", + "gauss2 = cv2.GaussianBlur(img2,(5,5),200)\n", + "gauss3 = cv2.GaussianBlur(img3,(5,5),200)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Threshold Detection" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "ret,thresh1 = cv2.threshold(gauss1,127,255,0)\n", + "ret,thresh2 = cv2.threshold(gauss2,127,255,0)\n", + "ret,thresh3 = cv2.threshold(gauss3,127,255,0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Performing Blob Detection" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "detector = cv2.SimpleBlobDetector_create()\n", + "keypoint1 = detector.detect(thresh1);\n", + "imgkeypoint1 = cv2.drawKeypoints(thresh1,keypoint1,np.array([]),(0,255,0),cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)\n", + "keypoint2 = detector.detect(thresh2);\n", + "imgkeypoint2= cv2.drawKeypoints(thresh2,keypoint2,np.array([]),(0,255,0),cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)\n", + "keypoint3 = detector.detect(thresh3);\n", + "imgkeypoint3 = cv2.drawKeypoints(thresh3,keypoint3,np.array([]),(0,255,0),cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Output Image Display" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-1" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cv2.imshow(\"legend\",imgkeypoint1);\n", + "cv2.waitKey(0)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-1" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cv2.imshow(\"legend\",imgkeypoint2);\n", + "cv2.waitKey(0)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-1" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cv2.imshow(\"legend\",imgkeypoint3);\n", + "cv2.waitKey(0)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + 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If the image cannot be read (because of missing file, improper permissions, unsupported or invalid format) then this method returns an empty matrix. + +#### cvtColor() +cv2.cvtColor() method is used to convert an image from one color space to another. There are more than 150 color-space conversion methods available in OpenCV. + +#### GaussianBlur() +In the Gaussian Blur operation, the image is convolved with a Gaussian filter instead of the box filter. The Gaussian filter is a low-pass filter that removes the high-frequency components are reduced. It also smoothens or blurs the image. You can perform this operation on an image using the Gaussianblur() method of the imgproc class. Gaussian blurring is highly effective in removing Gaussian noise from an image. + +#### cv2.threshold() +If pixel value is greater than a threshold value, it is assigned one value (may be white), else it is assigned another value (may be black). The function used is cv2.threshold. First argument is the source image, which should be a grayscale image. Second argument is the threshold value which is used to classify the pixel values. Third argument is the maxVal which represents the value to be given if pixel value is more than (sometimes less than) the threshold value. + +#### cv2.SimpleBlobDetector_create() +SimpleBlobDetector is an algorithm which is controlled by parameters in the following way- + +Thresholding : Convert the source images to several binary images by thresholding the source image with thresholds starting at minThreshold. These thresholds are incremented by thresholdStep until maxThreshold. So the first threshold is minThreshold, the second is minThreshold + thresholdStep, the third is minThreshold + 2 x thresholdStep, and so on. +Grouping : In each binary image, connected white pixels are grouped together. Let’s call these binary blobs. +Merging : The centers of the binary blobs in the binary images are computed, and blobs located closer than minDistBetweenBlobs are merged. +Center & Radius Calculation : The centers and radii of the new merged blobs are computed and returned. \ No newline at end of file From 0293eab1d6748982084269e973d9240a43eb4196 Mon Sep 17 00:00:00 2001 From: Srimonti Dutta Date: Fri, 9 Apr 2021 18:45:53 +0530 Subject: [PATCH 2/2] Added input and output images for issue-91 --- .../{Images => Input Images}/sample1.jpg | Bin .../{Images => Input Images}/sample2.jpg | Bin .../{Images => Input Images}/sample3.jpg | Bin Hole_Detection/Output Images/sample1.PNG | Bin 0 -> 23218 bytes Hole_Detection/Output Images/sample2.PNG | Bin 0 -> 31318 bytes Hole_Detection/Output Images/sample3.PNG | Bin 0 -> 29627 bytes 6 files changed, 0 insertions(+), 0 deletions(-) rename Hole_Detection/{Images => Input Images}/sample1.jpg (100%) rename Hole_Detection/{Images => Input Images}/sample2.jpg (100%) rename Hole_Detection/{Images => Input Images}/sample3.jpg (100%) create mode 100644 Hole_Detection/Output Images/sample1.PNG create mode 100644 Hole_Detection/Output Images/sample2.PNG create mode 100644 Hole_Detection/Output Images/sample3.PNG diff --git a/Hole_Detection/Images/sample1.jpg b/Hole_Detection/Input Images/sample1.jpg similarity index 100% rename from Hole_Detection/Images/sample1.jpg rename to Hole_Detection/Input Images/sample1.jpg diff --git a/Hole_Detection/Images/sample2.jpg b/Hole_Detection/Input Images/sample2.jpg similarity index 100% rename from Hole_Detection/Images/sample2.jpg rename to Hole_Detection/Input Images/sample2.jpg diff --git a/Hole_Detection/Images/sample3.jpg b/Hole_Detection/Input Images/sample3.jpg similarity index 100% rename from Hole_Detection/Images/sample3.jpg rename to Hole_Detection/Input Images/sample3.jpg diff --git a/Hole_Detection/Output Images/sample1.PNG b/Hole_Detection/Output Images/sample1.PNG new file 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