├── .gitattributes ├── .gitignore ├── LicensePlateRecoginition.ipynb ├── QR CODE Scanner.ipynb ├── VPen.ipynb ├── Virtual Pen ├── VPen.ipynb ├── finding HSV value (screenshot).png ├── finding HSV values.ipynb ├── hsv_value.npy ├── virtual pen demo.mp4 └── virtual pen on action(screenshot).png ├── cartooning and sketching live app .ipynb ├── cartoonizing an image using opencv.ipynb ├── color detection ├── color detection.ipynb ├── color palette.jpg └── colors.csv ├── color palette using OpenCV.ipynb ├── contrast enhancing of color images using opencv.ipynb ├── contrast enhancing of gray scale image using opencv.ipynb ├── document scanner.ipynb ├── draw vertical lines on coin.ipynb ├── face detection using opencv.ipynb ├── image bluring using opencv python.ipynb ├── image resizing using opencv.ipynb ├── image segmentation.ipynb ├── invisible cloak.ipynb ├── motion blurring effect .ipynb ├── negative flim.ipynb ├── noise removing using opencv.ipynb ├── non-photorealistic rendering .ipynb ├── number plate detection.ipynb ├── object tracking using OpenCV.ipynb ├── pencil drawing effect.ipynb ├── reversing video using opencv.ipynb ├── sharpening of images using opencv.ipynb ├── thresholding techniques.ipynb └── watermarking on images using OpenCV.ipynb /.gitattributes: -------------------------------------------------------------------------------- 1 | # Auto detect text files and perform LF normalization 2 | * text=auto 3 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script from a template 32 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 33 | *.manifest 34 | *.spec 35 | 36 | # Installer logs 37 | pip-log.txt 38 | pip-delete-this-directory.txt 39 | 40 | # Unit test / coverage reports 41 | htmlcov/ 42 | .tox/ 43 | .nox/ 44 | .coverage 45 | .coverage.* 46 | .cache 47 | nosetests.xml 48 | coverage.xml 49 | *.cover 50 | *.py,cover 51 | .hypothesis/ 52 | .pytest_cache/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | target/ 76 | 77 | # Jupyter Notebook 78 | .ipynb_checkpoints 79 | 80 | # IPython 81 | profile_default/ 82 | ipython_config.py 83 | 84 | # pyenv 85 | .python-version 86 | 87 | # pipenv 88 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 89 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 90 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 91 | # install all needed dependencies. 92 | #Pipfile.lock 93 | 94 | # celery beat schedule file 95 | celerybeat-schedule 96 | 97 | # SageMath parsed files 98 | *.sage.py 99 | 100 | # Environments 101 | .env 102 | .venv 103 | env/ 104 | venv/ 105 | ENV/ 106 | env.bak/ 107 | venv.bak/ 108 | 109 | # Spyder project settings 110 | .spyderproject 111 | .spyproject 112 | 113 | # Rope project settings 114 | .ropeproject 115 | 116 | # mkdocs documentation 117 | /site 118 | 119 | # mypy 120 | .mypy_cache/ 121 | .dmypy.json 122 | dmypy.json 123 | 124 | # Pyre type checker 125 | .pyre/ 126 | -------------------------------------------------------------------------------- /LicensePlateRecoginition.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "follow on insta\n", 8 | "@programmimg_fever" 9 | ] 10 | }, 11 | { 12 | "cell_type": "markdown", 13 | "metadata": {}, 14 | "source": [ 15 | "# LicensePlateRecognition using OpenCV python" 16 | ] 17 | }, 18 | { 19 | "cell_type": "code", 20 | "execution_count": null, 21 | "metadata": {}, 22 | "outputs": [ 23 | { 24 | "name": "stdout", 25 | "output_type": "stream", 26 | "text": [ 27 | "programming_fever's License Plate Recognition\n", 28 | "\n", 29 | "Detected license plate Number is: MH 20 EE 7598\n" 30 | ] 31 | } 32 | ], 33 | "source": [ 34 | "import cv2\n", 35 | "import imutils\n", 36 | "import numpy as np\n", 37 | "import pytesseract\n", 38 | "pytesseract.pytesseract.tesseract_cmd = r'C:\\Program Files (x86)\\Tesseract-OCR\\tesseract.exe'\n", 39 | "\n", 40 | "img = cv2.imread('D://skoda1.jpg',cv2.IMREAD_COLOR)\n", 41 | "img = cv2.resize(img, (600,400) )\n", 42 | "\n", 43 | "gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) \n", 44 | "gray = cv2.bilateralFilter(gray, 13, 15, 15) \n", 45 | "\n", 46 | "edged = cv2.Canny(gray, 30, 200) \n", 47 | "contours = cv2.findContours(edged.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)\n", 48 | "contours = imutils.grab_contours(contours)\n", 49 | "contours = sorted(contours, key = cv2.contourArea, reverse = True)[:10]\n", 50 | "screenCnt = None\n", 51 | "\n", 52 | "for c in contours:\n", 53 | " \n", 54 | " peri = cv2.arcLength(c, True)\n", 55 | " approx = cv2.approxPolyDP(c, 0.018 * peri, True)\n", 56 | " \n", 57 | " if len(approx) == 4:\n", 58 | " screenCnt = approx\n", 59 | " break\n", 60 | "\n", 61 | "if screenCnt is None:\n", 62 | " detected = 0\n", 63 | " print (\"No contour detected\")\n", 64 | "else:\n", 65 | " detected = 1\n", 66 | "\n", 67 | "if detected == 1:\n", 68 | " cv2.drawContours(img, [screenCnt], -1, (0, 0, 255), 3)\n", 69 | "\n", 70 | "mask = np.zeros(gray.shape,np.uint8)\n", 71 | "new_image = cv2.drawContours(mask,[screenCnt],0,255,-1,)\n", 72 | "new_image = cv2.bitwise_and(img,img,mask=mask)\n", 73 | "\n", 74 | "(x, y) = np.where(mask == 255)\n", 75 | "(topx, topy) = (np.min(x), np.min(y))\n", 76 | "(bottomx, bottomy) = (np.max(x), np.max(y))\n", 77 | "Cropped = gray[topx:bottomx+1, topy:bottomy+1]\n", 78 | "\n", 79 | "text = pytesseract.image_to_string(Cropped, config='--psm 11')\n", 80 | "print(\"programming_fever's License Plate Recognition\\n\")\n", 81 | "print(\"Detected license plate Number is:\",text)\n", 82 | "img = cv2.resize(img,(500,300))\n", 83 | "Cropped = cv2.resize(Cropped,(400,200))\n", 84 | "cv2.imshow('car',img)\n", 85 | "cv2.imshow('Cropped',Cropped)\n", 86 | "\n", 87 | "cv2.waitKey(0)\n", 88 | "cv2.destroyAllWindows()" 89 | ] 90 | }, 91 | { 92 | "cell_type": "markdown", 93 | "metadata": {}, 94 | "source": [ 95 | "you can find code description @medium publication\n", 96 | "@programmimg_fever" 97 | ] 98 | }, 99 | { 100 | "cell_type": "code", 101 | "execution_count": null, 102 | "metadata": {}, 103 | "outputs": [], 104 | "source": [] 105 | } 106 | ], 107 | "metadata": { 108 | "kernelspec": { 109 | "display_name": "Python 3", 110 | "language": "python", 111 | "name": "python3" 112 | }, 113 | "language_info": { 114 | "codemirror_mode": { 115 | "name": "ipython", 116 | "version": 3 117 | }, 118 | "file_extension": ".py", 119 | "mimetype": "text/x-python", 120 | "name": "python", 121 | "nbconvert_exporter": "python", 122 | "pygments_lexer": "ipython3", 123 | "version": "3.7.6" 124 | } 125 | }, 126 | "nbformat": 4, 127 | "nbformat_minor": 4 128 | } 129 | -------------------------------------------------------------------------------- /QR CODE Scanner.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# QR code Scanner" 8 | ] 9 | }, 10 | { 11 | "cell_type": "code", 12 | "execution_count": null, 13 | "metadata": {}, 14 | "outputs": [ 15 | { 16 | "name": "stdout", 17 | "output_type": "stream", 18 | "text": [ 19 | "Decoded Data : https://www.instagram.com/programming_fever/\n", 20 | "[[[ 40. 40.]]\n", 21 | "\n", 22 | " [[369. 40.]]\n", 23 | "\n", 24 | " [[369. 369.]]\n", 25 | "\n", 26 | " [[ 40. 369.]]]\n" 27 | ] 28 | } 29 | ], 30 | "source": [ 31 | "#programming_fever\n", 32 | "import cv2\n", 33 | "import numpy as np\n", 34 | "import sys\n", 35 | "import time\n", 36 | "\n", 37 | "inputImage = cv2.imread(\"D://OpenCV//opencv jupyter files//programming_fever.png\")\n", 38 | "# Display barcode and QR code location\n", 39 | "def display(im, bbox):\n", 40 | " n = len(bbox)\n", 41 | " for j in range(n):\n", 42 | " cv2.line(im, tuple(bbox[j][0]), tuple(bbox[ (j+1) % n][0]), (255,0,0), 3)\n", 43 | "\n", 44 | " # Display results\n", 45 | " cv2.imshow(\"Results\", im)\n", 46 | " \n", 47 | "qrDecoder = cv2.QRCodeDetector()\n", 48 | "# Detect and decode the qrcode\n", 49 | "data,bbox,rectifiedImage = qrDecoder.detectAndDecode(inputImage)\n", 50 | "if len(data)>0:\n", 51 | " print(\"Decoded Data : {}\".format(data))\n", 52 | " display(inputImage, bbox)\n", 53 | " rectifiedImage = np.uint8(rectifiedImage)\n", 54 | " cv2.imshow(\"Rectified QRCode\", rectifiedImage)\n", 55 | "\n", 56 | "else:\n", 57 | " print(\"QR Code not detected\")\n", 58 | " cv2.imshow(\"Results\", inputImage)\n", 59 | "\n", 60 | "cv2.waitKey(0)\n", 61 | "cv2.destroyAllWindows()\n", 62 | "\n" 63 | ] 64 | }, 65 | { 66 | "cell_type": "markdown", 67 | "metadata": {}, 68 | "source": [ 69 | "FB Page\n", 70 | "@programmimg_fever" 71 | ] 72 | }, 73 | { 74 | "cell_type": "markdown", 75 | "metadata": {}, 76 | "source": [ 77 | "GitHub link\n", 78 | "@programmimg_fever" 79 | ] 80 | }, 81 | { 82 | "cell_type": "markdown", 83 | "metadata": {}, 84 | "source": [ 85 | "Twitter \n", 86 | "@programmimg_fever" 87 | ] 88 | } 89 | ], 90 | "metadata": { 91 | "kernelspec": { 92 | "display_name": "Python 3", 93 | "language": "python", 94 | "name": "python3" 95 | }, 96 | "language_info": { 97 | "codemirror_mode": { 98 | "name": "ipython", 99 | "version": 3 100 | }, 101 | "file_extension": ".py", 102 | "mimetype": "text/x-python", 103 | "name": "python", 104 | "nbconvert_exporter": "python", 105 | "pygments_lexer": "ipython3", 106 | "version": "3.7.6" 107 | } 108 | }, 109 | "nbformat": 4, 110 | "nbformat_minor": 4 111 | } 112 | -------------------------------------------------------------------------------- /VPen.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# VIRTUAL PEN USING OPENCV PYTHON" 8 | ] 9 | }, 10 | { 11 | "cell_type": "code", 12 | "execution_count": null, 13 | "metadata": {}, 14 | "outputs": [], 15 | "source": [] 16 | }, 17 | { 18 | "cell_type": "code", 19 | "execution_count": 1, 20 | "metadata": {}, 21 | "outputs": [ 22 | { 23 | "ename": "FileNotFoundError", 24 | "evalue": "[Errno 2] No such file or directory: 'hsv value.npy'", 25 | "output_type": "error", 26 | "traceback": [ 27 | "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", 28 | "\u001b[1;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", 29 | "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[0mload_from_disk\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mload_from_disk\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 8\u001b[1;33m \u001b[0mhsv_value\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'hsv value.npy'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 10\u001b[0m \u001b[0mcap\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcv2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mVideoCapture\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", 30 | "\u001b[1;32mE:\\Anaconda\\lib\\site-packages\\numpy\\lib\\npyio.py\u001b[0m in \u001b[0;36mload\u001b[1;34m(file, mmap_mode, allow_pickle, fix_imports, encoding)\u001b[0m\n\u001b[0;32m 426\u001b[0m \u001b[0mown_fid\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 427\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 428\u001b[1;33m \u001b[0mfid\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mos_fspath\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfile\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"rb\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 429\u001b[0m \u001b[0mown_fid\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 430\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", 31 | "\u001b[1;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'hsv value.npy'" 32 | ] 33 | } 34 | ], 35 | "source": [ 36 | "#programming_fever\n", 37 | "import cv2\n", 38 | "import numpy as np\n", 39 | "import time\n", 40 | "\n", 41 | "load_from_disk = True\n", 42 | "if load_from_disk:\n", 43 | " hsv_value = np.load('hsv_value.npy')\n", 44 | "\n", 45 | "cap = cv2.VideoCapture(0)\n", 46 | "cap.set(3,1280)\n", 47 | "cap.set(4,720)\n", 48 | "\n", 49 | "kernel = np.ones((5,5),np.uint8)\n", 50 | "\n", 51 | "# Initializing the canvas on which we will draw upon\n", 52 | "canvas = None\n", 53 | "\n", 54 | "# Initilize x1,y1 points\n", 55 | "x1,y1=0,0\n", 56 | "\n", 57 | "# Threshold for noise\n", 58 | "noiseth = 800\n", 59 | "\n", 60 | "while(1):\n", 61 | " _, frame = cap.read()\n", 62 | " frame = cv2.flip( frame, 1 )\n", 63 | " \n", 64 | " # Initialize the canvas as a black image of the same size as the frame.\n", 65 | " if canvas is None:\n", 66 | " canvas = np.zeros_like(frame)\n", 67 | "\n", 68 | " # Convert BGR to HSV\n", 69 | " hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)\n", 70 | " \n", 71 | " # If you're reading from memory then load the upper and lower ranges \n", 72 | " # from there\n", 73 | " if load_from_disk:\n", 74 | " lower_range = hsv_value[0]\n", 75 | " upper_range = hsv_value[1]\n", 76 | " \n", 77 | " # Otherwise define your own custom values for upper and lower range.\n", 78 | " #else: [[92, 116, 150], [179, 255, 255]]\n", 79 | " lower_range = np.array([134, 20, 204])\n", 80 | " upper_range = np.array([179, 255, 255])\n", 81 | " \n", 82 | " mask = cv2.inRange(hsv, lower_range, upper_range)\n", 83 | " \n", 84 | " # Perform morphological operations to get rid of the noise\n", 85 | " mask = cv2.erode(mask,kernel,iterations = 1)\n", 86 | " mask = cv2.dilate(mask,kernel,iterations = 2)\n", 87 | " \n", 88 | " # Find Contours\n", 89 | " contours, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n", 90 | " \n", 91 | " # Make sure there is a contour present and also its size is bigger than \n", 92 | " # the noise threshold.\n", 93 | " if contours and cv2.contourArea(max(contours, \n", 94 | " key = cv2.contourArea)) > noiseth:\n", 95 | " \n", 96 | " c = max(contours, key = cv2.contourArea) \n", 97 | " x2,y2,w,h = cv2.boundingRect(c)\n", 98 | " \n", 99 | " # If there were no previous points then save the detected x2,y2 \n", 100 | " # coordinates as x1,y1. \n", 101 | " # This is true when we writing for the first time or when writing \n", 102 | " # again when the pen had disappeared from view.\n", 103 | " if x1 == 0 and y1 == 0:\n", 104 | " x1,y1= x2,y2\n", 105 | " \n", 106 | " else:\n", 107 | " # Draw the line on the canvas\n", 108 | " canvas = cv2.line(canvas, (x1,y1),(x2,y2), [255,0,0], 4)\n", 109 | " \n", 110 | " # After the line is drawn the new points become the previous points.\n", 111 | " x1,y1= x2,y2\n", 112 | "\n", 113 | " else:\n", 114 | " # If there were no contours detected then make x1,y1 = 0\n", 115 | " x1,y1 =0,0\n", 116 | " \n", 117 | " # Merge the canvas and the frame.\n", 118 | " frame = cv2.add(frame,canvas)\n", 119 | " \n", 120 | " # Optionally stack both frames and show it.\n", 121 | " stacked = np.hstack((canvas,frame))\n", 122 | " cv2.imshow('Trackbars',cv2.resize(stacked,None,fx=0.6,fy=0.6))\n", 123 | "\n", 124 | " k = cv2.waitKey(1) & 0xFF\n", 125 | " if k == 27:\n", 126 | " break\n", 127 | " \n", 128 | " # When c is pressed clear the canvas\n", 129 | " if k == ord('c'):\n", 130 | " canvas = None\n", 131 | "\n", 132 | "cv2.destroyAllWindows()\n", 133 | "cap.release()\n" 134 | ] 135 | }, 136 | { 137 | "cell_type": "markdown", 138 | "metadata": {}, 139 | "source": [ 140 | "# FB Page\n", 141 | "@programmimg_fever" 142 | ] 143 | }, 144 | { 145 | "cell_type": "markdown", 146 | "metadata": {}, 147 | "source": [ 148 | "# GitHub link\n", 149 | "@programmimg_fever" 150 | ] 151 | }, 152 | { 153 | "cell_type": "markdown", 154 | "metadata": {}, 155 | "source": [ 156 | "# Twitter \n", 157 | "@programmimg_fever" 158 | ] 159 | }, 160 | { 161 | "cell_type": "markdown", 162 | "metadata": {}, 163 | "source": [ 164 | "# follow on insta\n", 165 | "@programmimg_fever" 166 | ] 167 | } 168 | ], 169 | "metadata": { 170 | "kernelspec": { 171 | "display_name": "Python 3", 172 | "language": "python", 173 | "name": "python3" 174 | }, 175 | "language_info": { 176 | "codemirror_mode": { 177 | "name": "ipython", 178 | "version": 3 179 | }, 180 | "file_extension": ".py", 181 | "mimetype": "text/x-python", 182 | "name": "python", 183 | "nbconvert_exporter": "python", 184 | "pygments_lexer": "ipython3", 185 | "version": "3.7.6" 186 | } 187 | }, 188 | "nbformat": 4, 189 | "nbformat_minor": 4 190 | } 191 | -------------------------------------------------------------------------------- /Virtual Pen/VPen.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# VIRTUAL PEN USING OPENCV PYTHON" 8 | ] 9 | }, 10 | { 11 | "cell_type": "markdown", 12 | "metadata": {}, 13 | "source": [ 14 | "code description is available in medium \n", 15 | "@programmimg_fever" 16 | ] 17 | }, 18 | { 19 | "cell_type": "code", 20 | "execution_count": null, 21 | "metadata": {}, 22 | "outputs": [], 23 | "source": [ 24 | "#programming_fever\n", 25 | "import cv2\n", 26 | "import numpy as np\n", 27 | "import time\n", 28 | "\n", 29 | "load_from_disk = True\n", 30 | "if load_from_disk:\n", 31 | " hsv_value = np.load('hsv_value.npy')\n", 32 | "\n", 33 | "cap = cv2.VideoCapture(0)\n", 34 | "cap.set(3,1280)\n", 35 | "cap.set(4,720)\n", 36 | "\n", 37 | "kernel = np.ones((5,5),np.uint8)\n", 38 | "\n", 39 | "# Initializing the canvas on which we will draw upon\n", 40 | "canvas = None\n", 41 | "\n", 42 | "# Initilize x1,y1 points\n", 43 | "x1,y1=0,0\n", 44 | "\n", 45 | "# Threshold for noise\n", 46 | "noiseth = 800\n", 47 | "\n", 48 | "while(1):\n", 49 | " _, frame = cap.read()\n", 50 | " frame = cv2.flip( frame, 1 )\n", 51 | " \n", 52 | " # Initialize the canvas as a black image of the same size as the frame.\n", 53 | " if canvas is None:\n", 54 | " canvas = np.zeros_like(frame)\n", 55 | "\n", 56 | " # Convert BGR to HSV\n", 57 | " hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)\n", 58 | " \n", 59 | " # If you're reading from memory then load the upper and lower ranges \n", 60 | " # from there\n", 61 | " if load_from_disk:\n", 62 | " lower_range = hsv_value[0]\n", 63 | " upper_range = hsv_value[1]\n", 64 | " \n", 65 | " # Otherwise define your own custom values for upper and lower range.\n", 66 | " else: \n", 67 | " lower_range = np.array([134, 20, 204])\n", 68 | " upper_range = np.array([179, 255, 255])\n", 69 | " \n", 70 | " mask = cv2.inRange(hsv, lower_range, upper_range)\n", 71 | " \n", 72 | " # Perform morphological operations to get rid of the noise\n", 73 | " mask = cv2.erode(mask,kernel,iterations = 1)\n", 74 | " mask = cv2.dilate(mask,kernel,iterations = 2)\n", 75 | " \n", 76 | " # Find Contours\n", 77 | " contours, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n", 78 | " \n", 79 | " # Make sure there is a contour present and also its size is bigger than \n", 80 | " # the noise threshold.\n", 81 | " if contours and cv2.contourArea(max(contours, \n", 82 | " key = cv2.contourArea)) > noiseth:\n", 83 | " \n", 84 | " c = max(contours, key = cv2.contourArea) \n", 85 | " x2,y2,w,h = cv2.boundingRect(c)\n", 86 | " \n", 87 | " # If there were no previous points then save the detected x2,y2 \n", 88 | " # coordinates as x1,y1. \n", 89 | " # This is true when we writing for the first time or when writing \n", 90 | " # again when the pen had disappeared from view.\n", 91 | " if x1 == 0 and y1 == 0:\n", 92 | " x1,y1= x2,y2\n", 93 | " \n", 94 | " else:\n", 95 | " # Draw the line on the canvas\n", 96 | " canvas = cv2.line(canvas, (x1,y1),(x2,y2), [255,0,0], 4)\n", 97 | " \n", 98 | " # After the line is drawn the new points become the previous points.\n", 99 | " x1,y1= x2,y2\n", 100 | "\n", 101 | " else:\n", 102 | " # If there were no contours detected then make x1,y1 = 0\n", 103 | " x1,y1 =0,0\n", 104 | " \n", 105 | " # Merge the canvas and the frame.\n", 106 | " frame = cv2.add(frame,canvas)\n", 107 | " \n", 108 | " # Optionally stack both frames and show it.\n", 109 | " stacked = np.hstack((canvas,frame))\n", 110 | " cv2.imshow('VIRTUAL PEN',cv2.resize(stacked,None,fx=0.6,fy=0.6))\n", 111 | "\n", 112 | " k = cv2.waitKey(1) & 0xFF\n", 113 | " if k == 27:\n", 114 | " break\n", 115 | " \n", 116 | " # When c is pressed clear the canvas\n", 117 | " if k == ord('c'):\n", 118 | " canvas = None\n", 119 | "\n", 120 | "cv2.destroyAllWindows()\n", 121 | "cap.release()\n" 122 | ] 123 | }, 124 | { 125 | "cell_type": "markdown", 126 | "metadata": {}, 127 | "source": [ 128 | "# FB Page\n", 129 | "@programmimg_fever" 130 | ] 131 | }, 132 | { 133 | "cell_type": "markdown", 134 | "metadata": {}, 135 | "source": [ 136 | "# GitHub link\n", 137 | "@programmimg_fever" 138 | ] 139 | }, 140 | { 141 | "cell_type": "markdown", 142 | "metadata": {}, 143 | "source": [ 144 | "# Twitter \n", 145 | "@programmimg_fever" 146 | ] 147 | }, 148 | { 149 | "cell_type": "markdown", 150 | "metadata": {}, 151 | "source": [ 152 | "# follow on insta\n", 153 | "@programmimg_fever" 154 | ] 155 | }, 156 | { 157 | "cell_type": "code", 158 | "execution_count": null, 159 | "metadata": {}, 160 | "outputs": [], 161 | "source": [] 162 | } 163 | ], 164 | "metadata": { 165 | "kernelspec": { 166 | "display_name": "Python 3", 167 | "language": "python", 168 | "name": "python3" 169 | }, 170 | "language_info": { 171 | "codemirror_mode": { 172 | "name": "ipython", 173 | "version": 3 174 | }, 175 | "file_extension": ".py", 176 | "mimetype": "text/x-python", 177 | "name": "python", 178 | "nbconvert_exporter": "python", 179 | "pygments_lexer": "ipython3", 180 | "version": "3.7.6" 181 | } 182 | }, 183 | "nbformat": 4, 184 | "nbformat_minor": 4 185 | } 186 | -------------------------------------------------------------------------------- /Virtual Pen/finding HSV value (screenshot).png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GeekyPRAVEE/OpenCV-Projects/505fbbd86fc1281a870b3427555aff148aa44a08/Virtual Pen/finding HSV value (screenshot).png -------------------------------------------------------------------------------- /Virtual Pen/finding HSV values.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# to find HSV value" 8 | ] 9 | }, 10 | { 11 | "cell_type": "code", 12 | "execution_count": null, 13 | "metadata": {}, 14 | "outputs": [], 15 | "source": [ 16 | "import cv2\n", 17 | "import numpy as np\n", 18 | "import time\n", 19 | "# A required callback method that goes into the trackbar function.\n", 20 | "def nothing(x):\n", 21 | " pass\n", 22 | "\n", 23 | "# Initializing the webcam feed.\n", 24 | "cap = cv2.VideoCapture(0)\n", 25 | "cap.set(3,1280)\n", 26 | "cap.set(4,720)\n", 27 | "\n", 28 | "# Create a window named trackbars.\n", 29 | "cv2.namedWindow(\"Trackbars\")\n", 30 | "\n", 31 | "# Now create 6 trackbars that will control the lower and upper range of \n", 32 | "# H,S and V channels. The Arguments are like this: Name of trackbar, \n", 33 | "# window name, range,callback function. For Hue the range is 0-179 and\n", 34 | "# for S,V its 0-255.\n", 35 | "cv2.createTrackbar(\"L - H\", \"Trackbars\", 0, 179, nothing)\n", 36 | "cv2.createTrackbar(\"L - S\", \"Trackbars\", 0, 255, nothing)\n", 37 | "cv2.createTrackbar(\"L - V\", \"Trackbars\", 0, 255, nothing)\n", 38 | "cv2.createTrackbar(\"U - H\", \"Trackbars\", 179, 179, nothing)\n", 39 | "cv2.createTrackbar(\"U - S\", \"Trackbars\", 255, 255, nothing)\n", 40 | "cv2.createTrackbar(\"U - V\", \"Trackbars\", 255, 255, nothing)\n", 41 | " \n", 42 | "while True:\n", 43 | " \n", 44 | " # Start reading the webcam feed frame by frame.\n", 45 | " ret, frame = cap.read()\n", 46 | " if not ret:\n", 47 | " break\n", 48 | " # Flip the frame horizontally (Not required)\n", 49 | " frame = cv2.flip( frame, 1 ) \n", 50 | " \n", 51 | " # Convert the BGR image to HSV image.\n", 52 | " hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)\n", 53 | " \n", 54 | " # Get the new values of the trackbar in real time as the user changes \n", 55 | " # them\n", 56 | " l_h = cv2.getTrackbarPos(\"L - H\", \"Trackbars\")\n", 57 | " l_s = cv2.getTrackbarPos(\"L - S\", \"Trackbars\")\n", 58 | " l_v = cv2.getTrackbarPos(\"L - V\", \"Trackbars\")\n", 59 | " u_h = cv2.getTrackbarPos(\"U - H\", \"Trackbars\")\n", 60 | " u_s = cv2.getTrackbarPos(\"U - S\", \"Trackbars\")\n", 61 | " u_v = cv2.getTrackbarPos(\"U - V\", \"Trackbars\")\n", 62 | " \n", 63 | " # Set the lower and upper HSV range according to the value selected\n", 64 | " # by the trackbar\n", 65 | " lower_range = np.array([l_h, l_s, l_v])\n", 66 | " upper_range = np.array([u_h, u_s, u_v])\n", 67 | " \n", 68 | " # Filter the image and get the binary mask, where white represents \n", 69 | " # your target color\n", 70 | " mask = cv2.inRange(hsv, lower_range, upper_range)\n", 71 | " \n", 72 | " # You can also visualize the real part of the target color (Optional)\n", 73 | " res = cv2.bitwise_and(frame, frame, mask=mask)\n", 74 | " \n", 75 | " # Converting the binary mask to 3 channel image, this is just so \n", 76 | " # we can stack it with the others\n", 77 | " mask_3 = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)\n", 78 | " \n", 79 | " # stack the mask, orginal frame and the filtered result\n", 80 | " stacked = np.hstack((mask_3,frame,res))\n", 81 | " \n", 82 | " # Show this stacked frame at 40% of the size.\n", 83 | " cv2.imshow('Trackbars',cv2.resize(stacked,None,fx=0.4,fy=0.4))\n", 84 | " \n", 85 | " # If the user presses ESC then exit the program\n", 86 | " key = cv2.waitKey(1)\n", 87 | " if key == 27:\n", 88 | " break\n", 89 | " \n", 90 | " # If the user presses `s` then print this array.\n", 91 | " if key == ord('s'):\n", 92 | " \n", 93 | " thearray = [[l_h,l_s,l_v],[u_h, u_s, u_v]]\n", 94 | " print(thearray)\n", 95 | " \n", 96 | " # Also save this array as penval.npy\n", 97 | " np.save('hsv values',thearray)\n", 98 | " break\n", 99 | " \n", 100 | "# Release the camera & destroy the windows. \n", 101 | "cap.release()\n", 102 | "cv2.destroyAllWindows()" 103 | ] 104 | } 105 | ], 106 | "metadata": { 107 | "kernelspec": { 108 | "display_name": "Python 3", 109 | "language": "python", 110 | "name": "python3" 111 | }, 112 | "language_info": { 113 | "codemirror_mode": { 114 | "name": "ipython", 115 | "version": 3 116 | }, 117 | "file_extension": ".py", 118 | "mimetype": "text/x-python", 119 | "name": "python", 120 | "nbconvert_exporter": "python", 121 | "pygments_lexer": "ipython3", 122 | "version": "3.7.6" 123 | } 124 | }, 125 | "nbformat": 4, 126 | "nbformat_minor": 4 127 | } 128 | -------------------------------------------------------------------------------- /Virtual Pen/hsv_value.npy: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GeekyPRAVEE/OpenCV-Projects/505fbbd86fc1281a870b3427555aff148aa44a08/Virtual Pen/hsv_value.npy -------------------------------------------------------------------------------- /Virtual Pen/virtual pen demo.mp4: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GeekyPRAVEE/OpenCV-Projects/505fbbd86fc1281a870b3427555aff148aa44a08/Virtual Pen/virtual pen demo.mp4 -------------------------------------------------------------------------------- /Virtual Pen/virtual pen on action(screenshot).png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GeekyPRAVEE/OpenCV-Projects/505fbbd86fc1281a870b3427555aff148aa44a08/Virtual Pen/virtual pen on action(screenshot).png -------------------------------------------------------------------------------- /cartooning and sketching live app .ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "#press s for sketch mode\n", 11 | "#press c for caroon mode\n", 12 | "#press ENTER for normal mode\n", 13 | "import cv2\n", 14 | "import numpy as np\n", 15 | "def cartoonize_image(img, ds_factor=4, sketch_mode=False):\n", 16 | "\n", 17 | " img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n", 18 | " img_gray = cv2.medianBlur(img_gray, 7)\n", 19 | "\n", 20 | " edges = cv2.Laplacian(img_gray, cv2.CV_8U, ksize=5)\n", 21 | " ret, mask = cv2.threshold(edges, 100, 255, cv2.THRESH_BINARY_INV)\n", 22 | "\n", 23 | " if sketch_mode:\n", 24 | " return cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)\n", 25 | "\n", 26 | " img_small = cv2.resize(img, None, fx=1.0/ds_factor, fy=1.0/ds_factor , interpolation=cv2.INTER_AREA)\n", 27 | " num_repetitions = 10\n", 28 | " sigma_color = 5\n", 29 | " sigma_space = 7\n", 30 | " size = 5\n", 31 | "\n", 32 | " for i in range(num_repetitions):\n", 33 | " img_small = cv2.bilateralFilter(img_small, size, sigma_color, sigma_space)\n", 34 | " img_output = cv2.resize(img_small, None, fx=ds_factor, fy=ds_factor, interpolation=cv2.INTER_LINEAR)\n", 35 | " dst = np.zeros(img_gray.shape)\n", 36 | " dst = cv2.bitwise_and(img_output, img_output, mask=mask)\n", 37 | " return dst\n", 38 | "\n", 39 | "if __name__=='__main__':\n", 40 | " cap = cv2.VideoCapture(0)\n", 41 | " cur_char = -1\n", 42 | " prev_char = -1\n", 43 | " while True:\n", 44 | " ret, frame = cap.read()\n", 45 | " frame = cv2.resize(frame, None, fx=0.5, fy=0.5,interpolation=cv2.INTER_AREA)\n", 46 | " c = cv2.waitKey(1)\n", 47 | " if c == 27:\n", 48 | " break\n", 49 | " if c > -1 and c != prev_char:\n", 50 | " cur_char = c\n", 51 | " prev_char = c\n", 52 | " if cur_char == ord('s'):\n", 53 | " cv2.imshow('sketch mode', cartoonize_image(frame, sketch_mode=True))\n", 54 | " elif cur_char == ord('c'):\n", 55 | " cv2.imshow('Cartoon mode', cartoonize_image(frame, sketch_mode=False))\n", 56 | " else:\n", 57 | " cv2.imshow('normal mode', frame)\n", 58 | " cap.release()\n", 59 | " cv2.destroyAllWindows()\n", 60 | " " 61 | ] 62 | }, 63 | { 64 | "cell_type": "code", 65 | "execution_count": null, 66 | "metadata": {}, 67 | "outputs": [], 68 | "source": [] 69 | } 70 | ], 71 | "metadata": { 72 | "kernelspec": { 73 | "display_name": "Python 3", 74 | "language": "python", 75 | "name": "python3" 76 | }, 77 | "language_info": { 78 | "codemirror_mode": { 79 | "name": "ipython", 80 | "version": 3 81 | }, 82 | "file_extension": ".py", 83 | "mimetype": "text/x-python", 84 | "name": "python", 85 | "nbconvert_exporter": "python", 86 | "pygments_lexer": "ipython3", 87 | "version": "3.7.4" 88 | } 89 | }, 90 | "nbformat": 4, 91 | "nbformat_minor": 2 92 | } 93 | -------------------------------------------------------------------------------- /cartoonizing an image using opencv.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "#cartoonizing an image using OpenCV\n", 11 | "import cv2\n", 12 | "img_rgb = cv2.imread(\"E://OpenCV//bmw.png\") \n", 13 | "numBilateralFilters = 30 \n", 14 | "\n", 15 | "for _ in range(numBilateralFilters): \n", 16 | " img_rgb = cv2.bilateralFilter(img_rgb, 9, 9, 7) \n", 17 | "\n", 18 | "img_gray = cv2.cvtColor(img_rgb, cv2.COLOR_RGB2GRAY)\n", 19 | " \n", 20 | "img_blur = cv2.medianBlur(img_gray, 3) \n", 21 | " \n", 22 | "img_edge = cv2.adaptiveThreshold(img_blur, 255, \n", 23 | " cv2.ADAPTIVE_THRESH_MEAN_C, \n", 24 | " cv2.THRESH_BINARY, 9, 2) \n", 25 | "\n", 26 | "img_edge = cv2.cvtColor(img_edge, cv2.COLOR_GRAY2RGB) \n", 27 | "cv2.imshow(\"img_rgb\", img_rgb) \n", 28 | "cv2.imshow(\"img_edge\", img_edge) \n", 29 | "\n", 30 | "res=cv2.bitwise_and(img_rgb, img_edge) \n", 31 | " \n", 32 | "cv2.imshow(\"Cartoon version\", res) \n", 33 | "cv2.waitKey(0) \n", 34 | "cv2.destroyAllWindows() \n" 35 | ] 36 | } 37 | ], 38 | "metadata": { 39 | "kernelspec": { 40 | "display_name": "Python 3", 41 | "language": "python", 42 | "name": "python3" 43 | }, 44 | "language_info": { 45 | "codemirror_mode": { 46 | "name": "ipython", 47 | "version": 3 48 | }, 49 | "file_extension": ".py", 50 | "mimetype": "text/x-python", 51 | "name": "python", 52 | "nbconvert_exporter": "python", 53 | "pygments_lexer": "ipython3", 54 | "version": "3.7.4" 55 | } 56 | }, 57 | "nbformat": 4, 58 | "nbformat_minor": 2 59 | } 60 | -------------------------------------------------------------------------------- /color detection/color detection.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# color detection using OpenCV" 8 | ] 9 | }, 10 | { 11 | "cell_type": "code", 12 | "execution_count": 11, 13 | "metadata": {}, 14 | "outputs": [], 15 | "source": [ 16 | "#programming_fever\n", 17 | "import cv2\n", 18 | "import numpy as np\n", 19 | "import pandas as pd\n", 20 | "\n", 21 | "img_path = \"D://OpenCV//shape-detection//New folder//palette.jpg\"\n", 22 | "img = cv2.imread(img_path)\n", 23 | "img=cv2.resize(img,(700,500))\n", 24 | "\n", 25 | "clicked = False\n", 26 | "r = g = b = xpos = ypos = 0\n", 27 | "\n", 28 | "#Reading csv file with pandas and giving names to each column\n", 29 | "index=[\"color\",\"color_name\",\"hex\",\"R\",\"G\",\"B\"]\n", 30 | "csv = pd.read_csv('colors.csv', names=index, header=None)\n", 31 | "\n", 32 | "#function to calculate minimum distance from all colors and get the most matching color\n", 33 | "def getColorName(R,G,B):\n", 34 | " minimum = 10000\n", 35 | " for i in range(len(csv)):\n", 36 | " d = abs(R- int(csv.loc[i,\"R\"])) + abs(G- int(csv.loc[i,\"G\"]))+ abs(B- int(csv.loc[i,\"B\"]))\n", 37 | " if(d<=minimum):\n", 38 | " minimum = d\n", 39 | " cname = csv.loc[i,\"color_name\"]\n", 40 | " return cname\n", 41 | "\n", 42 | "#function to get x,y coordinates of mouse double click\n", 43 | "def draw_function(event, x,y,flags,param):\n", 44 | " if event == cv2.EVENT_LBUTTONDBLCLK:\n", 45 | " global b,g,r,xpos,ypos, clicked\n", 46 | " clicked = True\n", 47 | " xpos = x\n", 48 | " ypos = y\n", 49 | " b,g,r = img[y,x]\n", 50 | " b = int(b)\n", 51 | " g = int(g)\n", 52 | " r = int(r)\n", 53 | "cv2.namedWindow('color detection by programming_fever')\n", 54 | "cv2.setMouseCallback('color detection by programming_fever',draw_function)\n", 55 | "\n", 56 | "while(1):\n", 57 | "\n", 58 | " cv2.imshow(\"color detection by programming_fever\",img)\n", 59 | " if (clicked):\n", 60 | " \n", 61 | " #cv2.rectangle(image, startpoint, endpoint, color, thickness)-1 fills entire rectangle \n", 62 | " cv2.rectangle(img,(20,20), (750,60), (b,g,r), -1)\n", 63 | "\n", 64 | " #Creating text string to display( Color name and RGB values )\n", 65 | " text = getColorName(r,g,b) + ' R='+ str(r) + ' G='+ str(g) + ' B='+ str(b)\n", 66 | " \n", 67 | " #cv2.putText(img,text,start,font(0-7),fontScale,color,thickness,lineType )\n", 68 | " cv2.putText(img, text,(50,50),2,0.8,(255,255,255),2,cv2.LINE_AA)\n", 69 | "\n", 70 | " #For very light colours we will display text in black colour\n", 71 | " if(r+g+b>=600):\n", 72 | " cv2.putText(img, text,(50,50),2,0.8,(0,0,0),2,cv2.LINE_AA)\n", 73 | " \n", 74 | " clicked=False\n", 75 | "\n", 76 | " if cv2.waitKey(20) & 0xFF ==27:\n", 77 | " break\n", 78 | " \n", 79 | "cv2.destroyAllWindows()" 80 | ] 81 | }, 82 | { 83 | "cell_type": "code", 84 | "execution_count": null, 85 | "metadata": {}, 86 | "outputs": [], 87 | "source": [] 88 | }, 89 | { 90 | "cell_type": "code", 91 | "execution_count": null, 92 | "metadata": {}, 93 | "outputs": [], 94 | "source": [] 95 | } 96 | ], 97 | "metadata": { 98 | "kernelspec": { 99 | "display_name": "Python 3", 100 | "language": "python", 101 | "name": "python3" 102 | }, 103 | "language_info": { 104 | "codemirror_mode": { 105 | "name": "ipython", 106 | "version": 3 107 | }, 108 | "file_extension": ".py", 109 | "mimetype": "text/x-python", 110 | "name": "python", 111 | "nbconvert_exporter": "python", 112 | "pygments_lexer": "ipython3", 113 | "version": "3.7.6" 114 | } 115 | }, 116 | "nbformat": 4, 117 | "nbformat_minor": 4 118 | } 119 | -------------------------------------------------------------------------------- /color detection/color palette.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GeekyPRAVEE/OpenCV-Projects/505fbbd86fc1281a870b3427555aff148aa44a08/color detection/color palette.jpg -------------------------------------------------------------------------------- /color detection/colors.csv: -------------------------------------------------------------------------------- 1 | air_force_blue_raf,"Air Force Blue (Raf)",#5d8aa8,93,138,168 2 | air_force_blue_usaf,"Air Force Blue (Usaf)",#00308f,0,48,143 3 | air_superiority_blue,"Air Superiority Blue",#72a0c1,114,160,193 4 | alabama_crimson,"Alabama Crimson",#a32638,163,38,56 5 | alice_blue,"Alice Blue",#f0f8ff,240,248,255 6 | alizarin_crimson,"Alizarin Crimson",#e32636,227,38,54 7 | alloy_orange,"Alloy Orange",#c46210,196,98,16 8 | almond,"Almond",#efdecd,239,222,205 9 | amaranth,"Amaranth",#e52b50,229,43,80 10 | amber,"Amber",#ffbf00,255,191,0 11 | amber_sae_ece,"Amber (Sae/Ece)",#ff7e00,255,126,0 12 | american_rose,"American Rose",#ff033e,255,3,62 13 | amethyst,"Amethyst",#96c,153,102,204 14 | android_green,"Android Green",#a4c639,164,198,57 15 | anti_flash_white,"Anti-Flash White",#f2f3f4,242,243,244 16 | antique_brass,"Antique Brass",#cd9575,205,149,117 17 | antique_fuchsia,"Antique Fuchsia",#915c83,145,92,131 18 | antique_ruby,"Antique Ruby",#841b2d,132,27,45 19 | antique_white,"Antique White",#faebd7,250,235,215 20 | ao_english,"Ao (English)",#008000,0,128,0 21 | apple_green,"Apple Green",#8db600,141,182,0 22 | apricot,"Apricot",#fbceb1,251,206,177 23 | aqua,"Aqua",#0ff,0,255,255 24 | aquamarine,"Aquamarine",#7fffd4,127,255,212 25 | army_green,"Army Green",#4b5320,75,83,32 26 | arsenic,"Arsenic",#3b444b,59,68,75 27 | arylide_yellow,"Arylide Yellow",#e9d66b,233,214,107 28 | ash_grey,"Ash Grey",#b2beb5,178,190,181 29 | asparagus,"Asparagus",#87a96b,135,169,107 30 | atomic_tangerine,"Atomic Tangerine",#f96,255,153,102 31 | auburn,"Auburn",#a52a2a,165,42,42 32 | aureolin,"Aureolin",#fdee00,253,238,0 33 | aurometalsaurus,"Aurometalsaurus",#6e7f80,110,127,128 34 | avocado,"Avocado",#568203,86,130,3 35 | azure,"Azure",#007fff,0,127,255 36 | azure_mist_web,"Azure Mist/Web",#f0ffff,240,255,255 37 | baby_blue,"Baby Blue",#89cff0,137,207,240 38 | baby_blue_eyes,"Baby Blue Eyes",#a1caf1,161,202,241 39 | baby_pink,"Baby Pink",#f4c2c2,244,194,194 40 | ball_blue,"Ball Blue",#21abcd,33,171,205 41 | banana_mania,"Banana Mania",#fae7b5,250,231,181 42 | banana_yellow,"Banana Yellow",#ffe135,255,225,53 43 | barn_red,"Barn Red",#7c0a02,124,10,2 44 | battleship_grey,"Battleship Grey",#848482,132,132,130 45 | bazaar,"Bazaar",#98777b,152,119,123 46 | beau_blue,"Beau Blue",#bcd4e6,188,212,230 47 | beaver,"Beaver",#9f8170,159,129,112 48 | beige,"Beige",#f5f5dc,245,245,220 49 | big_dip_o_ruby,"Big Dip O’Ruby",#9c2542,156,37,66 50 | bisque,"Bisque",#ffe4c4,255,228,196 51 | bistre,"Bistre",#3d2b1f,61,43,31 52 | bittersweet,"Bittersweet",#fe6f5e,254,111,94 53 | bittersweet_shimmer,"Bittersweet Shimmer",#bf4f51,191,79,81 54 | black,"Black",#000,0,0,0 55 | black_bean,"Black Bean",#3d0c02,61,12,2 56 | black_leather_jacket,"Black Leather Jacket",#253529,37,53,41 57 | black_olive,"Black Olive",#3b3c36,59,60,54 58 | blanched_almond,"Blanched Almond",#ffebcd,255,235,205 59 | blast_off_bronze,"Blast-Off Bronze",#a57164,165,113,100 60 | bleu_de_france,"Bleu De France",#318ce7,49,140,231 61 | blizzard_blue,"Blizzard Blue",#ace5ee,172,229,238 62 | blond,"Blond",#faf0be,250,240,190 63 | blue,"Blue",#00f,0,0,255 64 | blue_bell,"Blue Bell",#a2a2d0,162,162,208 65 | blue_crayola,"Blue (Crayola)",#1f75fe,31,117,254 66 | blue_gray,"Blue Gray",#69c,102,153,204 67 | blue_green,"Blue-Green",#0d98ba,13,152,186 68 | blue_munsell,"Blue (Munsell)",#0093af,0,147,175 69 | blue_ncs,"Blue (Ncs)",#0087bd,0,135,189 70 | blue_pigment,"Blue (Pigment)",#339,51,51,153 71 | blue_ryb,"Blue (Ryb)",#0247fe,2,71,254 72 | blue_sapphire,"Blue Sapphire",#126180,18,97,128 73 | blue_violet,"Blue-Violet",#8a2be2,138,43,226 74 | blush,"Blush",#de5d83,222,93,131 75 | bole,"Bole",#79443b,121,68,59 76 | bondi_blue,"Bondi Blue",#0095b6,0,149,182 77 | bone,"Bone",#e3dac9,227,218,201 78 | boston_university_red,"Boston University Red",#c00,204,0,0 79 | bottle_green,"Bottle Green",#006a4e,0,106,78 80 | boysenberry,"Boysenberry",#873260,135,50,96 81 | brandeis_blue,"Brandeis Blue",#0070ff,0,112,255 82 | brass,"Brass",#b5a642,181,166,66 83 | brick_red,"Brick Red",#cb4154,203,65,84 84 | bright_cerulean,"Bright Cerulean",#1dacd6,29,172,214 85 | bright_green,"Bright Green",#6f0,102,255,0 86 | bright_lavender,"Bright Lavender",#bf94e4,191,148,228 87 | bright_maroon,"Bright Maroon",#c32148,195,33,72 88 | bright_pink,"Bright Pink",#ff007f,255,0,127 89 | bright_turquoise,"Bright Turquoise",#08e8de,8,232,222 90 | bright_ube,"Bright Ube",#d19fe8,209,159,232 91 | brilliant_lavender,"Brilliant Lavender",#f4bbff,244,187,255 92 | brilliant_rose,"Brilliant Rose",#ff55a3,255,85,163 93 | brink_pink,"Brink Pink",#fb607f,251,96,127 94 | british_racing_green,"British Racing Green",#004225,0,66,37 95 | bronze,"Bronze",#cd7f32,205,127,50 96 | brown_traditional,"Brown (Traditional)",#964b00,150,75,0 97 | brown_web,"Brown (Web)",#a52a2a,165,42,42 98 | bubble_gum,"Bubble Gum",#ffc1cc,255,193,204 99 | bubbles,"Bubbles",#e7feff,231,254,255 100 | buff,"Buff",#f0dc82,240,220,130 101 | bulgarian_rose,"Bulgarian Rose",#480607,72,6,7 102 | burgundy,"Burgundy",#800020,128,0,32 103 | burlywood,"Burlywood",#deb887,222,184,135 104 | burnt_orange,"Burnt Orange",#c50,204,85,0 105 | burnt_sienna,"Burnt Sienna",#e97451,233,116,81 106 | burnt_umber,"Burnt Umber",#8a3324,138,51,36 107 | byzantine,"Byzantine",#bd33a4,189,51,164 108 | byzantium,"Byzantium",#702963,112,41,99 109 | cadet,"Cadet",#536872,83,104,114 110 | cadet_blue,"Cadet Blue",#5f9ea0,95,158,160 111 | cadet_grey,"Cadet Grey",#91a3b0,145,163,176 112 | cadmium_green,"Cadmium Green",#006b3c,0,107,60 113 | cadmium_orange,"Cadmium Orange",#ed872d,237,135,45 114 | cadmium_red,"Cadmium Red",#e30022,227,0,34 115 | cadmium_yellow,"Cadmium Yellow",#fff600,255,246,0 116 | caf_au_lait,"Café Au Lait",#a67b5b,166,123,91 117 | caf_noir,"Café Noir",#4b3621,75,54,33 118 | cal_poly_green,"Cal Poly Green",#1e4d2b,30,77,43 119 | cambridge_blue,"Cambridge Blue",#a3c1ad,163,193,173 120 | camel,"Camel",#c19a6b,193,154,107 121 | cameo_pink,"Cameo Pink",#efbbcc,239,187,204 122 | camouflage_green,"Camouflage Green",#78866b,120,134,107 123 | canary_yellow,"Canary Yellow",#ffef00,255,239,0 124 | candy_apple_red,"Candy Apple Red",#ff0800,255,8,0 125 | candy_pink,"Candy Pink",#e4717a,228,113,122 126 | capri,"Capri",#00bfff,0,191,255 127 | caput_mortuum,"Caput Mortuum",#592720,89,39,32 128 | cardinal,"Cardinal",#c41e3a,196,30,58 129 | caribbean_green,"Caribbean Green",#0c9,0,204,153 130 | carmine,"Carmine",#960018,150,0,24 131 | carmine_m_p,"Carmine (M&P)",#d70040,215,0,64 132 | carmine_pink,"Carmine Pink",#eb4c42,235,76,66 133 | carmine_red,"Carmine Red",#ff0038,255,0,56 134 | carnation_pink,"Carnation Pink",#ffa6c9,255,166,201 135 | carnelian,"Carnelian",#b31b1b,179,27,27 136 | carolina_blue,"Carolina Blue",#99badd,153,186,221 137 | carrot_orange,"Carrot Orange",#ed9121,237,145,33 138 | catalina_blue,"Catalina Blue",#062a78,6,42,120 139 | ceil,"Ceil",#92a1cf,146,161,207 140 | celadon,"Celadon",#ace1af,172,225,175 141 | celadon_blue,"Celadon Blue",#007ba7,0,123,167 142 | celadon_green,"Celadon Green",#2f847c,47,132,124 143 | celeste_colour,"Celeste (Colour)",#b2ffff,178,255,255 144 | celestial_blue,"Celestial Blue",#4997d0,73,151,208 145 | cerise,"Cerise",#de3163,222,49,99 146 | cerise_pink,"Cerise Pink",#ec3b83,236,59,131 147 | cerulean,"Cerulean",#007ba7,0,123,167 148 | cerulean_blue,"Cerulean Blue",#2a52be,42,82,190 149 | cerulean_frost,"Cerulean Frost",#6d9bc3,109,155,195 150 | cg_blue,"Cg Blue",#007aa5,0,122,165 151 | cg_red,"Cg Red",#e03c31,224,60,49 152 | chamoisee,"Chamoisee",#a0785a,160,120,90 153 | champagne,"Champagne",#fad6a5,250,214,165 154 | charcoal,"Charcoal",#36454f,54,69,79 155 | charm_pink,"Charm Pink",#e68fac,230,143,172 156 | chartreuse_traditional,"Chartreuse (Traditional)",#dfff00,223,255,0 157 | chartreuse_web,"Chartreuse (Web)",#7fff00,127,255,0 158 | cherry,"Cherry",#de3163,222,49,99 159 | cherry_blossom_pink,"Cherry Blossom Pink",#ffb7c5,255,183,197 160 | chestnut,"Chestnut",#cd5c5c,205,92,92 161 | china_pink,"China Pink",#de6fa1,222,111,161 162 | china_rose,"China Rose",#a8516e,168,81,110 163 | chinese_red,"Chinese Red",#aa381e,170,56,30 164 | chocolate_traditional,"Chocolate (Traditional)",#7b3f00,123,63,0 165 | chocolate_web,"Chocolate (Web)",#d2691e,210,105,30 166 | chrome_yellow,"Chrome Yellow",#ffa700,255,167,0 167 | cinereous,"Cinereous",#98817b,152,129,123 168 | cinnabar,"Cinnabar",#e34234,227,66,52 169 | cinnamon,"Cinnamon",#d2691e,210,105,30 170 | citrine,"Citrine",#e4d00a,228,208,10 171 | classic_rose,"Classic Rose",#fbcce7,251,204,231 172 | cobalt,"Cobalt",#0047ab,0,71,171 173 | cocoa_brown,"Cocoa Brown",#d2691e,210,105,30 174 | coffee,"Coffee",#6f4e37,111,78,55 175 | columbia_blue,"Columbia Blue",#9bddff,155,221,255 176 | congo_pink,"Congo Pink",#f88379,248,131,121 177 | cool_black,"Cool Black",#002e63,0,46,99 178 | cool_grey,"Cool Grey",#8c92ac,140,146,172 179 | copper,"Copper",#b87333,184,115,51 180 | copper_crayola,"Copper (Crayola)",#da8a67,218,138,103 181 | copper_penny,"Copper Penny",#ad6f69,173,111,105 182 | copper_red,"Copper Red",#cb6d51,203,109,81 183 | copper_rose,"Copper Rose",#966,153,102,102 184 | coquelicot,"Coquelicot",#ff3800,255,56,0 185 | coral,"Coral",#ff7f50,255,127,80 186 | coral_pink,"Coral Pink",#f88379,248,131,121 187 | coral_red,"Coral Red",#ff4040,255,64,64 188 | cordovan,"Cordovan",#893f45,137,63,69 189 | corn,"Corn",#fbec5d,251,236,93 190 | cornell_red,"Cornell Red",#b31b1b,179,27,27 191 | cornflower_blue,"Cornflower Blue",#6495ed,100,149,237 192 | cornsilk,"Cornsilk",#fff8dc,255,248,220 193 | cosmic_latte,"Cosmic Latte",#fff8e7,255,248,231 194 | cotton_candy,"Cotton Candy",#ffbcd9,255,188,217 195 | cream,"Cream",#fffdd0,255,253,208 196 | crimson,"Crimson",#dc143c,220,20,60 197 | crimson_glory,"Crimson Glory",#be0032,190,0,50 198 | cyan,"Cyan",#0ff,0,255,255 199 | cyan_process,"Cyan (Process)",#00b7eb,0,183,235 200 | daffodil,"Daffodil",#ffff31,255,255,49 201 | dandelion,"Dandelion",#f0e130,240,225,48 202 | dark_blue,"Dark Blue",#00008b,0,0,139 203 | dark_brown,"Dark Brown",#654321,101,67,33 204 | dark_byzantium,"Dark Byzantium",#5d3954,93,57,84 205 | dark_candy_apple_red,"Dark Candy Apple Red",#a40000,164,0,0 206 | dark_cerulean,"Dark Cerulean",#08457e,8,69,126 207 | dark_chestnut,"Dark Chestnut",#986960,152,105,96 208 | dark_coral,"Dark Coral",#cd5b45,205,91,69 209 | dark_cyan,"Dark Cyan",#008b8b,0,139,139 210 | dark_electric_blue,"Dark Electric Blue",#536878,83,104,120 211 | dark_goldenrod,"Dark Goldenrod",#b8860b,184,134,11 212 | dark_gray,"Dark Gray",#a9a9a9,169,169,169 213 | dark_green,"Dark Green",#013220,1,50,32 214 | dark_imperial_blue,"Dark Imperial Blue",#00416a,0,65,106 215 | dark_jungle_green,"Dark Jungle Green",#1a2421,26,36,33 216 | dark_khaki,"Dark Khaki",#bdb76b,189,183,107 217 | dark_lava,"Dark Lava",#483c32,72,60,50 218 | dark_lavender,"Dark Lavender",#734f96,115,79,150 219 | dark_magenta,"Dark Magenta",#8b008b,139,0,139 220 | dark_midnight_blue,"Dark Midnight Blue",#036,0,51,102 221 | dark_olive_green,"Dark Olive Green",#556b2f,85,107,47 222 | dark_orange,"Dark Orange",#ff8c00,255,140,0 223 | dark_orchid,"Dark Orchid",#9932cc,153,50,204 224 | dark_pastel_blue,"Dark Pastel Blue",#779ecb,119,158,203 225 | dark_pastel_green,"Dark Pastel Green",#03c03c,3,192,60 226 | dark_pastel_purple,"Dark Pastel Purple",#966fd6,150,111,214 227 | dark_pastel_red,"Dark Pastel Red",#c23b22,194,59,34 228 | dark_pink,"Dark Pink",#e75480,231,84,128 229 | dark_powder_blue,"Dark Powder Blue",#039,0,51,153 230 | dark_raspberry,"Dark Raspberry",#872657,135,38,87 231 | dark_red,"Dark Red",#8b0000,139,0,0 232 | dark_salmon,"Dark Salmon",#e9967a,233,150,122 233 | dark_scarlet,"Dark Scarlet",#560319,86,3,25 234 | dark_sea_green,"Dark Sea Green",#8fbc8f,143,188,143 235 | dark_sienna,"Dark Sienna",#3c1414,60,20,20 236 | dark_slate_blue,"Dark Slate Blue",#483d8b,72,61,139 237 | dark_slate_gray,"Dark Slate Gray",#2f4f4f,47,79,79 238 | dark_spring_green,"Dark Spring Green",#177245,23,114,69 239 | dark_tan,"Dark Tan",#918151,145,129,81 240 | dark_tangerine,"Dark Tangerine",#ffa812,255,168,18 241 | dark_taupe,"Dark Taupe",#483c32,72,60,50 242 | dark_terra_cotta,"Dark Terra Cotta",#cc4e5c,204,78,92 243 | dark_turquoise,"Dark Turquoise",#00ced1,0,206,209 244 | dark_violet,"Dark Violet",#9400d3,148,0,211 245 | dark_yellow,"Dark Yellow",#9b870c,155,135,12 246 | dartmouth_green,"Dartmouth Green",#00703c,0,112,60 247 | davy_s_grey,"Davy'S Grey",#555,85,85,85 248 | debian_red,"Debian Red",#d70a53,215,10,83 249 | deep_carmine,"Deep Carmine",#a9203e,169,32,62 250 | deep_carmine_pink,"Deep Carmine Pink",#ef3038,239,48,56 251 | deep_carrot_orange,"Deep Carrot Orange",#e9692c,233,105,44 252 | deep_cerise,"Deep Cerise",#da3287,218,50,135 253 | deep_champagne,"Deep Champagne",#fad6a5,250,214,165 254 | deep_chestnut,"Deep Chestnut",#b94e48,185,78,72 255 | deep_coffee,"Deep Coffee",#704241,112,66,65 256 | deep_fuchsia,"Deep Fuchsia",#c154c1,193,84,193 257 | deep_jungle_green,"Deep Jungle Green",#004b49,0,75,73 258 | deep_lilac,"Deep Lilac",#95b,153,85,187 259 | deep_magenta,"Deep Magenta",#c0c,204,0,204 260 | deep_peach,"Deep Peach",#ffcba4,255,203,164 261 | deep_pink,"Deep Pink",#ff1493,255,20,147 262 | deep_ruby,"Deep Ruby",#843f5b,132,63,91 263 | deep_saffron,"Deep Saffron",#f93,255,153,51 264 | deep_sky_blue,"Deep Sky Blue",#00bfff,0,191,255 265 | deep_tuscan_red,"Deep Tuscan Red",#66424d,102,66,77 266 | denim,"Denim",#1560bd,21,96,189 267 | desert,"Desert",#c19a6b,193,154,107 268 | desert_sand,"Desert Sand",#edc9af,237,201,175 269 | dim_gray,"Dim Gray",#696969,105,105,105 270 | dodger_blue,"Dodger Blue",#1e90ff,30,144,255 271 | dogwood_rose,"Dogwood Rose",#d71868,215,24,104 272 | dollar_bill,"Dollar Bill",#85bb65,133,187,101 273 | drab,"Drab",#967117,150,113,23 274 | duke_blue,"Duke Blue",#00009c,0,0,156 275 | earth_yellow,"Earth Yellow",#e1a95f,225,169,95 276 | ebony,"Ebony",#555d50,85,93,80 277 | ecru,"Ecru",#c2b280,194,178,128 278 | eggplant,"Eggplant",#614051,97,64,81 279 | eggshell,"Eggshell",#f0ead6,240,234,214 280 | egyptian_blue,"Egyptian Blue",#1034a6,16,52,166 281 | electric_blue,"Electric Blue",#7df9ff,125,249,255 282 | electric_crimson,"Electric Crimson",#ff003f,255,0,63 283 | electric_cyan,"Electric Cyan",#0ff,0,255,255 284 | electric_green,"Electric Green",#0f0,0,255,0 285 | electric_indigo,"Electric Indigo",#6f00ff,111,0,255 286 | electric_lavender,"Electric Lavender",#f4bbff,244,187,255 287 | electric_lime,"Electric Lime",#cf0,204,255,0 288 | electric_purple,"Electric Purple",#bf00ff,191,0,255 289 | electric_ultramarine,"Electric Ultramarine",#3f00ff,63,0,255 290 | electric_violet,"Electric Violet",#8f00ff,143,0,255 291 | electric_yellow,"Electric Yellow",#ff0,255,255,0 292 | emerald,"Emerald",#50c878,80,200,120 293 | english_lavender,"English Lavender",#b48395,180,131,149 294 | eton_blue,"Eton Blue",#96c8a2,150,200,162 295 | fallow,"Fallow",#c19a6b,193,154,107 296 | falu_red,"Falu Red",#801818,128,24,24 297 | fandango,"Fandango",#b53389,181,51,137 298 | fashion_fuchsia,"Fashion Fuchsia",#f400a1,244,0,161 299 | fawn,"Fawn",#e5aa70,229,170,112 300 | feldgrau,"Feldgrau",#4d5d53,77,93,83 301 | fern_green,"Fern Green",#4f7942,79,121,66 302 | ferrari_red,"Ferrari Red",#ff2800,255,40,0 303 | field_drab,"Field Drab",#6c541e,108,84,30 304 | fire_engine_red,"Fire Engine Red",#ce2029,206,32,41 305 | firebrick,"Firebrick",#b22222,178,34,34 306 | flame,"Flame",#e25822,226,88,34 307 | flamingo_pink,"Flamingo Pink",#fc8eac,252,142,172 308 | flavescent,"Flavescent",#f7e98e,247,233,142 309 | flax,"Flax",#eedc82,238,220,130 310 | floral_white,"Floral White",#fffaf0,255,250,240 311 | fluorescent_orange,"Fluorescent Orange",#ffbf00,255,191,0 312 | fluorescent_pink,"Fluorescent Pink",#ff1493,255,20,147 313 | fluorescent_yellow,"Fluorescent Yellow",#cf0,204,255,0 314 | folly,"Folly",#ff004f,255,0,79 315 | forest_green_traditional,"Forest Green (Traditional)",#014421,1,68,33 316 | forest_green_web,"Forest Green (Web)",#228b22,34,139,34 317 | french_beige,"French Beige",#a67b5b,166,123,91 318 | french_blue,"French Blue",#0072bb,0,114,187 319 | french_lilac,"French Lilac",#86608e,134,96,142 320 | french_lime,"French Lime",#cf0,204,255,0 321 | french_raspberry,"French Raspberry",#c72c48,199,44,72 322 | french_rose,"French Rose",#f64a8a,246,74,138 323 | fuchsia,"Fuchsia",#f0f,255,0,255 324 | fuchsia_crayola,"Fuchsia (Crayola)",#c154c1,193,84,193 325 | fuchsia_pink,"Fuchsia Pink",#f7f,255,119,255 326 | fuchsia_rose,"Fuchsia Rose",#c74375,199,67,117 327 | fulvous,"Fulvous",#e48400,228,132,0 328 | fuzzy_wuzzy,"Fuzzy Wuzzy",#c66,204,102,102 329 | gainsboro,"Gainsboro",#dcdcdc,220,220,220 330 | gamboge,"Gamboge",#e49b0f,228,155,15 331 | ghost_white,"Ghost White",#f8f8ff,248,248,255 332 | ginger,"Ginger",#b06500,176,101,0 333 | glaucous,"Glaucous",#6082b6,96,130,182 334 | glitter,"Glitter",#e6e8fa,230,232,250 335 | gold_metallic,"Gold (Metallic)",#d4af37,212,175,55 336 | gold_web_golden,"Gold (Web) (Golden)",#ffd700,255,215,0 337 | golden_brown,"Golden Brown",#996515,153,101,21 338 | golden_poppy,"Golden Poppy",#fcc200,252,194,0 339 | golden_yellow,"Golden Yellow",#ffdf00,255,223,0 340 | goldenrod,"Goldenrod",#daa520,218,165,32 341 | granny_smith_apple,"Granny Smith Apple",#a8e4a0,168,228,160 342 | gray,"Gray",#808080,128,128,128 343 | gray_asparagus,"Gray-Asparagus",#465945,70,89,69 344 | gray_html_css_gray,"Gray (Html/Css Gray)",#808080,128,128,128 345 | gray_x11_gray,"Gray (X11 Gray)",#bebebe,190,190,190 346 | green_color_wheel_x11_green,"Green (Color Wheel) (X11 Green)",#0f0,0,255,0 347 | green_crayola,"Green (Crayola)",#1cac78,28,172,120 348 | green_html_css_green,"Green (Html/Css Green)",#008000,0,128,0 349 | green_munsell,"Green (Munsell)",#00a877,0,168,119 350 | green_ncs,"Green (Ncs)",#009f6b,0,159,107 351 | green_pigment,"Green (Pigment)",#00a550,0,165,80 352 | green_ryb,"Green (Ryb)",#66b032,102,176,50 353 | green_yellow,"Green-Yellow",#adff2f,173,255,47 354 | grullo,"Grullo",#a99a86,169,154,134 355 | guppie_green,"Guppie Green",#00ff7f,0,255,127 356 | halay_be,"Halayà úBe",#663854,102,56,84 357 | han_blue,"Han Blue",#446ccf,68,108,207 358 | han_purple,"Han Purple",#5218fa,82,24,250 359 | hansa_yellow,"Hansa Yellow",#e9d66b,233,214,107 360 | harlequin,"Harlequin",#3fff00,63,255,0 361 | harvard_crimson,"Harvard Crimson",#c90016,201,0,22 362 | harvest_gold,"Harvest Gold",#da9100,218,145,0 363 | heart_gold,"Heart Gold",#808000,128,128,0 364 | heliotrope,"Heliotrope",#df73ff,223,115,255 365 | hollywood_cerise,"Hollywood Cerise",#f400a1,244,0,161 366 | honeydew,"Honeydew",#f0fff0,240,255,240 367 | honolulu_blue,"Honolulu Blue",#007fbf,0,127,191 368 | hooker_s_green,"Hooker'S Green",#49796b,73,121,107 369 | hot_magenta,"Hot Magenta",#ff1dce,255,29,206 370 | hot_pink,"Hot Pink",#ff69b4,255,105,180 371 | hunter_green,"Hunter Green",#355e3b,53,94,59 372 | iceberg,"Iceberg",#71a6d2,113,166,210 373 | icterine,"Icterine",#fcf75e,252,247,94 374 | imperial_blue,"Imperial Blue",#002395,0,35,149 375 | inchworm,"Inchworm",#b2ec5d,178,236,93 376 | india_green,"India Green",#138808,19,136,8 377 | indian_red,"Indian Red",#cd5c5c,205,92,92 378 | indian_yellow,"Indian Yellow",#e3a857,227,168,87 379 | indigo,"Indigo",#6f00ff,111,0,255 380 | indigo_dye,"Indigo (Dye)",#00416a,0,65,106 381 | indigo_web,"Indigo (Web)",#4b0082,75,0,130 382 | international_klein_blue,"International Klein Blue",#002fa7,0,47,167 383 | international_orange_aerospace,"International Orange (Aerospace)",#ff4f00,255,79,0 384 | international_orange_engineering,"International Orange (Engineering)",#ba160c,186,22,12 385 | international_orange_golden_gate_bridge,"International Orange (Golden Gate Bridge)",#c0362c,192,54,44 386 | iris,"Iris",#5a4fcf,90,79,207 387 | isabelline,"Isabelline",#f4f0ec,244,240,236 388 | islamic_green,"Islamic Green",#009000,0,144,0 389 | ivory,"Ivory",#fffff0,255,255,240 390 | jade,"Jade",#00a86b,0,168,107 391 | jasmine,"Jasmine",#f8de7e,248,222,126 392 | jasper,"Jasper",#d73b3e,215,59,62 393 | jazzberry_jam,"Jazzberry Jam",#a50b5e,165,11,94 394 | jet,"Jet",#343434,52,52,52 395 | jonquil,"Jonquil",#fada5e,250,218,94 396 | june_bud,"June Bud",#bdda57,189,218,87 397 | jungle_green,"Jungle Green",#29ab87,41,171,135 398 | kelly_green,"Kelly Green",#4cbb17,76,187,23 399 | kenyan_copper,"Kenyan Copper",#7c1c05,124,28,5 400 | khaki_html_css_khaki,"Khaki (Html/Css) (Khaki)",#c3b091,195,176,145 401 | khaki_x11_light_khaki,"Khaki (X11) (Light Khaki)",#f0e68c,240,230,140 402 | ku_crimson,"Ku Crimson",#e8000d,232,0,13 403 | la_salle_green,"La Salle Green",#087830,8,120,48 404 | languid_lavender,"Languid Lavender",#d6cadd,214,202,221 405 | lapis_lazuli,"Lapis Lazuli",#26619c,38,97,156 406 | laser_lemon,"Laser Lemon",#fefe22,254,254,34 407 | laurel_green,"Laurel Green",#a9ba9d,169,186,157 408 | lava,"Lava",#cf1020,207,16,32 409 | lavender_blue,"Lavender Blue",#ccf,204,204,255 410 | lavender_blush,"Lavender Blush",#fff0f5,255,240,245 411 | lavender_floral,"Lavender (Floral)",#b57edc,181,126,220 412 | lavender_gray,"Lavender Gray",#c4c3d0,196,195,208 413 | lavender_indigo,"Lavender Indigo",#9457eb,148,87,235 414 | lavender_magenta,"Lavender Magenta",#ee82ee,238,130,238 415 | lavender_mist,"Lavender Mist",#e6e6fa,230,230,250 416 | lavender_pink,"Lavender Pink",#fbaed2,251,174,210 417 | lavender_purple,"Lavender Purple",#967bb6,150,123,182 418 | lavender_rose,"Lavender Rose",#fba0e3,251,160,227 419 | lavender_web,"Lavender (Web)",#e6e6fa,230,230,250 420 | lawn_green,"Lawn Green",#7cfc00,124,252,0 421 | lemon,"Lemon",#fff700,255,247,0 422 | lemon_chiffon,"Lemon Chiffon",#fffacd,255,250,205 423 | lemon_lime,"Lemon Lime",#e3ff00,227,255,0 424 | licorice,"Licorice",#1a1110,26,17,16 425 | light_apricot,"Light Apricot",#fdd5b1,253,213,177 426 | light_blue,"Light Blue",#add8e6,173,216,230 427 | light_brown,"Light Brown",#b5651d,181,101,29 428 | light_carmine_pink,"Light Carmine Pink",#e66771,230,103,113 429 | light_coral,"Light Coral",#f08080,240,128,128 430 | light_cornflower_blue,"Light Cornflower Blue",#93ccea,147,204,234 431 | light_crimson,"Light Crimson",#f56991,245,105,145 432 | light_cyan,"Light Cyan",#e0ffff,224,255,255 433 | light_fuchsia_pink,"Light Fuchsia Pink",#f984ef,249,132,239 434 | light_goldenrod_yellow,"Light Goldenrod Yellow",#fafad2,250,250,210 435 | light_gray,"Light Gray",#d3d3d3,211,211,211 436 | light_green,"Light Green",#90ee90,144,238,144 437 | light_khaki,"Light Khaki",#f0e68c,240,230,140 438 | light_pastel_purple,"Light Pastel Purple",#b19cd9,177,156,217 439 | light_pink,"Light Pink",#ffb6c1,255,182,193 440 | light_red_ochre,"Light Red Ochre",#e97451,233,116,81 441 | light_salmon,"Light Salmon",#ffa07a,255,160,122 442 | light_salmon_pink,"Light Salmon Pink",#f99,255,153,153 443 | light_sea_green,"Light Sea Green",#20b2aa,32,178,170 444 | light_sky_blue,"Light Sky Blue",#87cefa,135,206,250 445 | light_slate_gray,"Light Slate Gray",#789,119,136,153 446 | light_taupe,"Light Taupe",#b38b6d,179,139,109 447 | light_thulian_pink,"Light Thulian Pink",#e68fac,230,143,172 448 | light_yellow,"Light Yellow",#ffffe0,255,255,224 449 | lilac,"Lilac",#c8a2c8,200,162,200 450 | lime_color_wheel,"Lime (Color Wheel)",#bfff00,191,255,0 451 | lime_green,"Lime Green",#32cd32,50,205,50 452 | lime_web_x11_green,"Lime (Web) (X11 Green)",#0f0,0,255,0 453 | limerick,"Limerick",#9dc209,157,194,9 454 | lincoln_green,"Lincoln Green",#195905,25,89,5 455 | linen,"Linen",#faf0e6,250,240,230 456 | lion,"Lion",#c19a6b,193,154,107 457 | little_boy_blue,"Little Boy Blue",#6ca0dc,108,160,220 458 | liver,"Liver",#534b4f,83,75,79 459 | lust,"Lust",#e62020,230,32,32 460 | magenta,"Magenta",#f0f,255,0,255 461 | magenta_dye,"Magenta (Dye)",#ca1f7b,202,31,123 462 | magenta_process,"Magenta (Process)",#ff0090,255,0,144 463 | magic_mint,"Magic Mint",#aaf0d1,170,240,209 464 | magnolia,"Magnolia",#f8f4ff,248,244,255 465 | mahogany,"Mahogany",#c04000,192,64,0 466 | maize,"Maize",#fbec5d,251,236,93 467 | majorelle_blue,"Majorelle Blue",#6050dc,96,80,220 468 | malachite,"Malachite",#0bda51,11,218,81 469 | manatee,"Manatee",#979aaa,151,154,170 470 | mango_tango,"Mango Tango",#ff8243,255,130,67 471 | mantis,"Mantis",#74c365,116,195,101 472 | mardi_gras,"Mardi Gras",#880085,136,0,133 473 | maroon_crayola,"Maroon (Crayola)",#c32148,195,33,72 474 | maroon_html_css,"Maroon (Html/Css)",#800000,128,0,0 475 | maroon_x11,"Maroon (X11)",#b03060,176,48,96 476 | mauve,"Mauve",#e0b0ff,224,176,255 477 | mauve_taupe,"Mauve Taupe",#915f6d,145,95,109 478 | mauvelous,"Mauvelous",#ef98aa,239,152,170 479 | maya_blue,"Maya Blue",#73c2fb,115,194,251 480 | meat_brown,"Meat Brown",#e5b73b,229,183,59 481 | medium_aquamarine,"Medium Aquamarine",#6da,102,221,170 482 | medium_blue,"Medium Blue",#0000cd,0,0,205 483 | medium_candy_apple_red,"Medium Candy Apple Red",#e2062c,226,6,44 484 | medium_carmine,"Medium Carmine",#af4035,175,64,53 485 | medium_champagne,"Medium Champagne",#f3e5ab,243,229,171 486 | medium_electric_blue,"Medium Electric Blue",#035096,3,80,150 487 | medium_jungle_green,"Medium Jungle Green",#1c352d,28,53,45 488 | medium_lavender_magenta,"Medium Lavender Magenta",#dda0dd,221,160,221 489 | medium_orchid,"Medium Orchid",#ba55d3,186,85,211 490 | medium_persian_blue,"Medium Persian Blue",#0067a5,0,103,165 491 | medium_purple,"Medium Purple",#9370db,147,112,219 492 | medium_red_violet,"Medium Red-Violet",#bb3385,187,51,133 493 | medium_ruby,"Medium Ruby",#aa4069,170,64,105 494 | medium_sea_green,"Medium Sea Green",#3cb371,60,179,113 495 | medium_slate_blue,"Medium Slate Blue",#7b68ee,123,104,238 496 | medium_spring_bud,"Medium Spring Bud",#c9dc87,201,220,135 497 | medium_spring_green,"Medium Spring Green",#00fa9a,0,250,154 498 | medium_taupe,"Medium Taupe",#674c47,103,76,71 499 | medium_turquoise,"Medium Turquoise",#48d1cc,72,209,204 500 | medium_tuscan_red,"Medium Tuscan Red",#79443b,121,68,59 501 | medium_vermilion,"Medium Vermilion",#d9603b,217,96,59 502 | medium_violet_red,"Medium Violet-Red",#c71585,199,21,133 503 | mellow_apricot,"Mellow Apricot",#f8b878,248,184,120 504 | mellow_yellow,"Mellow Yellow",#f8de7e,248,222,126 505 | melon,"Melon",#fdbcb4,253,188,180 506 | midnight_blue,"Midnight Blue",#191970,25,25,112 507 | midnight_green_eagle_green,"Midnight Green (Eagle Green)",#004953,0,73,83 508 | mikado_yellow,"Mikado Yellow",#ffc40c,255,196,12 509 | mint,"Mint",#3eb489,62,180,137 510 | mint_cream,"Mint Cream",#f5fffa,245,255,250 511 | mint_green,"Mint Green",#98ff98,152,255,152 512 | misty_rose,"Misty Rose",#ffe4e1,255,228,225 513 | moccasin,"Moccasin",#faebd7,250,235,215 514 | mode_beige,"Mode Beige",#967117,150,113,23 515 | moonstone_blue,"Moonstone Blue",#73a9c2,115,169,194 516 | mordant_red_19,"Mordant Red 19",#ae0c00,174,12,0 517 | moss_green,"Moss Green",#addfad,173,223,173 518 | mountain_meadow,"Mountain Meadow",#30ba8f,48,186,143 519 | mountbatten_pink,"Mountbatten Pink",#997a8d,153,122,141 520 | msu_green,"Msu Green",#18453b,24,69,59 521 | mulberry,"Mulberry",#c54b8c,197,75,140 522 | mustard,"Mustard",#ffdb58,255,219,88 523 | myrtle,"Myrtle",#21421e,33,66,30 524 | nadeshiko_pink,"Nadeshiko Pink",#f6adc6,246,173,198 525 | napier_green,"Napier Green",#2a8000,42,128,0 526 | naples_yellow,"Naples Yellow",#fada5e,250,218,94 527 | navajo_white,"Navajo White",#ffdead,255,222,173 528 | navy_blue,"Navy Blue",#000080,0,0,128 529 | neon_carrot,"Neon Carrot",#ffa343,255,163,67 530 | neon_fuchsia,"Neon Fuchsia",#fe4164,254,65,100 531 | neon_green,"Neon Green",#39ff14,57,255,20 532 | new_york_pink,"New York Pink",#d7837f,215,131,127 533 | non_photo_blue,"Non-Photo Blue",#a4dded,164,221,237 534 | north_texas_green,"North Texas Green",#059033,5,144,51 535 | ocean_boat_blue,"Ocean Boat Blue",#0077be,0,119,190 536 | ochre,"Ochre",#c72,204,119,34 537 | office_green,"Office Green",#008000,0,128,0 538 | old_gold,"Old Gold",#cfb53b,207,181,59 539 | old_lace,"Old Lace",#fdf5e6,253,245,230 540 | old_lavender,"Old Lavender",#796878,121,104,120 541 | old_mauve,"Old Mauve",#673147,103,49,71 542 | old_rose,"Old Rose",#c08081,192,128,129 543 | olive,"Olive",#808000,128,128,0 544 | olive_drab_7,"Olive Drab #7",#3c341f,60,52,31 545 | olive_drab_web_olive_drab_3,"Olive Drab (Web) (Olive Drab #3)",#6b8e23,107,142,35 546 | olivine,"Olivine",#9ab973,154,185,115 547 | onyx,"Onyx",#353839,53,56,57 548 | opera_mauve,"Opera Mauve",#b784a7,183,132,167 549 | orange_color_wheel,"Orange (Color Wheel)",#ff7f00,255,127,0 550 | orange_peel,"Orange Peel",#ff9f00,255,159,0 551 | orange_red,"Orange-Red",#ff4500,255,69,0 552 | orange_ryb,"Orange (Ryb)",#fb9902,251,153,2 553 | orange_web_color,"Orange (Web Color)",#ffa500,255,165,0 554 | orchid,"Orchid",#da70d6,218,112,214 555 | otter_brown,"Otter Brown",#654321,101,67,33 556 | ou_crimson_red,"Ou Crimson Red",#900,153,0,0 557 | outer_space,"Outer Space",#414a4c,65,74,76 558 | outrageous_orange,"Outrageous Orange",#ff6e4a,255,110,74 559 | oxford_blue,"Oxford Blue",#002147,0,33,71 560 | pakistan_green,"Pakistan Green",#060,0,102,0 561 | palatinate_blue,"Palatinate Blue",#273be2,39,59,226 562 | palatinate_purple,"Palatinate Purple",#682860,104,40,96 563 | pale_aqua,"Pale Aqua",#bcd4e6,188,212,230 564 | pale_blue,"Pale Blue",#afeeee,175,238,238 565 | pale_brown,"Pale Brown",#987654,152,118,84 566 | pale_carmine,"Pale Carmine",#af4035,175,64,53 567 | pale_cerulean,"Pale Cerulean",#9bc4e2,155,196,226 568 | pale_chestnut,"Pale Chestnut",#ddadaf,221,173,175 569 | pale_copper,"Pale Copper",#da8a67,218,138,103 570 | pale_cornflower_blue,"Pale Cornflower Blue",#abcdef,171,205,239 571 | pale_gold,"Pale Gold",#e6be8a,230,190,138 572 | pale_goldenrod,"Pale Goldenrod",#eee8aa,238,232,170 573 | pale_green,"Pale Green",#98fb98,152,251,152 574 | pale_lavender,"Pale Lavender",#dcd0ff,220,208,255 575 | pale_magenta,"Pale Magenta",#f984e5,249,132,229 576 | pale_pink,"Pale Pink",#fadadd,250,218,221 577 | pale_plum,"Pale Plum",#dda0dd,221,160,221 578 | pale_red_violet,"Pale Red-Violet",#db7093,219,112,147 579 | pale_robin_egg_blue,"Pale Robin Egg Blue",#96ded1,150,222,209 580 | pale_silver,"Pale Silver",#c9c0bb,201,192,187 581 | pale_spring_bud,"Pale Spring Bud",#ecebbd,236,235,189 582 | pale_taupe,"Pale Taupe",#bc987e,188,152,126 583 | pale_violet_red,"Pale Violet-Red",#db7093,219,112,147 584 | pansy_purple,"Pansy Purple",#78184a,120,24,74 585 | papaya_whip,"Papaya Whip",#ffefd5,255,239,213 586 | paris_green,"Paris Green",#50c878,80,200,120 587 | pastel_blue,"Pastel Blue",#aec6cf,174,198,207 588 | pastel_brown,"Pastel Brown",#836953,131,105,83 589 | pastel_gray,"Pastel Gray",#cfcfc4,207,207,196 590 | pastel_green,"Pastel Green",#7d7,119,221,119 591 | pastel_magenta,"Pastel Magenta",#f49ac2,244,154,194 592 | pastel_orange,"Pastel Orange",#ffb347,255,179,71 593 | pastel_pink,"Pastel Pink",#dea5a4,222,165,164 594 | pastel_purple,"Pastel Purple",#b39eb5,179,158,181 595 | pastel_red,"Pastel Red",#ff6961,255,105,97 596 | pastel_violet,"Pastel Violet",#cb99c9,203,153,201 597 | pastel_yellow,"Pastel Yellow",#fdfd96,253,253,150 598 | patriarch,"Patriarch",#800080,128,0,128 599 | payne_s_grey,"Payne'S Grey",#536878,83,104,120 600 | peach,"Peach",#ffe5b4,255,229,180 601 | peach_crayola,"Peach (Crayola)",#ffcba4,255,203,164 602 | peach_orange,"Peach-Orange",#fc9,255,204,153 603 | peach_puff,"Peach Puff",#ffdab9,255,218,185 604 | peach_yellow,"Peach-Yellow",#fadfad,250,223,173 605 | pear,"Pear",#d1e231,209,226,49 606 | pearl,"Pearl",#eae0c8,234,224,200 607 | pearl_aqua,"Pearl Aqua",#88d8c0,136,216,192 608 | pearly_purple,"Pearly Purple",#b768a2,183,104,162 609 | peridot,"Peridot",#e6e200,230,226,0 610 | periwinkle,"Periwinkle",#ccf,204,204,255 611 | persian_blue,"Persian Blue",#1c39bb,28,57,187 612 | persian_green,"Persian Green",#00a693,0,166,147 613 | persian_indigo,"Persian Indigo",#32127a,50,18,122 614 | persian_orange,"Persian Orange",#d99058,217,144,88 615 | persian_pink,"Persian Pink",#f77fbe,247,127,190 616 | persian_plum,"Persian Plum",#701c1c,112,28,28 617 | persian_red,"Persian Red",#c33,204,51,51 618 | persian_rose,"Persian Rose",#fe28a2,254,40,162 619 | persimmon,"Persimmon",#ec5800,236,88,0 620 | peru,"Peru",#cd853f,205,133,63 621 | phlox,"Phlox",#df00ff,223,0,255 622 | phthalo_blue,"Phthalo Blue",#000f89,0,15,137 623 | phthalo_green,"Phthalo Green",#123524,18,53,36 624 | piggy_pink,"Piggy Pink",#fddde6,253,221,230 625 | pine_green,"Pine Green",#01796f,1,121,111 626 | pink,"Pink",#ffc0cb,255,192,203 627 | pink_lace,"Pink Lace",#ffddf4,255,221,244 628 | pink_orange,"Pink-Orange",#f96,255,153,102 629 | pink_pearl,"Pink Pearl",#e7accf,231,172,207 630 | pink_sherbet,"Pink Sherbet",#f78fa7,247,143,167 631 | pistachio,"Pistachio",#93c572,147,197,114 632 | platinum,"Platinum",#e5e4e2,229,228,226 633 | plum_traditional,"Plum (Traditional)",#8e4585,142,69,133 634 | plum_web,"Plum (Web)",#dda0dd,221,160,221 635 | portland_orange,"Portland Orange",#ff5a36,255,90,54 636 | powder_blue_web,"Powder Blue (Web)",#b0e0e6,176,224,230 637 | princeton_orange,"Princeton Orange",#ff8f00,255,143,0 638 | prune,"Prune",#701c1c,112,28,28 639 | prussian_blue,"Prussian Blue",#003153,0,49,83 640 | psychedelic_purple,"Psychedelic Purple",#df00ff,223,0,255 641 | puce,"Puce",#c89,204,136,153 642 | pumpkin,"Pumpkin",#ff7518,255,117,24 643 | purple_heart,"Purple Heart",#69359c,105,53,156 644 | purple_html_css,"Purple (Html/Css)",#800080,128,0,128 645 | purple_mountain_majesty,"Purple Mountain Majesty",#9678b6,150,120,182 646 | purple_munsell,"Purple (Munsell)",#9f00c5,159,0,197 647 | purple_pizzazz,"Purple Pizzazz",#fe4eda,254,78,218 648 | purple_taupe,"Purple Taupe",#50404d,80,64,77 649 | purple_x11,"Purple (X11)",#a020f0,160,32,240 650 | quartz,"Quartz",#51484f,81,72,79 651 | rackley,"Rackley",#5d8aa8,93,138,168 652 | radical_red,"Radical Red",#ff355e,255,53,94 653 | rajah,"Rajah",#fbab60,251,171,96 654 | raspberry,"Raspberry",#e30b5d,227,11,93 655 | raspberry_glace,"Raspberry Glace",#915f6d,145,95,109 656 | raspberry_pink,"Raspberry Pink",#e25098,226,80,152 657 | raspberry_rose,"Raspberry Rose",#b3446c,179,68,108 658 | raw_umber,"Raw Umber",#826644,130,102,68 659 | razzle_dazzle_rose,"Razzle Dazzle Rose",#f3c,255,51,204 660 | razzmatazz,"Razzmatazz",#e3256b,227,37,107 661 | red,"Red",#f00,255,0,0 662 | red_brown,"Red-Brown",#a52a2a,165,42,42 663 | red_devil,"Red Devil",#860111,134,1,17 664 | red_munsell,"Red (Munsell)",#f2003c,242,0,60 665 | red_ncs,"Red (Ncs)",#c40233,196,2,51 666 | red_orange,"Red-Orange",#ff5349,255,83,73 667 | red_pigment,"Red (Pigment)",#ed1c24,237,28,36 668 | red_ryb,"Red (Ryb)",#fe2712,254,39,18 669 | red_violet,"Red-Violet",#c71585,199,21,133 670 | redwood,"Redwood",#ab4e52,171,78,82 671 | regalia,"Regalia",#522d80,82,45,128 672 | resolution_blue,"Resolution Blue",#002387,0,35,135 673 | rich_black,"Rich Black",#004040,0,64,64 674 | rich_brilliant_lavender,"Rich Brilliant Lavender",#f1a7fe,241,167,254 675 | rich_carmine,"Rich Carmine",#d70040,215,0,64 676 | rich_electric_blue,"Rich Electric Blue",#0892d0,8,146,208 677 | rich_lavender,"Rich Lavender",#a76bcf,167,107,207 678 | rich_lilac,"Rich Lilac",#b666d2,182,102,210 679 | rich_maroon,"Rich Maroon",#b03060,176,48,96 680 | rifle_green,"Rifle Green",#414833,65,72,51 681 | robin_egg_blue,"Robin Egg Blue",#0cc,0,204,204 682 | rose,"Rose",#ff007f,255,0,127 683 | rose_bonbon,"Rose Bonbon",#f9429e,249,66,158 684 | rose_ebony,"Rose Ebony",#674846,103,72,70 685 | rose_gold,"Rose Gold",#b76e79,183,110,121 686 | rose_madder,"Rose Madder",#e32636,227,38,54 687 | rose_pink,"Rose Pink",#f6c,255,102,204 688 | rose_quartz,"Rose Quartz",#aa98a9,170,152,169 689 | rose_taupe,"Rose Taupe",#905d5d,144,93,93 690 | rose_vale,"Rose Vale",#ab4e52,171,78,82 691 | rosewood,"Rosewood",#65000b,101,0,11 692 | rosso_corsa,"Rosso Corsa",#d40000,212,0,0 693 | rosy_brown,"Rosy Brown",#bc8f8f,188,143,143 694 | royal_azure,"Royal Azure",#0038a8,0,56,168 695 | royal_blue_traditional,"Royal Blue (Traditional)",#002366,0,35,102 696 | royal_blue_web,"Royal Blue (Web)",#4169e1,65,105,225 697 | royal_fuchsia,"Royal Fuchsia",#ca2c92,202,44,146 698 | royal_purple,"Royal Purple",#7851a9,120,81,169 699 | royal_yellow,"Royal Yellow",#fada5e,250,218,94 700 | rubine_red,"Rubine Red",#d10056,209,0,86 701 | ruby,"Ruby",#e0115f,224,17,95 702 | ruby_red,"Ruby Red",#9b111e,155,17,30 703 | ruddy,"Ruddy",#ff0028,255,0,40 704 | ruddy_brown,"Ruddy Brown",#bb6528,187,101,40 705 | ruddy_pink,"Ruddy Pink",#e18e96,225,142,150 706 | rufous,"Rufous",#a81c07,168,28,7 707 | russet,"Russet",#80461b,128,70,27 708 | rust,"Rust",#b7410e,183,65,14 709 | rusty_red,"Rusty Red",#da2c43,218,44,67 710 | sacramento_state_green,"Sacramento State Green",#00563f,0,86,63 711 | saddle_brown,"Saddle Brown",#8b4513,139,69,19 712 | safety_orange_blaze_orange,"Safety Orange (Blaze Orange)",#ff6700,255,103,0 713 | saffron,"Saffron",#f4c430,244,196,48 714 | salmon,"Salmon",#ff8c69,255,140,105 715 | salmon_pink,"Salmon Pink",#ff91a4,255,145,164 716 | sand,"Sand",#c2b280,194,178,128 717 | sand_dune,"Sand Dune",#967117,150,113,23 718 | sandstorm,"Sandstorm",#ecd540,236,213,64 719 | sandy_brown,"Sandy Brown",#f4a460,244,164,96 720 | sandy_taupe,"Sandy Taupe",#967117,150,113,23 721 | sangria,"Sangria",#92000a,146,0,10 722 | sap_green,"Sap Green",#507d2a,80,125,42 723 | sapphire,"Sapphire",#0f52ba,15,82,186 724 | sapphire_blue,"Sapphire Blue",#0067a5,0,103,165 725 | satin_sheen_gold,"Satin Sheen Gold",#cba135,203,161,53 726 | scarlet,"Scarlet",#ff2400,255,36,0 727 | scarlet_crayola,"Scarlet (Crayola)",#fd0e35,253,14,53 728 | school_bus_yellow,"School Bus Yellow",#ffd800,255,216,0 729 | screamin_green,"Screamin' Green",#76ff7a,118,255,122 730 | sea_blue,"Sea Blue",#006994,0,105,148 731 | sea_green,"Sea Green",#2e8b57,46,139,87 732 | seal_brown,"Seal Brown",#321414,50,20,20 733 | seashell,"Seashell",#fff5ee,255,245,238 734 | selective_yellow,"Selective Yellow",#ffba00,255,186,0 735 | sepia,"Sepia",#704214,112,66,20 736 | shadow,"Shadow",#8a795d,138,121,93 737 | shamrock_green,"Shamrock Green",#009e60,0,158,96 738 | shocking_pink,"Shocking Pink",#fc0fc0,252,15,192 739 | shocking_pink_crayola,"Shocking Pink (Crayola)",#ff6fff,255,111,255 740 | sienna,"Sienna",#882d17,136,45,23 741 | silver,"Silver",#c0c0c0,192,192,192 742 | sinopia,"Sinopia",#cb410b,203,65,11 743 | skobeloff,"Skobeloff",#007474,0,116,116 744 | sky_blue,"Sky Blue",#87ceeb,135,206,235 745 | sky_magenta,"Sky Magenta",#cf71af,207,113,175 746 | slate_blue,"Slate Blue",#6a5acd,106,90,205 747 | slate_gray,"Slate Gray",#708090,112,128,144 748 | smalt_dark_powder_blue,"Smalt (Dark Powder Blue)",#039,0,51,153 749 | smokey_topaz,"Smokey Topaz",#933d41,147,61,65 750 | smoky_black,"Smoky Black",#100c08,16,12,8 751 | snow,"Snow",#fffafa,255,250,250 752 | spiro_disco_ball,"Spiro Disco Ball",#0fc0fc,15,192,252 753 | spring_bud,"Spring Bud",#a7fc00,167,252,0 754 | spring_green,"Spring Green",#00ff7f,0,255,127 755 | st_patrick_s_blue,"St. Patrick'S Blue",#23297a,35,41,122 756 | steel_blue,"Steel Blue",#4682b4,70,130,180 757 | stil_de_grain_yellow,"Stil De Grain Yellow",#fada5e,250,218,94 758 | stizza,"Stizza",#900,153,0,0 759 | stormcloud,"Stormcloud",#4f666a,79,102,106 760 | straw,"Straw",#e4d96f,228,217,111 761 | sunglow,"Sunglow",#fc3,255,204,51 762 | sunset,"Sunset",#fad6a5,250,214,165 763 | tan,"Tan",#d2b48c,210,180,140 764 | tangelo,"Tangelo",#f94d00,249,77,0 765 | tangerine,"Tangerine",#f28500,242,133,0 766 | tangerine_yellow,"Tangerine Yellow",#fc0,255,204,0 767 | tango_pink,"Tango Pink",#e4717a,228,113,122 768 | taupe,"Taupe",#483c32,72,60,50 769 | taupe_gray,"Taupe Gray",#8b8589,139,133,137 770 | tea_green,"Tea Green",#d0f0c0,208,240,192 771 | tea_rose_orange,"Tea Rose (Orange)",#f88379,248,131,121 772 | tea_rose_rose,"Tea Rose (Rose)",#f4c2c2,244,194,194 773 | teal,"Teal",#008080,0,128,128 774 | teal_blue,"Teal Blue",#367588,54,117,136 775 | teal_green,"Teal Green",#00827f,0,130,127 776 | telemagenta,"Telemagenta",#cf3476,207,52,118 777 | tenn_tawny,"Tenné (Tawny)",#cd5700,205,87,0 778 | terra_cotta,"Terra Cotta",#e2725b,226,114,91 779 | thistle,"Thistle",#d8bfd8,216,191,216 780 | thulian_pink,"Thulian Pink",#de6fa1,222,111,161 781 | tickle_me_pink,"Tickle Me Pink",#fc89ac,252,137,172 782 | tiffany_blue,"Tiffany Blue",#0abab5,10,186,181 783 | tiger_s_eye,"Tiger'S Eye",#e08d3c,224,141,60 784 | timberwolf,"Timberwolf",#dbd7d2,219,215,210 785 | titanium_yellow,"Titanium Yellow",#eee600,238,230,0 786 | tomato,"Tomato",#ff6347,255,99,71 787 | toolbox,"Toolbox",#746cc0,116,108,192 788 | topaz,"Topaz",#ffc87c,255,200,124 789 | tractor_red,"Tractor Red",#fd0e35,253,14,53 790 | trolley_grey,"Trolley Grey",#808080,128,128,128 791 | tropical_rain_forest,"Tropical Rain Forest",#00755e,0,117,94 792 | true_blue,"True Blue",#0073cf,0,115,207 793 | tufts_blue,"Tufts Blue",#417dc1,65,125,193 794 | tumbleweed,"Tumbleweed",#deaa88,222,170,136 795 | turkish_rose,"Turkish Rose",#b57281,181,114,129 796 | turquoise,"Turquoise",#30d5c8,48,213,200 797 | turquoise_blue,"Turquoise Blue",#00ffef,0,255,239 798 | turquoise_green,"Turquoise Green",#a0d6b4,160,214,180 799 | tuscan_red,"Tuscan Red",#7c4848,124,72,72 800 | twilight_lavender,"Twilight Lavender",#8a496b,138,73,107 801 | tyrian_purple,"Tyrian Purple",#66023c,102,2,60 802 | ua_blue,"Ua Blue",#03a,0,51,170 803 | ua_red,"Ua Red",#d9004c,217,0,76 804 | ube,"Ube",#8878c3,136,120,195 805 | ucla_blue,"Ucla Blue",#536895,83,104,149 806 | ucla_gold,"Ucla Gold",#ffb300,255,179,0 807 | ufo_green,"Ufo Green",#3cd070,60,208,112 808 | ultra_pink,"Ultra Pink",#ff6fff,255,111,255 809 | ultramarine,"Ultramarine",#120a8f,18,10,143 810 | ultramarine_blue,"Ultramarine Blue",#4166f5,65,102,245 811 | umber,"Umber",#635147,99,81,71 812 | unbleached_silk,"Unbleached Silk",#ffddca,255,221,202 813 | united_nations_blue,"United Nations Blue",#5b92e5,91,146,229 814 | university_of_california_gold,"University Of California Gold",#b78727,183,135,39 815 | unmellow_yellow,"Unmellow Yellow",#ff6,255,255,102 816 | up_forest_green,"Up Forest Green",#014421,1,68,33 817 | up_maroon,"Up Maroon",#7b1113,123,17,19 818 | upsdell_red,"Upsdell Red",#ae2029,174,32,41 819 | urobilin,"Urobilin",#e1ad21,225,173,33 820 | usafa_blue,"Usafa Blue",#004f98,0,79,152 821 | usc_cardinal,"Usc Cardinal",#900,153,0,0 822 | usc_gold,"Usc Gold",#fc0,255,204,0 823 | utah_crimson,"Utah Crimson",#d3003f,211,0,63 824 | vanilla,"Vanilla",#f3e5ab,243,229,171 825 | vegas_gold,"Vegas Gold",#c5b358,197,179,88 826 | venetian_red,"Venetian Red",#c80815,200,8,21 827 | verdigris,"Verdigris",#43b3ae,67,179,174 828 | vermilion_cinnabar,"Vermilion (Cinnabar)",#e34234,227,66,52 829 | vermilion_plochere,"Vermilion (Plochere)",#d9603b,217,96,59 830 | veronica,"Veronica",#a020f0,160,32,240 831 | violet,"Violet",#8f00ff,143,0,255 832 | violet_blue,"Violet-Blue",#324ab2,50,74,178 833 | violet_color_wheel,"Violet (Color Wheel)",#7f00ff,127,0,255 834 | violet_ryb,"Violet (Ryb)",#8601af,134,1,175 835 | violet_web,"Violet (Web)",#ee82ee,238,130,238 836 | viridian,"Viridian",#40826d,64,130,109 837 | vivid_auburn,"Vivid Auburn",#922724,146,39,36 838 | vivid_burgundy,"Vivid Burgundy",#9f1d35,159,29,53 839 | vivid_cerise,"Vivid Cerise",#da1d81,218,29,129 840 | vivid_tangerine,"Vivid Tangerine",#ffa089,255,160,137 841 | vivid_violet,"Vivid Violet",#9f00ff,159,0,255 842 | warm_black,"Warm Black",#004242,0,66,66 843 | waterspout,"Waterspout",#a4f4f9,164,244,249 844 | wenge,"Wenge",#645452,100,84,82 845 | wheat,"Wheat",#f5deb3,245,222,179 846 | white,"White",#fff,255,255,255 847 | white_smoke,"White Smoke",#f5f5f5,245,245,245 848 | wild_blue_yonder,"Wild Blue Yonder",#a2add0,162,173,208 849 | wild_strawberry,"Wild Strawberry",#ff43a4,255,67,164 850 | wild_watermelon,"Wild Watermelon",#fc6c85,252,108,133 851 | wine,"Wine",#722f37,114,47,55 852 | wine_dregs,"Wine Dregs",#673147,103,49,71 853 | wisteria,"Wisteria",#c9a0dc,201,160,220 854 | wood_brown,"Wood Brown",#c19a6b,193,154,107 855 | xanadu,"Xanadu",#738678,115,134,120 856 | yale_blue,"Yale Blue",#0f4d92,15,77,146 857 | yellow,"Yellow",#ff0,255,255,0 858 | yellow_green,"Yellow-Green",#9acd32,154,205,50 859 | yellow_munsell,"Yellow (Munsell)",#efcc00,239,204,0 860 | yellow_ncs,"Yellow (Ncs)",#ffd300,255,211,0 861 | yellow_orange,"Yellow Orange",#ffae42,255,174,66 862 | yellow_process,"Yellow (Process)",#ffef00,255,239,0 863 | yellow_ryb,"Yellow (Ryb)",#fefe33,254,254,51 864 | zaffre,"Zaffre",#0014a8,0,20,168 865 | zinnwaldite_brown,"Zinnwaldite Brown",#2c1608,44,22,8 866 | -------------------------------------------------------------------------------- /color palette using OpenCV.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "# Python program to create RGB color palette with trackbars \n", 11 | "import cv2 \n", 12 | "import numpy as np \n", 13 | "\n", 14 | "def emptyFunction(): \n", 15 | " pass\n", 16 | " \n", 17 | "def main(): \n", 18 | " image = np.zeros((512, 512, 3), np.uint8) \n", 19 | " windowName =\"Open CV Color Palette\"\n", 20 | " cv2.namedWindow(windowName) \n", 21 | " \n", 22 | " cv2.createTrackbar('Blue', windowName, 0, 255, emptyFunction) \n", 23 | " cv2.createTrackbar('Green', windowName, 0, 255, emptyFunction) \n", 24 | " cv2.createTrackbar('Red', windowName, 0, 255, emptyFunction) \n", 25 | " \n", 26 | " while(True): \n", 27 | " cv2.imshow(windowName, image) \n", 28 | " \n", 29 | " if cv2.waitKey(1) == 27: \n", 30 | " break\n", 31 | " \n", 32 | " blue = cv2.getTrackbarPos('Blue', windowName) \n", 33 | " green = cv2.getTrackbarPos('Green', windowName) \n", 34 | " red = cv2.getTrackbarPos('Red', windowName) \n", 35 | " \n", 36 | " image[:] = [blue, green, red] \n", 37 | " print(blue, green, red) \n", 38 | " \n", 39 | " cv2.destroyAllWindows() \n", 40 | " \n", 41 | "if __name__==\"__main__\": \n", 42 | " main() " 43 | ] 44 | } 45 | ], 46 | "metadata": { 47 | "kernelspec": { 48 | "display_name": "Python 3", 49 | "language": "python", 50 | "name": "python3" 51 | }, 52 | "language_info": { 53 | "codemirror_mode": { 54 | "name": "ipython", 55 | "version": 3 56 | }, 57 | "file_extension": ".py", 58 | "mimetype": "text/x-python", 59 | "name": "python", 60 | "nbconvert_exporter": "python", 61 | "pygments_lexer": "ipython3", 62 | "version": "3.7.4" 63 | } 64 | }, 65 | "nbformat": 4, 66 | "nbformat_minor": 2 67 | } 68 | -------------------------------------------------------------------------------- /contrast enhancing of color images using opencv.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "#contrast enhancing in color image\n", 11 | "import cv2\n", 12 | "import numpy as np\n", 13 | "img = cv2.imread('E://OpenCV//hi.png')\n", 14 | "img=cv2.resize(img,(500,500))\n", 15 | "img_yuv = cv2.cvtColor(img, cv2.COLOR_BGR2YUV)\n", 16 | "\n", 17 | "img_yuv[:,:,0] = cv2.equalizeHist(img_yuv[:,:,0])\n", 18 | "\n", 19 | "img_output = cv2.cvtColor(img_yuv, cv2.COLOR_YUV2BGR)\n", 20 | "cv2.imshow('Color input image', img)\n", 21 | "cv2.imshow('Histogram equalized', img_output)\n", 22 | "cv2.waitKey(0)\n", 23 | "cv2.destroyAllWindows()" 24 | ] 25 | } 26 | ], 27 | "metadata": { 28 | "kernelspec": { 29 | "display_name": "Python 3", 30 | "language": "python", 31 | "name": "python3" 32 | }, 33 | "language_info": { 34 | "codemirror_mode": { 35 | "name": "ipython", 36 | "version": 3 37 | }, 38 | "file_extension": ".py", 39 | "mimetype": "text/x-python", 40 | "name": "python", 41 | "nbconvert_exporter": "python", 42 | "pygments_lexer": "ipython3", 43 | "version": "3.7.4" 44 | } 45 | }, 46 | "nbformat": 4, 47 | "nbformat_minor": 2 48 | } 49 | -------------------------------------------------------------------------------- /contrast enhancing of gray scale image using opencv.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "#contrast enchancing in grayscale image\n", 11 | "import cv2\n", 12 | "import numpy as np\n", 13 | "img = cv2.imread('E://OpenCV//histog.png', 0)\n", 14 | "img=cv2.resize(img,(500,500))\n", 15 | "histeq = cv2.equalizeHist(img)\n", 16 | "cv2.imshow('Input', img)\n", 17 | "cv2.imshow('Histogram equalized', histeq)\n", 18 | "cv2.waitKey(0)\n", 19 | "cv2.destroyAllWindows()" 20 | ] 21 | } 22 | ], 23 | "metadata": { 24 | "kernelspec": { 25 | "display_name": "Python 3", 26 | "language": "python", 27 | "name": "python3" 28 | }, 29 | "language_info": { 30 | "codemirror_mode": { 31 | "name": "ipython", 32 | "version": 3 33 | }, 34 | "file_extension": ".py", 35 | "mimetype": "text/x-python", 36 | "name": "python", 37 | "nbconvert_exporter": "python", 38 | "pygments_lexer": "ipython3", 39 | "version": "3.7.4" 40 | } 41 | }, 42 | "nbformat": 4, 43 | "nbformat_minor": 2 44 | } 45 | -------------------------------------------------------------------------------- /document scanner.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "#document scanner using simple python code\n", 11 | "import numpy as np\n", 12 | "import cv2\n", 13 | "import imutils\n", 14 | "\n", 15 | "args_image =\"E://OpenCV//docu1.jpg\"\n", 16 | "\n", 17 | "image = cv2.imread(args_image)\n", 18 | "image=cv2.resize(image,(500,500))\n", 19 | "orig = image.copy()\n", 20 | "cv2.imshow(\"Original Image\", image)\n", 21 | "cv2.waitKey(0)\n", 22 | "cv2.destroyAllWindows()\n", 23 | "\n", 24 | "grayImage = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n", 25 | "grayImageBlur = cv2.blur(grayImage,(2,2))\n", 26 | "edgedImage = cv2.Canny(grayImageBlur, 100, 300, 3)\n", 27 | "\n", 28 | "cv2.imshow(\"gray\", grayImage)\n", 29 | "cv2.waitKey(0)\n", 30 | "cv2.destroyAllWindows()\n", 31 | "cv2.imshow(\"grayBlur\", grayImageBlur)\n", 32 | "cv2.waitKey(0)\n", 33 | "cv2.destroyAllWindows()\n", 34 | "cv2.imshow(\"Edge Detected Image\", edgedImage)\n", 35 | "cv2.waitKey(0)\n", 36 | "cv2.destroyAllWindows()\n", 37 | "\n", 38 | "allContours = cv2.findContours(edgedImage.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)\n", 39 | "allContours = imutils.grab_contours(allContours)\n", 40 | "allContours = sorted(allContours, key=cv2.contourArea, reverse=True)[:1]\n", 41 | "\n", 42 | "perimeter = cv2.arcLength(allContours[0], True) \n", 43 | "ROIdimensions = cv2.approxPolyDP(allContours[0], 0.02*perimeter, True)\n", 44 | "cv2.drawContours(image, [ROIdimensions], -1, (0,255,0), 2)\n", 45 | "cv2.imshow(\"Contour Outline\", image)\n", 46 | "cv2.waitKey(0)\n", 47 | "cv2.destroyAllWindows()\n", 48 | "ROIdimensions = ROIdimensions.reshape(4,2)\n", 49 | "rect = np.zeros((4,2), dtype=\"float32\")\n", 50 | "s = np.sum(ROIdimensions, axis=1)\n", 51 | "rect[0] = ROIdimensions[np.argmin(s)]\n", 52 | "rect[2] = ROIdimensions[np.argmax(s)]\n", 53 | "diff = np.diff(ROIdimensions, axis=1)\n", 54 | "rect[1] = ROIdimensions[np.argmin(diff)]\n", 55 | "rect[3] = ROIdimensions[np.argmax(diff)]\n", 56 | "\n", 57 | "(tl, tr, br, bl) = rect\n", 58 | "\n", 59 | "widthA = np.sqrt((tl[0] -tr[0])**2 + (tl[1] - tr[1])**2 )\n", 60 | "widthB = np.sqrt((bl[0] - br[0])**2 + (bl[1] - br[1])**2 )\n", 61 | "maxWidth = max(int(widthA), int(widthB))\n", 62 | "\n", 63 | "heightA = np.sqrt((tl[0] - bl[0])**2 + (tl[1] - bl[1])**2 )\n", 64 | "heightB = np.sqrt((tr[0] - br[0])**2 + (tr[1] - br[1])**2 )\n", 65 | "maxHeight = max(int(heightA), int(heightB))\n", 66 | "dst = np.array([\n", 67 | " [0,0],\n", 68 | " [maxWidth-1, 0],\n", 69 | " [maxWidth-1, maxHeight-1],\n", 70 | " [0, maxHeight-1]], dtype=\"float32\")\n", 71 | "\n", 72 | "transformMatrix = cv2.getPerspectiveTransform(rect, dst)\n", 73 | "scan = cv2.warpPerspective(orig, transformMatrix, (maxWidth, maxHeight))\n", 74 | "cv2.imshow(\"Scaned\",scan)\n", 75 | "cv2.waitKey(0)\n", 76 | "cv2.destroyAllWindows()\n", 77 | "scanGray = cv2.cvtColor(scan, cv2.COLOR_BGR2GRAY)\n", 78 | "cv2.imshow(\"scanGray\", scanGray)\n", 79 | "cv2.waitKey(0)\n", 80 | "cv2.destroyAllWindows()\n", 81 | "from skimage.filters import threshold_local\n", 82 | "T = threshold_local(scanGray, 9, offset=8, method=\"gaussian\")\n", 83 | "scanBW = (scanGray > T).astype(\"uint8\") * 255\n", 84 | "cv2.imshow(\"scanned\", scanBW)\n", 85 | "cv2.waitKey(0)\n", 86 | "cv2.destroyAllWindows()\n" 87 | ] 88 | }, 89 | { 90 | "cell_type": "code", 91 | "execution_count": null, 92 | "metadata": {}, 93 | "outputs": [], 94 | "source": [] 95 | }, 96 | { 97 | "cell_type": "code", 98 | "execution_count": 1, 99 | "metadata": {}, 100 | "outputs": [], 101 | "source": [] 102 | }, 103 | { 104 | "cell_type": "code", 105 | "execution_count": null, 106 | "metadata": {}, 107 | "outputs": [], 108 | "source": [] 109 | }, 110 | { 111 | "cell_type": "code", 112 | "execution_count": null, 113 | "metadata": {}, 114 | "outputs": [], 115 | "source": [] 116 | }, 117 | { 118 | "cell_type": "code", 119 | "execution_count": null, 120 | "metadata": {}, 121 | "outputs": [], 122 | "source": [] 123 | }, 124 | { 125 | "cell_type": "code", 126 | "execution_count": null, 127 | "metadata": {}, 128 | "outputs": [], 129 | "source": [] 130 | }, 131 | { 132 | "cell_type": "code", 133 | "execution_count": null, 134 | "metadata": {}, 135 | "outputs": [], 136 | "source": [] 137 | }, 138 | { 139 | "cell_type": "code", 140 | "execution_count": null, 141 | "metadata": {}, 142 | "outputs": [], 143 | "source": [] 144 | } 145 | ], 146 | "metadata": { 147 | "kernelspec": { 148 | "display_name": "Python 3", 149 | "language": "python", 150 | "name": "python3" 151 | }, 152 | "language_info": { 153 | "codemirror_mode": { 154 | "name": "ipython", 155 | "version": 3 156 | }, 157 | "file_extension": ".py", 158 | "mimetype": "text/x-python", 159 | "name": "python", 160 | "nbconvert_exporter": "python", 161 | "pygments_lexer": "ipython3", 162 | "version": "3.7.4" 163 | } 164 | }, 165 | "nbformat": 4, 166 | "nbformat_minor": 2 167 | } 168 | -------------------------------------------------------------------------------- /image bluring using opencv python.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [ 8 | { 9 | "name": "stdout", 10 | "output_type": "stream", 11 | "text": [ 12 | "[[[0 0 0]\n", 13 | " [0 0 0]\n", 14 | " [0 0 0]\n", 15 | " ...\n", 16 | " [0 0 0]\n", 17 | " [0 0 0]\n", 18 | " [0 0 0]]\n", 19 | "\n", 20 | " [[0 0 0]\n", 21 | " [0 0 0]\n", 22 | " [0 0 0]\n", 23 | " ...\n", 24 | " [0 0 0]\n", 25 | " [0 0 0]\n", 26 | " [0 0 0]]\n", 27 | "\n", 28 | " [[0 0 0]\n", 29 | " [0 0 0]\n", 30 | " [0 0 0]\n", 31 | " ...\n", 32 | " [0 0 0]\n", 33 | " [0 0 0]\n", 34 | " [0 0 0]]\n", 35 | "\n", 36 | " ...\n", 37 | "\n", 38 | " [[0 0 0]\n", 39 | " [0 0 0]\n", 40 | " [0 0 0]\n", 41 | " ...\n", 42 | " [0 0 0]\n", 43 | " [0 0 0]\n", 44 | " [0 0 0]]\n", 45 | "\n", 46 | " [[0 0 0]\n", 47 | " [0 0 0]\n", 48 | " [0 0 0]\n", 49 | " ...\n", 50 | " [0 0 0]\n", 51 | " [0 0 0]\n", 52 | " [0 0 0]]\n", 53 | "\n", 54 | " [[0 0 0]\n", 55 | " [0 0 0]\n", 56 | " [0 0 0]\n", 57 | " ...\n", 58 | " [0 0 0]\n", 59 | " [0 0 0]\n", 60 | " [0 0 0]]]\n", 61 | "\n" 62 | ] 63 | } 64 | ], 65 | "source": [ 66 | "#programming_fever\n", 67 | "#image bluring\n", 68 | "import cv2 \n", 69 | "import numpy as np \n", 70 | " \n", 71 | "imag = cv2.imread('E://OpenCV//programming_fever_.logo.jpg') \n", 72 | "image = cv2.resize(imag, (0, 0), fx =0.1, fy =0.1) \n", 73 | "\n", 74 | "blur_filter1 = np.ones((3, 3), np.float)/(9.0) \n", 75 | " \n", 76 | "blur_filter2 = np.ones((5, 5), np.float)/(25.0) \n", 77 | " \n", 78 | "blur_filter3 = np.ones((7, 7), np.float)/(49.0) \n", 79 | " \n", 80 | "image_blur1 = cv2.filter2D(image, -1, blur_filter1) \n", 81 | "image_blur2 = cv2.filter2D(image, -1, blur_filter2) \n", 82 | "image_blur3 = cv2.filter2D(image, -1, blur_filter3) \n", 83 | "print(image) \n", 84 | "print(type(image))\n", 85 | "cv2.imshow('programming_fever.logo.ORIGINAL', image) \n", 86 | "cv2.imshow('programming_fever.logo.BLUR1', image_blur1) \n", 87 | "cv2.imshow('programming_fever.logo.BLUR2', image_blur2) \n", 88 | "cv2.imshow('programming_fever.logo.BLUR3', image_blur3) \n", 89 | " \n", 90 | "cv2.waitKey(0) \n", 91 | "cv2.destroyAllWindows()" 92 | ] 93 | }, 94 | { 95 | "cell_type": "code", 96 | "execution_count": null, 97 | "metadata": {}, 98 | "outputs": [], 99 | "source": [] 100 | } 101 | ], 102 | "metadata": { 103 | "kernelspec": { 104 | "display_name": "Python 3", 105 | "language": "python", 106 | "name": "python3" 107 | }, 108 | "language_info": { 109 | "codemirror_mode": { 110 | "name": "ipython", 111 | "version": 3 112 | }, 113 | "file_extension": ".py", 114 | "mimetype": "text/x-python", 115 | "name": "python", 116 | "nbconvert_exporter": "python", 117 | "pygments_lexer": "ipython3", 118 | "version": "3.7.4" 119 | } 120 | }, 121 | "nbformat": 4, 122 | "nbformat_minor": 2 123 | } 124 | -------------------------------------------------------------------------------- /image resizing using opencv.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "#image resizing\n", 11 | "import cv2 \n", 12 | "import numpy as np \n", 13 | "import matplotlib.pyplot as plt \n", 14 | "%matplotlib qt \n", 15 | " \n", 16 | "image = cv2.imread(\"E://OpenCV//programming_fever_.logo.jpg\", 1) \n", 17 | " \n", 18 | "half = cv2.resize(image, (0, 0), fx = 0.1, fy = 0.1) \n", 19 | "bigger = cv2.resize(image, (1050, 1610)) \n", 20 | " \n", 21 | "stretch_near = cv2.resize(image, (780, 540), \n", 22 | " interpolation = cv2.INTER_NEAREST) \n", 23 | " \n", 24 | "Titles =[\"Original\", \"Half\", \"Bigger\", \"Interpolation Nearest\"] \n", 25 | "images =[image, half, bigger, stretch_near] \n", 26 | "count = 4\n", 27 | " \n", 28 | "for i in range(count): \n", 29 | " plt.subplot(2, 2, i + 1) \n", 30 | " plt.title(Titles[i]) \n", 31 | " plt.imshow(images[i]) \n", 32 | "plt.show() " 33 | ] 34 | } 35 | ], 36 | "metadata": { 37 | "kernelspec": { 38 | "display_name": "Python 3", 39 | "language": "python", 40 | "name": "python3" 41 | }, 42 | "language_info": { 43 | "codemirror_mode": { 44 | "name": "ipython", 45 | "version": 3 46 | }, 47 | "file_extension": ".py", 48 | "mimetype": "text/x-python", 49 | "name": "python", 50 | "nbconvert_exporter": "python", 51 | "pygments_lexer": "ipython3", 52 | "version": "3.7.4" 53 | } 54 | }, 55 | "nbformat": 4, 56 | "nbformat_minor": 2 57 | } 58 | -------------------------------------------------------------------------------- /image segmentation.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# programming_fever" 8 | ] 9 | }, 10 | { 11 | "cell_type": "markdown", 12 | "metadata": {}, 13 | "source": [ 14 | "image segmentation using OpenCV" 15 | ] 16 | }, 17 | { 18 | "cell_type": "code", 19 | "execution_count": 24, 20 | "metadata": {}, 21 | "outputs": [], 22 | "source": [ 23 | "import cv2\n", 24 | "import numpy as np\n", 25 | "# Draw rectangle based on the input selection\n", 26 | "def draw_rectangle(event, x, y, flags, params):\n", 27 | " global x_init, y_init, drawing, top_left_pt, bottom_right_pt,img_orig\n", 28 | " # Detecting mouse button down event\n", 29 | " if event == cv2.EVENT_LBUTTONDOWN:\n", 30 | " drawing = True\n", 31 | " x_init, y_init = x, y\n", 32 | " # Detecting mouse movement\n", 33 | " elif event == cv2.EVENT_MOUSEMOVE:\n", 34 | " if drawing:\n", 35 | " top_left_pt, bottom_right_pt = (x_init,y_init), (x,y)\n", 36 | " img[y_init:y, x_init:x] = 255 - img_orig[y_init:y,\n", 37 | " x_init:x]\n", 38 | " cv2.rectangle(img, top_left_pt, bottom_right_pt,\n", 39 | " (0,255,0), 2)\n", 40 | " # Detecting mouse button up event\n", 41 | " elif event == cv2.EVENT_LBUTTONUP:\n", 42 | " drawing = False\n", 43 | " top_left_pt, bottom_right_pt = (x_init,y_init), (x,y)\n", 44 | " img[y_init:y, x_init:x] = 255 - img[y_init:y, x_init:x]\n", 45 | " cv2.rectangle(img, top_left_pt, bottom_right_pt,\n", 46 | " (0,255,0), 2)\n", 47 | " rect_final = (x_init, y_init, x-x_init, y-y_init)\n", 48 | " # Run Grabcut on the region of interest\n", 49 | " run_grabcut(img_orig, rect_final)\n", 50 | " # Grabcut algorithm\n", 51 | "def run_grabcut(img_orig, rect_final):\n", 52 | "# Initialize the mask\n", 53 | " mask = np.zeros(img_orig.shape[:2],np.uint8)\n", 54 | " # Extract the rectangle and set the region of\n", 55 | " # interest in the above mask\n", 56 | " x,y,w,h = rect_final\n", 57 | "\n", 58 | " mask[y:y+h, x:x+w] = 1\n", 59 | " # Initialize background and foreground models\n", 60 | " bgdModel = np.zeros((1,65), np.float64)\n", 61 | " fgdModel = np.zeros((1,65), np.float64)\n", 62 | " # Run Grabcut algorithm\n", 63 | " cv2.grabCut(img_orig, mask, rect_final, bgdModel, fgdModel, 5,\n", 64 | " cv2.GC_INIT_WITH_RECT)\n", 65 | " # Extract new mask\n", 66 | " mask2 = np.where((mask==2)|(mask==0),0,1).astype('uint8')\n", 67 | " # Apply the above mask to the image\n", 68 | " img_orig = img_orig*mask2[:,:,np.newaxis]\n", 69 | " # Display the image\n", 70 | " cv2.imshow('Output', img_orig)\n", 71 | "if __name__=='__main__':\n", 72 | " drawing = False\n", 73 | " top_left_pt, bottom_right_pt = (-1,-1), (-1,-1)\n", 74 | " # Read the input image\n", 75 | " img_orig = cv2.imread(\"D://OpenCV//sundarpichai.jpg\")\n", 76 | " img_orig = cv2.resize( img_orig ,(500,500))\n", 77 | " img = img_orig.copy()\n", 78 | " cv2.namedWindow('Input')\n", 79 | " cv2.setMouseCallback('Input', draw_rectangle)\n", 80 | " while True:\n", 81 | " cv2.imshow('Input', img)\n", 82 | " c = cv2.waitKey(1)\n", 83 | " if c == 27:\n", 84 | " break\n", 85 | " cv2.destroyAllWindows()" 86 | ] 87 | }, 88 | { 89 | "cell_type": "code", 90 | "execution_count": null, 91 | "metadata": {}, 92 | "outputs": [], 93 | "source": [] 94 | }, 95 | { 96 | "cell_type": "code", 97 | "execution_count": null, 98 | "metadata": {}, 99 | "outputs": [], 100 | "source": [] 101 | } 102 | ], 103 | "metadata": { 104 | "kernelspec": { 105 | "display_name": "Python 3", 106 | "language": "python", 107 | "name": "python3" 108 | }, 109 | "language_info": { 110 | "codemirror_mode": { 111 | "name": "ipython", 112 | "version": 3 113 | }, 114 | "file_extension": ".py", 115 | "mimetype": "text/x-python", 116 | "name": "python", 117 | "nbconvert_exporter": "python", 118 | "pygments_lexer": "ipython3", 119 | "version": "3.7.6" 120 | } 121 | }, 122 | "nbformat": 4, 123 | "nbformat_minor": 4 124 | } 125 | -------------------------------------------------------------------------------- /invisible cloak.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "#harry potter's invisibility cloak using OpenCV python\n", 11 | "import cv2\n", 12 | "import time\n", 13 | "import numpy as np\n", 14 | "## Preparation for writing the ouput video\n", 15 | "fourcc = cv2.VideoWriter_fourcc(*'XVID')\n", 16 | "out = cv2.VideoWriter('output.avi', fourcc, 20.0, (640, 480))\n", 17 | "##reading from the webcam\n", 18 | "cap = cv2.VideoCapture(0)\n", 19 | "## Allow the system to sleep for 3 seconds before the webcam starts\n", 20 | "time.sleep(3)\n", 21 | "count = 0\n", 22 | "background = 0\n", 23 | "## Capture the background in range of 60\n", 24 | "for i in range(60):\n", 25 | " ret, background = cap.read()\n", 26 | "background = np.flip(background, axis=1)\n", 27 | "## Read every frame from the webcam, until the camera is open\n", 28 | "while (cap.isOpened()):\n", 29 | " ret, img = cap.read()\n", 30 | " if not ret:\n", 31 | " break\n", 32 | " count += 1\n", 33 | " img = np.flip(img, axis=1)\n", 34 | " ## Convert the color space from BGR to HSV\n", 35 | " hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)\n", 36 | " ## Generat masks to detect red color\n", 37 | " ##YOU CAN CHANGE THE COLOR VALUE BELOW ACCORDING TO YOUR CLOTH COLOR\n", 38 | " lower_red = np.array([0, 120, 70])\n", 39 | " upper_red = np.array([10, 255,255])\n", 40 | " mask1 = cv2.inRange(hsv, lower_red, upper_red)\n", 41 | " lower_red = np.array([170, 120, 70])\n", 42 | " upper_red = np.array([180, 255, 255])\n", 43 | " mask2 = cv2.inRange(hsv, lower_red, upper_red)\n", 44 | " mask1 = mask1 + mask2\n", 45 | " ## Open and Dilate the mask image\n", 46 | " mask1 = cv2.morphologyEx(mask1, cv2.MORPH_OPEN, np.ones((3, 3), np.uint8))\n", 47 | " mask1 = cv2.morphologyEx(mask1, cv2.MORPH_DILATE, np.ones((3, 3), np.uint8))\n", 48 | " ## Create an inverted mask to segment out the red color from the frame\n", 49 | " mask2 = cv2.bitwise_not(mask1)\n", 50 | " ## Segment the red color part out of the frame using bitwise and with the inverted mask\n", 51 | " res1 = cv2.bitwise_and(img, img, mask=mask2)\n", 52 | " ## Create image showing static background frame pixels only for the masked region\n", 53 | " res2 = cv2.bitwise_and(background, background, mask=mask1)\n", 54 | " ## Generating the final output and writing\n", 55 | " finalOutput = cv2.addWeighted(res1, 1, res2, 1, 0)\n", 56 | " out.write(finalOutput)\n", 57 | " cv2.imshow(\"magic\", finalOutput)\n", 58 | " cv2.waitKey(1)\n", 59 | "cap.release()\n", 60 | "out.release()\n", 61 | "cv2.destroyAllWindows()\n" 62 | ] 63 | }, 64 | { 65 | "cell_type": "code", 66 | "execution_count": null, 67 | "metadata": {}, 68 | "outputs": [], 69 | "source": [] 70 | } 71 | ], 72 | "metadata": { 73 | "kernelspec": { 74 | "display_name": "Python 3", 75 | "language": "python", 76 | "name": "python3" 77 | }, 78 | "language_info": { 79 | "codemirror_mode": { 80 | "name": "ipython", 81 | "version": 3 82 | }, 83 | "file_extension": ".py", 84 | "mimetype": "text/x-python", 85 | "name": "python", 86 | "nbconvert_exporter": "python", 87 | "pygments_lexer": "ipython3", 88 | "version": "3.7.6" 89 | } 90 | }, 91 | "nbformat": 4, 92 | "nbformat_minor": 4 93 | } 94 | -------------------------------------------------------------------------------- /motion blurring effect .ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "#applying motion blur filter\n", 11 | "import cv2\n", 12 | "import numpy as np\n", 13 | "img = cv2.imread('input.jpg')\n", 14 | "cv2.imshow('Original', img)\n", 15 | "size = 15\n", 16 | "\n", 17 | "kernel_motion_blur = np.zeros((size, size))\n", 18 | "kernel_motion_blur[int((size-1)/2), :] = np.ones(size)\n", 19 | "kernel_motion_blur = kernel_motion_blur / size\n", 20 | "\n", 21 | "output = cv2.filter2D(img, -1, kernel_motion_blur)\n", 22 | "cv2.imshow('Motion Blur', output)\n", 23 | "cv2.waitKey(0)" 24 | ] 25 | } 26 | ], 27 | "metadata": { 28 | "kernelspec": { 29 | "display_name": "Python 3", 30 | "language": "python", 31 | "name": "python3" 32 | }, 33 | "language_info": { 34 | "codemirror_mode": { 35 | "name": "ipython", 36 | "version": 3 37 | }, 38 | "file_extension": ".py", 39 | "mimetype": "text/x-python", 40 | "name": "python", 41 | "nbconvert_exporter": "python", 42 | "pygments_lexer": "ipython3", 43 | "version": "3.7.4" 44 | } 45 | }, 46 | "nbformat": 4, 47 | "nbformat_minor": 2 48 | } 49 | -------------------------------------------------------------------------------- /negative flim.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#PROGRAMMING_FEVER\n", 10 | "#pravee\n", 11 | "import cv2\n", 12 | "import numpy as np\n", 13 | "def draw_rectangle(event, x, y, flags, params):\n", 14 | " global x_init, y_init, drawing, top_left_pt, bottom_right_pt\n", 15 | " if event == cv2.EVENT_LBUTTONDOWN:\n", 16 | " drawing = True\n", 17 | " x_init, y_init = x, y\n", 18 | " elif event == cv2.EVENT_MOUSEMOVE:\n", 19 | " if drawing:\n", 20 | " top_left_pt = (min(x_init, x), min(y_init, y))\n", 21 | " bottom_right_pt = (max(x_init, x), max(y_init, y))\n", 22 | " img[y_init:y, x_init:x] = 255 - img[y_init:y, x_init:x]\n", 23 | " elif event == cv2.EVENT_LBUTTONUP:\n", 24 | " drawing = False\n", 25 | " top_left_pt = (min(x_init, x), min(y_init, y))\n", 26 | " bottom_right_pt = (max(x_init, x), max(y_init, y))\n", 27 | " img[y_init:y, x_init:x] = 255 - img[y_init:y, x_init:x]\n", 28 | "if __name__=='__main__':\n", 29 | " drawing = False\n", 30 | " top_left_pt, bottom_right_pt = (-1,-1), (-1,-1)\n", 31 | " cap = cv2.VideoCapture(0)\n", 32 | " if not cap.isOpened():\n", 33 | " raise IOError(\"Cannot open webcam\")\n", 34 | " cv2.namedWindow('Webcam')\n", 35 | " cv2.setMouseCallback('Webcam', draw_rectangle)\n", 36 | " while True:\n", 37 | " ret, frame = cap.read()\n", 38 | " img = cv2.resize(frame, None, fx=0.5, fy=0.5,interpolation=cv2.INTER_AREA)\n", 39 | " (x0,y0), (x1,y1) = top_left_pt, bottom_right_pt\n", 40 | " img[y0:y1, x0:x1] = 255 - img[y0:y1, x0:x1]\n", 41 | " cv2.imshow('Webcam', img)\n", 42 | " c = cv2.waitKey(1)\n", 43 | " if c == 27:\n", 44 | " break\n", 45 | "cap.release()\n", 46 | "cv2.destroyAllWindows()" 47 | ] 48 | }, 49 | { 50 | "cell_type": "code", 51 | "execution_count": null, 52 | "metadata": {}, 53 | "outputs": [], 54 | "source": [] 55 | } 56 | ], 57 | "metadata": { 58 | "kernelspec": { 59 | "display_name": "Python 3", 60 | "language": "python", 61 | "name": "python3" 62 | }, 63 | "language_info": { 64 | "codemirror_mode": { 65 | "name": "ipython", 66 | "version": 3 67 | }, 68 | "file_extension": ".py", 69 | "mimetype": "text/x-python", 70 | "name": "python", 71 | "nbconvert_exporter": "python", 72 | "pygments_lexer": "ipython3", 73 | "version": "3.7.4" 74 | } 75 | }, 76 | "nbformat": 4, 77 | "nbformat_minor": 2 78 | } 79 | -------------------------------------------------------------------------------- /non-photorealistic rendering .ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "#non-photorealistic rendering\n", 11 | "#using cv2.edgePreservingFilter()\n", 12 | "import cv2\n", 13 | "img = cv2.imread(\"E://OpenCV//labrador.jpg\")\n", 14 | "img=cv2.resize(img,(450,500))\n", 15 | "img1 = cv2.edgePreservingFilter(img,\n", 16 | " flags=cv2.RECURS_FILTER, sigma_s=60, sigma_r=0.5)\n", 17 | "img2 = cv2.edgePreservingFilter(img,\n", 18 | " flags=cv2.NORMCONV_FILTER, sigma_s=100, sigma_r=0.4)\n", 19 | "cv2.imshow('sourceimg', img)\n", 20 | "cv2.imshow('edgepreserving1', img1)\n", 21 | "cv2.imshow('edgepreserving2', img2)\n", 22 | "cv2.waitKey() \n", 23 | "cv2.destroyAllWindows() " 24 | ] 25 | }, 26 | { 27 | "cell_type": "code", 28 | "execution_count": null, 29 | "metadata": {}, 30 | "outputs": [], 31 | "source": [ 32 | "#programming_fever\n", 33 | "#non-photorealistic rendering\n", 34 | "#using cv2.DetailEnhance()\n", 35 | "import cv2\n", 36 | "img = cv2.imread(\"E://OpenCV//cow.jpg\")\n", 37 | "img=cv2.resize(img,(500,500))\n", 38 | "dst = cv2.detailEnhance(img, sigma_s=200, sigma_r=0.1)\n", 39 | "cv2.imshow('sourceimg', img)\n", 40 | "cv2.imshow('detail enhanaced',dst)\n", 41 | "cv2.waitKey() \n", 42 | "cv2.destroyAllWindows() " 43 | ] 44 | }, 45 | { 46 | "cell_type": "code", 47 | "execution_count": null, 48 | "metadata": {}, 49 | "outputs": [], 50 | "source": [ 51 | "#programming_fever\n", 52 | "#non-photorealistic rendering\n", 53 | "#using cv2.pencilSketch()\n", 54 | "import cv2\n", 55 | "img = cv2.imread(\"E://OpenCV//gold.jpg\")\n", 56 | "img=cv2.resize(img,(450,500))\n", 57 | "img1, img2 = cv2.pencilSketch(img, \n", 58 | " sigma_s=200, sigma_r=0.1, shade_factor=0.3)\n", 59 | "cv2.imshow('sourceimg', img)\n", 60 | "cv2.imshow('graysketch', img1)\n", 61 | "cv2.imshow('colorsketch', img2)\n", 62 | "cv2.waitKey() \n", 63 | "cv2.destroyAllWindows() " 64 | ] 65 | }, 66 | { 67 | "cell_type": "code", 68 | "execution_count": null, 69 | "metadata": {}, 70 | "outputs": [], 71 | "source": [ 72 | "#programming_fever\n", 73 | "#non-photorealistic rendering\n", 74 | "#using cv2.stylization()\n", 75 | "import cv2\n", 76 | "img = cv2.imread(\"E://OpenCV//gold.jpg\")\n", 77 | "img=cv2.resize(img,(600,600))\n", 78 | "dst = cv2.stylization(img, sigma_s=200,sigma_r=0.45)\n", 79 | "gst=cv2.resize(img,(600,600))\n", 80 | "cv2.imshow('sourceimg', img)\n", 81 | "cv2.imshow('stylization', dst)\n", 82 | "cv2.waitKey() \n", 83 | "cv2.destroyAllWindows() " 84 | ] 85 | } 86 | ], 87 | "metadata": { 88 | "kernelspec": { 89 | "display_name": "Python 3", 90 | "language": "python", 91 | "name": "python3" 92 | }, 93 | "language_info": { 94 | "codemirror_mode": { 95 | "name": "ipython", 96 | "version": 3 97 | }, 98 | "file_extension": ".py", 99 | "mimetype": "text/x-python", 100 | "name": "python", 101 | "nbconvert_exporter": "python", 102 | "pygments_lexer": "ipython3", 103 | "version": "3.7.4" 104 | } 105 | }, 106 | "nbformat": 4, 107 | "nbformat_minor": 2 108 | } 109 | -------------------------------------------------------------------------------- /number plate detection.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [ 8 | { 9 | "name": "stdout", 10 | "output_type": "stream", 11 | "text": [ 12 | "Number of Contours found : 10\n", 13 | "[[[396 134]]\n", 14 | "\n", 15 | " [[270 139]]\n", 16 | "\n", 17 | " [[270 173]]\n", 18 | "\n", 19 | " [[395 167]]]\n" 20 | ] 21 | } 22 | ], 23 | "source": [ 24 | "#programming_fever\n", 25 | "#number plate detection\n", 26 | "import cv2\n", 27 | "import imutils as im\n", 28 | "\n", 29 | "input = 'E://OpenCV//car1.jpg'\n", 30 | "image = cv2.imread(input)\n", 31 | "\n", 32 | "newwidth = 500\n", 33 | "image = im.resize(image, width=newwidth)\n", 34 | "\n", 35 | "gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n", 36 | "\n", 37 | "d, sigmaColor, sigmaSpace = 11,17,17\n", 38 | "filtered_img = cv2.bilateralFilter(gray, d, sigmaColor, sigmaSpace)\n", 39 | "\n", 40 | "lower, upper = 170, 200\n", 41 | "edged = cv2.Canny(filtered_img, lower, upper)\n", 42 | "\n", 43 | "\n", 44 | "cnts,hir = cv2.findContours(edged.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)\n", 45 | "\n", 46 | "cnts=sorted(cnts, key = cv2.contourArea, reverse = True)[:10]\n", 47 | "NumberPlateCnt = None\n", 48 | "print(\"Number of Contours found : \" + str(len(cnts)))\n", 49 | "\n", 50 | "count = 0\n", 51 | "for c in cnts:\n", 52 | " peri = cv2.arcLength(c, True)\n", 53 | " epsilon = 0.01 * peri\n", 54 | " approx = cv2.approxPolyDP(c, epsilon, True)\n", 55 | " if len(approx) == 4: \n", 56 | " print(approx)\n", 57 | " NumberPlateCnt = approx \n", 58 | " break\n", 59 | "\n", 60 | "\n", 61 | "cv2.imshow(\"Input Image\", image)\n", 62 | "cv2.imshow(\"Gray scale Image\", gray)\n", 63 | "cv2.imshow(\"After Applying Bilateral Filter\", filtered_img)\n", 64 | "cv2.imshow(\"After Canny Edges\", edged)\n", 65 | "\n", 66 | "cv2.drawContours(image, [NumberPlateCnt], -1, (255,0,0), 2)\n", 67 | "cv2.imshow(\"Output\", image)\n", 68 | "\n", 69 | "cv2.waitKey(0) " 70 | ] 71 | }, 72 | { 73 | "cell_type": "code", 74 | "execution_count": null, 75 | "metadata": {}, 76 | "outputs": [], 77 | "source": [] 78 | } 79 | ], 80 | "metadata": { 81 | "kernelspec": { 82 | "display_name": "Python 3", 83 | "language": "python", 84 | "name": "python3" 85 | }, 86 | "language_info": { 87 | "codemirror_mode": { 88 | "name": "ipython", 89 | "version": 3 90 | }, 91 | "file_extension": ".py", 92 | "mimetype": "text/x-python", 93 | "name": "python", 94 | "nbconvert_exporter": "python", 95 | "pygments_lexer": "ipython3", 96 | "version": "3.7.4" 97 | } 98 | }, 99 | "nbformat": 4, 100 | "nbformat_minor": 2 101 | } 102 | -------------------------------------------------------------------------------- /object tracking using OpenCV.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "#objectTracking\n", 11 | "#in this code I tried to extract blue color object\n", 12 | "import cv2 \n", 13 | "import numpy as np \n", 14 | "cap = cv2.VideoCapture(0) \n", 15 | "while(1): \n", 16 | " _,frame = cap.read() \n", 17 | " hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) \n", 18 | " lower_blue = np.array([110, 50, 50]) \n", 19 | " upper_blue = np.array([130, 255, 255]) \n", 20 | " mask = cv2.inRange(hsv, lower_blue, upper_blue) \n", 21 | " result = cv2.bitwise_and(frame, frame, mask = mask) \n", 22 | " cv2.imshow('frame', frame) \n", 23 | " cv2.imshow('mask', mask) \n", 24 | " cv2.imshow('result', result) \n", 25 | " k= cv2.waitKey(1)& 0XFF\n", 26 | " if k==27:\n", 27 | " break\n", 28 | "cv2.destroyAllWindows() \n", 29 | "cap.release() " 30 | ] 31 | }, 32 | { 33 | "cell_type": "code", 34 | "execution_count": null, 35 | "metadata": {}, 36 | "outputs": [], 37 | "source": [] 38 | } 39 | ], 40 | "metadata": { 41 | "kernelspec": { 42 | "display_name": "Python 3", 43 | "language": "python", 44 | "name": "python3" 45 | }, 46 | "language_info": { 47 | "codemirror_mode": { 48 | "name": "ipython", 49 | "version": 3 50 | }, 51 | "file_extension": ".py", 52 | "mimetype": "text/x-python", 53 | "name": "python", 54 | "nbconvert_exporter": "python", 55 | "pygments_lexer": "ipython3", 56 | "version": "3.7.4" 57 | } 58 | }, 59 | "nbformat": 4, 60 | "nbformat_minor": 2 61 | } 62 | -------------------------------------------------------------------------------- /pencil drawing effect.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 6, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "#pencil drawing effect using opencv\n", 11 | "import numpy as np\n", 12 | "import cv2\n", 13 | "\n", 14 | "img =\"E://OpenCV//elonobama.jpg\"\n", 15 | "img_obj = cv2.imread(img)\n", 16 | "\n", 17 | "\n", 18 | "\n", 19 | "dim = (width,height)\n", 20 | "resized = cv2.resize(img_obj,dim,interpolation = cv2.INTER_AREA) \n", 21 | "\n", 22 | "kernel_sharpening = np.array([[-1,-1,-1], \n", 23 | " [-1, 9,-1],\n", 24 | " [-1,-1,-1]])\n", 25 | "sharpened = cv2.filter2D(resized,-1,kernel_sharpening) \n", 26 | "\n", 27 | "\n", 28 | "gray = cv2.cvtColor(sharpened , cv2.COLOR_BGR2GRAY) \n", 29 | "object_detection = cv2.cvtColor(sharpened, cv2.COLOR_BGR2HSV ) \n", 30 | "\n", 31 | "\n", 32 | "inv = 255-gray\n", 33 | "gauss = cv2.GaussianBlur(inv,ksize=(15,15),sigmaX=0,sigmaY=0) \n", 34 | "\n", 35 | "pencil = cv2.divide(gray,255-gauss,scale=256)\n", 36 | "\n", 37 | "cv2.imshow('resized',resized)\n", 38 | "cv2.imshow('sharp',sharpened)\n", 39 | "cv2.imshow(\"gray\", gray)\n", 40 | "cv2.imshow('pencil drawing',pencil)\n", 41 | "cv2.waitKey(0)\n", 42 | "cv2.destroyAllWindows()" 43 | ] 44 | }, 45 | { 46 | "cell_type": "code", 47 | "execution_count": null, 48 | "metadata": {}, 49 | "outputs": [], 50 | "source": [] 51 | } 52 | ], 53 | "metadata": { 54 | "kernelspec": { 55 | "display_name": "Python 3", 56 | "language": "python", 57 | "name": "python3" 58 | }, 59 | "language_info": { 60 | "codemirror_mode": { 61 | "name": "ipython", 62 | "version": 3 63 | }, 64 | "file_extension": ".py", 65 | "mimetype": "text/x-python", 66 | "name": "python", 67 | "nbconvert_exporter": "python", 68 | "pygments_lexer": "ipython3", 69 | "version": "3.7.4" 70 | } 71 | }, 72 | "nbformat": 4, 73 | "nbformat_minor": 2 74 | } 75 | -------------------------------------------------------------------------------- /reversing video using opencv.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "#play video in reverse mode using OpenCV python\n", 11 | "import cv2 \n", 12 | "cap = cv2.VideoCapture(\"E://OpenCV//video 2 img//BMW M4.mp4\") \n", 13 | "check , vid = cap.read()\n", 14 | "counter = 0\n", 15 | "check = True \n", 16 | "frame_list = [] \n", 17 | "while(check == True): \n", 18 | " cv2.imwrite(\"frame%d.jpg\" %counter , vid) \n", 19 | " check , vid = cap.read() \n", 20 | " frame_list.append(vid) \n", 21 | " counter += 1\n", 22 | "frame_list.pop() \n", 23 | "frame_list.reverse() \n", 24 | "for frame in frame_list: \n", 25 | " cv2.imshow(\"Frame\" , frame) \n", 26 | " if cv2.waitKey(25) and 0xFF == ord(\"q\"): \n", 27 | " break\n", 28 | "cap.release() \n", 29 | "cv2.destroyAllWindows()" 30 | ] 31 | } 32 | ], 33 | "metadata": { 34 | "kernelspec": { 35 | "display_name": "Python 3", 36 | "language": "python", 37 | "name": "python3" 38 | }, 39 | "language_info": { 40 | "codemirror_mode": { 41 | "name": "ipython", 42 | "version": 3 43 | }, 44 | "file_extension": ".py", 45 | "mimetype": "text/x-python", 46 | "name": "python", 47 | "nbconvert_exporter": "python", 48 | "pygments_lexer": "ipython3", 49 | "version": "3.7.4" 50 | } 51 | }, 52 | "nbformat": 4, 53 | "nbformat_minor": 4 54 | } 55 | -------------------------------------------------------------------------------- /sharpening of images using opencv.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [ 8 | { 9 | "data": { 10 | "text/plain": [ 11 | "
" 12 | ] 13 | }, 14 | "metadata": {}, 15 | "output_type": "display_data" 16 | } 17 | ], 18 | "source": [ 19 | "#programming_fever\n", 20 | "#sharepenning of images using OpenCV\n", 21 | "import cv2\n", 22 | "import numpy as np\n", 23 | "import matplotlib.pyplot as plt\n", 24 | "img = cv2.imread('E://OpenCV//bmw.png')\n", 25 | "img=cv2.resize(img,(300,300))\n", 26 | "cv2.imshow('Original', img)\n", 27 | "\n", 28 | "kernel_sharpen_1 = np.array([[-1,-1,-1], [-1,9,-1], [-1,-1,-1]])\n", 29 | "kernel_sharpen_2 = np.array([[1,1,1], [1,-7,1], [1,1,1]])\n", 30 | "kernel_sharpen_3 = np.array([[-1,-1,-1,-1,-1],\n", 31 | " [-1,3,3,3,-1],\n", 32 | " [-1,3,8,3,-1],\n", 33 | " [-1,3,3,3,-1],\n", 34 | " [-1,-1,-1,-1,-1]]) / 25.0\n", 35 | "\n", 36 | "output_1 = cv2.filter2D(img, -1, kernel_sharpen_1)\n", 37 | "output_2 = cv2.filter2D(img, -1, kernel_sharpen_2)\n", 38 | "output_3 = cv2.filter2D(img, -1, kernel_sharpen_3)\n", 39 | "\n", 40 | "cv2.imshow('Sharpening', output_1)\n", 41 | "cv2.imshow('Excessive Sharpening', output_2)\n", 42 | "cv2.imshow('Edge Enhancement', output_3)\n", 43 | "cv2.waitKey(0)\n", 44 | "cv2.destroyAllWindows()" 45 | ] 46 | }, 47 | { 48 | "cell_type": "code", 49 | "execution_count": null, 50 | "metadata": {}, 51 | "outputs": [], 52 | "source": [] 53 | } 54 | ], 55 | "metadata": { 56 | "kernelspec": { 57 | "display_name": "Python 3", 58 | "language": "python", 59 | "name": "python3" 60 | }, 61 | "language_info": { 62 | "codemirror_mode": { 63 | "name": "ipython", 64 | "version": 3 65 | }, 66 | "file_extension": ".py", 67 | "mimetype": "text/x-python", 68 | "name": "python", 69 | "nbconvert_exporter": "python", 70 | "pygments_lexer": "ipython3", 71 | "version": "3.7.4" 72 | } 73 | }, 74 | "nbformat": 4, 75 | "nbformat_minor": 2 76 | } 77 | -------------------------------------------------------------------------------- /thresholding techniques.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "#programming_fever\n", 10 | "import cv2 \n", 11 | "import numpy as np \n", 12 | "\n", 13 | "img = cv2.imread('E://OpenCV//bentley.png',0) \n", 14 | "cv2.imshow('original image',img) \n", 15 | "\n", 16 | "ret, thresh1 = cv2.threshold(img, 120, 255, cv2.THRESH_BINARY) \n", 17 | "ret, thresh2 = cv2.threshold(img, 120, 255, cv2.THRESH_BINARY_INV) \n", 18 | "ret, thresh3 = cv2.threshold(img, 120, 255, cv2.THRESH_TRUNC) \n", 19 | "ret, thresh4 = cv2.threshold(img, 120, 255, cv2.THRESH_TOZERO) \n", 20 | "ret, thresh5 = cv2.threshold(img, 120, 255, cv2.THRESH_TOZERO_INV) \n", 21 | " \n", 22 | "cv2.imshow('Binary Threshold', thresh1) \n", 23 | "cv2.imshow('Binary Threshold Inverted', thresh2) \n", 24 | "cv2.imshow('Truncated Threshold', thresh3) \n", 25 | "cv2.imshow('Set to zero', thresh4) \n", 26 | "cv2.imshow('Set to zero Inverted', thresh5) \n", 27 | " \n", 28 | "if cv2.waitKey(0) & 0xff == 27: \n", 29 | " cv2.destroyAllWindows() " 30 | ] 31 | } 32 | ], 33 | "metadata": { 34 | "kernelspec": { 35 | "display_name": "Python 3", 36 | "language": "python", 37 | "name": "python3" 38 | }, 39 | "language_info": { 40 | "codemirror_mode": { 41 | "name": "ipython", 42 | "version": 3 43 | }, 44 | "file_extension": ".py", 45 | "mimetype": "text/x-python", 46 | "name": "python", 47 | "nbconvert_exporter": "python", 48 | "pygments_lexer": "ipython3", 49 | "version": "3.7.4" 50 | } 51 | }, 52 | "nbformat": 4, 53 | "nbformat_minor": 2 54 | } 55 | --------------------------------------------------------------------------------