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      "body": "Your contribution cannot be approved because it does not follow the [Utopian Rules](https://utopian.io/rules).\n\nExplanation:\nYou've explained (some of) the code you were using incorrectly, and as a whole you only discuss 4 trivial code snippets using 1 OpenCV method for each snippet. And combined those examples don't lead to anything.\n\nTe code in your first resize (which you call \"zoom\") example, contains the following lines:\n```\nimg = cv.imread('test.jpg',1)\nsizex, sizey = img.shape[0]*1, img.shape[0]*1\nimg_new =cv.resize(img, (sizex, sizey))\n```\nNot only doesn't the `*1` operation do anything, in effect you are passing the same value (`img.shape[0]`) twice (once to both the `sizex` and `sizey` arguments of the `resize()` method), which in effect does **not** \"zoom\" but \"square\" the image (same width as height). But you probably didn't even notice / understand that because your \"explanation\" of this code is:\n\n```\nTo know the dimensions or the physical size of the image and the number of channels in it you can use the shape, this code img.shape img.shape[0]1, img.shape[0]1 width and height will multiply 1.\n```\n\nThe number of channels in it? Multiply by 1?\n\n(...)\n\nYou can contact us on [Discord](https://discord.gg/uTyJkNm).\n**[[utopian-moderator]](https://utopian.io/moderators)**",
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      "body": "\n#### What Will I Learn?\n\n- You will learn Python\n- You will learn OpenCV\n- You will learn PYCharm\n- You will learn Digital Imaging\n\n#### Requirements\n\n- PYCharm\n- OpenCV Package\n- NumPY Package\n\n#### Difficulty\n\n- Intermediate\n\n#### Tutorial Contents\n<center>![intro.png](https://cdn-images-1.medium.com/max/568/1*Y1S4hciQTfrB3xJuk2remA.png)</center>\n\nHello Everyone, I want to tell you about how to make digital imaging with python using OpenCV Package. But first, you must have PYCharm or NetBeans to run Digital Imaging Program. \n\nOkay, here I'm using PYCharm, follow my instructions.\n\n1 . The first program we make **Zoom** program, this is tutorial how to make zoom with Python using OpenCV and NumPY packages.\n\n- Create new Python file on your PYCharm with name resize-zoom.\n- Copy an image to folder project.\n- Write the source code below.\n``` \nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nsizex, sizey = img.shape[0]*1, img.shape[0]*1\nimg_new =cv.resize(img, (sizex, sizey))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Resize', img_new)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n- Run it, and see the output.\n![zoom.gif](https://steemit-production-imageproxy-web.s3.amazonaws.com/U5dqy4rQPsXubvYBZdoBU1sVzTEqmp1)\n\n**Explanation Code:**\n\n``import numpy as np``\n\n\n``import cv2 as cv``\n\nTo called OpenCV and NumPY package on this program.\n\n`` img = cv.imread('test.jpg',1)``\n\nThe img variable saves the result of the image file invocation performed by the function cv.imread\n\n``sizex, sizey = img.shape[0]*1, img.shape[0]*1``\n\n``img_new =cv.resize(img, (sizex, sizey))``\n\nTo know the dimensions or the physical size of the image and the number of channels in it you can use the shape, this code ``img.shape img.shape[0]1, img.shape[0]1`` width and height will multiply 1. And then, **resize()** function for change size image.\n\n``cv.imshow('Old Image', img)``\nTo show image file default, you can use cv.imshow('Title window', variable image file)\n\n``cv.imshow('Image After Resize', img_new)`` this code to show image file after zoomed, because at there you call variable which image has zoomed.\n\n2 . The Second program about how to blur an image with python using OpenCV and NumPY Packages.\nOn this program, we will use the **Averaging** technique.\n\n- Create new Python file on your PYCharm with name averaging.\n- Copy an image to folder project.\n- Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nblur = cv.blur(img, (10,10))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Blur', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n\n- Run it, and see the output.\n![blur.gif](https://steemitimages.com/0x0/https://im5.ezgif.com/tmp/ezgif-5-ee3d95cc01.gif)\n\n**Explanation Code:**\n\n``blur = cv.blur(img, (10,10))``\nThis code has two arguments are **img** to called a variable where image file place and  (10,10) where the intent of 2 argument that is to regulate how high rate of bleeding to be obtained. The high value will result in the higher blur effect.\n\n3 . This third program if you want to clear the noise image, can use technique **Median Blur**\n\n- Create new Python file on your PYCharm with name median-blur.\n- Copy an image to folder project. ***Attention! use noise-effect images for this technique.***\n-  Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('noise.jpg',1)\nblur = cv.medianBlur(img,5)\ncv.imshow('Old Image', img)\ncv.imshow('Image After Gaussian Blur', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n- Run it, and see output.\n![median.gif](https://steemitimages.com/0x0/https://im2.ezgif.com/tmp/ezgif-2-a8fc425466.gif)\n\n**Explanation Code:**\n``blur = cv.medianBlur(img,5)`` Just use the two arguments src as img variable where the image file is stored, and its value is 5 to set the strength of the resulting blur.\n\n4 . The fourth program uses the Edge Detection technique which only detects the line of objects in each image\n\n- Create new Python file on your PYCharm with name edge-detection.\n- Copy an image to folder project.\n- Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nblur = cv.Canny(img,50,60)\ncv.imshow('Old Image', img)\ncv.imshow('Image After Edge Detection', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n- Run it, and see output.\n![edge.gif](https://steemitimages.com/0x0/https://im2.ezgif.com/tmp/ezgif-2-147f96ca88.gif)\n\n**Explanation Code:**\n\n``blur = cv.Canny(img,50,60)``\n\nValue 50 as minVal.\n\nValue 60 as maxVal.\nminVal and maxVal which means as the value that governs the intensity of the gradient on the object.\nIf the value is changed to be smaller, then the line will be much more detailed.\n\n#### Curriculum\n\n- [How To install and Open Image with OpenCV Package](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv)\n\n    \n\n<br /><hr/><em>Posted on <a href=\"https://utopian.io/utopian-io/@farahulfa/learn-python-digital-imaging-with-opencv-and-numpy-packages\">Utopian.io -  Rewarding Open Source Contributors</a></em><hr/>",
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      "body": "Your contribution cannot be approved because it does not follow the [Utopian Rules](https://utopian.io/rules).\n\nHi, this is the reason your contribution was rejected\n\nThe tutorial is too trivial to be accepted and has nothing to do with the title of your tutorial. You only install numpy, pycharm and opencv created a file and saved it  - this is much too little information and simply too trivial to be a valuable contribution.\n\n\nYou can contact us on [Discord](https://discord.gg/uTyJkNm).\n**[[utopian-moderator]](https://utopian.io/moderators)**",
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      "body": "\n#### What Will I Learn?\n\n- You will learn Python\n- You will learn OpenCV\n- You will learn Pycharm\n\n#### Requirements\n\n- Pycharm\n- Package Numpy\n- Package OpenCV\n\n#### Difficulty\n\n- Basic\n\n#### Tutorial Contents\nHello All of member Utopian, now I wanna make a tutorial how to make \"Application Face Detection and Digital Imaging with Python,\" but first you must know, what is numpy and read my [previous tutorials](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy) to understand in this tutorial.\n\n##### Explanation OpenCV\n\nOpenCV is the main module used to perform processing on the creation of \"Application Face Detection and Digital Imaging with Python.\" OpenCV can perform many tasks, from reading image files, performing color editings, to detecting faces efficiently.\n\n##### Add Numpy Package on PYCharm [linux].\n\n**1 . Open your Terminal. Write this command *sudo pip install opencv-python***\n\n![1.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965220/fidbnon9tblf91aoqtps.png)\n\n**2 . Open your PYCharm. Click File > Settings > Project: facedetector > Project Interpreter > click +.**\n\n![2.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965738/fm22fj6iqv9ogdr5ifhz.png)\n\n**3 . search opencv-python > click install package.**\n\n![3.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965831/osdiaquxyav8w45ng7h6.png)\n\n**4 . Test your OpenCV package. Click right on project facedetector > new > Python file > Set Name file with tes-opencv > write this code.**\n```\nimport cv2\nprint (cv2.__version__)\n```\n\n**5 . Run it. if success, congratulation your OpenCV package already installed.**\n\n![4.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521966077/brxt4j0e8nxo6j0tqfqy.png)\n\n##### Add Numpy Package on PYCharm [Windows].\n\n1. open this [link](https://opencv.org/opencv-3.3.html)\n2. Select ***sourceforge*** on line ***Windows self-extracting archive*** and download it.\n3. Search the file you downloaded and extract the opencv file.\n4. Open folder ***opencv\\build\\python\\2.7\\x86*** and then copy file ***cv2***.\n5. Open folder ***C:\\Python27\\DLLs*** and paste file ***cv2***.\n6. Open folder ***C:\\Python27\\Lib\\site-packages*** and paste file ***cv2***.\n7. Open your PYCharm and restart it.\n8. Test your OpenCV package. Click right on project name > new > Python file > Set Name file with tes-opencv > write this code.\n```\nimport cv2\nprint (cv2.__version__)\n```\n9 . Run it. if success, congritulation your OpenCV package allready installed.\n\n##### Open image file with python, OpenCV and NumPY packages on PYCharm\n\n**1 . copy an image file to project facedetector folder.**\n![5.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521967203/kgdavhzakp52ecoodm7i.png)\n\n**2 . Create New python file, set name with load-image.**\n**3 . Write this code.**\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\ncv.imshow('image',img)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n**4 . Run it, and see that result.**\n![6.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521967585/tk0grzbiqgtoerhu7atp.png)\n\n##### Explain Source Code.\n**This code to call numpy and opencv packages.**\n``` \nimport numpy as np\nimport cv2 as cv\n```\n\n**This code to make variable img and use opencv to read test.jpg image file and  1 to read  image as full color, if  0 to read image as grayscale, if -1 will be opened as is.**\n```\nimg = cv.imread('test.jpg',1)\n```\n\n**This code to show image on variable img.**\n```\ncv.imshow('image',img)\n```\n\n**This code to close the window after you click any button. 0 intends to close the window within 0 milliseconds.**\n```\ncv.waitKey(0)\n\n```\n\n**This code to close all open windows.**\n```\ncv.destroyAllWindows()\n```\n\n##### Save image file with python, OpenCV and NumPY packages on PYCharm\n\n**1 . Create New fpython file one project facedetector, and set name *save-image***\n**2 . Write this code.**\n``` \nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',0)\ncv.imshow('image',img)\ncv.waitKey(0)\ncv.imwrite('test2.jpg',img)\ncv.destroyAllWindows()\n```\n **3 .  Run it, and see result.**\n\n![result.gif](https://im.ezgif.com/tmp/ezgif-1-c6e4a3fb94.gif)\n\n##### Explain Source Code.\n\n**This code to make variable img and use opencv to read test.jpg image file and  0 to read image as grayscale, if 1 to read  image as full color, if  -1 will be opened as is.**\n```\nimg = cv.imread('test.jpg',0)\n```\n\n**This code to save a new image file with name test2.jpg after you click any button**.\n```\ncv.imwrite('test2.jpg',img)\n```\n\nOkay all this tutorial to continue with another tutorial.\n\n#### Curriculum \n\n- [Install And learn About NumPY](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy)\n\n\n<br /><hr/><em>Posted on <a href=\"https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv\">Utopian.io -  Rewarding Open Source Contributors</a></em><hr/>",
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      "body": "\n#### What Will I Learn?\n\n- You will learn Python\n- You will learn OpenCV\n- You will learn PYCharm\n- You will learn Digital Imaging\n\n#### Requirements\n\n- PYCharm\n- OpenCV Package\n- NumPY Package\n\n#### Difficulty\n\n- Intermediate\n\n#### Tutorial Contents\n<center>![intro.png](https://cdn-images-1.medium.com/max/568/1*Y1S4hciQTfrB3xJuk2remA.png)</center>\n\nHello Everyone, I want to tell you about how to make digital imaging with python using OpenCV Package. But first, you must have PYCharm or NetBeans to run Digital Imaging Program. \n\nOkay, here I'm using PYCharm, follow my instructions.\n\n1 . The first program we make **Zoom** program, this is tutorial how to make zoom with Python using OpenCV and NumPY packages.\n\n- Create new Python file on your PYCharm with name resize-zoom.\n- Copy an image to folder project.\n- Write the source code below.\n``` \nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nsizex, sizey = img.shape[0]*1, img.shape[0]*1\nimg_new =cv.resize(img, (sizex, sizey))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Resize', img_new)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n- Run it, and see the output.\n![zoom.gif](https://steemit-production-imageproxy-web.s3.amazonaws.com/U5dqy4rQPsXubvYBZdoBU1sVzTEqmp1)\n\n**Explanation Code:**\n\n``import numpy as np``\n\n\n``import cv2 as cv``\n\nTo called OpenCV and NumPY package on this program.\n\n`` img = cv.imread('test.jpg',1)``\n\nThe img variable saves the result of the image file invocation performed by the function cv.imread\n\n``sizex, sizey = img.shape[0]*1, img.shape[0]*1``\n\n``img_new =cv.resize(img, (sizex, sizey))``\n\nTo know the dimensions or the physical size of the image and the number of channels in it you can use the shape, this code ``img.shape img.shape[0]1, img.shape[0]1`` width and height will multiply 1. And then, **resize()** function for change size image.\n\n``cv.imshow('Old Image', img)``\nTo show image file default, you can use cv.imshow('Title window', variable image file)\n\n``cv.imshow('Image After Resize', img_new)`` this code to show image file after zoomed, because at there you call variable which image has zoomed.\n\n2 . The Second program about how to blur an image with python using OpenCV and NumPY Packages.\nOn this program, we will use the **Averaging** technique.\n\n- Create new Python file on your PYCharm with name averaging.\n- Copy an image to folder project.\n- Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nblur = cv.blur(img, (10,10))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Blur', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n\n- Run it, and see the output.\n![blur.gif](https://steemitimages.com/0x0/https://im5.ezgif.com/tmp/ezgif-5-ee3d95cc01.gif)\n\n**Explanation Code:**\n\n``blur = cv.blur(img, (10,10))``\nThis code has two arguments are **img** to called a variable where image file place and  (10,10) where the intent of 2 argument that is to regulate how high rate of bleeding to be obtained. The high value will result in the higher blur effect.\n\n3 . This third program if you want to clear the noise image, can use technique **Median Blur**\n\n- Create new Python file on your PYCharm with name median-blur.\n- Copy an image to folder project. ***Attention! use noise-effect images for this technique.***\n-  Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('noise.jpg',1)\nblur = cv.medianBlur(img,5)\ncv.imshow('Old Image', img)\ncv.imshow('Image After Gaussian Blur', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n- Run it, and see output.\n![median.gif](https://steemitimages.com/0x0/https://im2.ezgif.com/tmp/ezgif-2-a8fc425466.gif)\n\n**Explanation Code:**\n``blur = cv.medianBlur(img,5)`` Just use the two arguments src as img variable where the image file is stored, and its value is 5 to set the strength of the resulting blur.\n\n4 . The fourth program uses the Edge Detection technique which only detects the line of objects in each image\n\n- Create new Python file on your PYCharm with name edge-detection.\n- Copy an image to folder project.\n- Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nblur = cv.Canny(img,50,60)\ncv.imshow('Old Image', img)\ncv.imshow('Image After Edge Detection', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n- Run it, and see output.\n![edge.gif](https://steemitimages.com/0x0/https://im2.ezgif.com/tmp/ezgif-2-147f96ca88.gif)\n\n**Explanation Code:**\n\n``blur = cv.Canny(img,50,60)``\n\nValue 50 as minVal.\n\nValue 60 as maxVal.\nminVal and maxVal which means as the value that governs the intensity of the gradient on the object.\nIf the value is changed to be smaller, then the line will be much more detailed.\n\n#### Curriculum\n\n- [How To install and Open Image with OpenCV Package](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv)\n\n    \n\n<br /><hr/><em>Posted on <a href=\"https://utopian.io/utopian-io/@farahulfa/learn-python-digital-imaging-with-opencv-and-numpy-packages\">Utopian.io -  Rewarding Open Source Contributors</a></em><hr/>",
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      "body": "if you said that, means the contribution of existing tutorial categories in utopian can be deleted because there is already google",
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      "body": "Your contribution cannot be approved because it does not follow the [Utopian Rules](https://utopian.io/rules).\n\n- The content of this tutorial is well documented in the OpenCV documentation. You can check it <a href=\"https://docs.opencv.org/3.0-beta/modules/imgproc/doc/filtering.html\">here</a> and <a href=\"https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_imgproc/py_canny/py_canny.html\">here</a>\n\nYou can contact us on [Discord](https://discord.gg/uTyJkNm).\n**[[utopian-moderator]](https://utopian.io/moderators)**",
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      "body": "\n#### What Will I Learn?\n\n- You will learn Python\n- You will learn OpenCV\n- You will learn Digital Imaging\n\n#### Requirements\n\n- PYCharm\n- OpenCV Package\n- NumPY Package\n\n#### Difficulty\n\n- Intermediate\n\n#### Tutorial Contents\n\n##### What Is Blur Effect?\nThe blur effect is an effect that results in a blurred image, out of focus, blur, and things like that.\nBut with OpenCV, we can recognize the code structure to make the image blur, and there are several techniques to blur an image that we will discuss in this part include:\n- Averaging\n- Gaussian Blur\n- Median Blur\n- Edge Detection\n\n##### Averaging\n\nThe first technique is called averaging because the process of blurring the image is done by taking the average of the entire image and changing it to a new value.\nTo get a blur effect with this technique, we can use the function **blur()**\n\n###### Example Program:\n\n1. Create new Python file on your PYCharm with name averaging.\n\n2. Copy an image to folder project.\n\n3. Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nblur = cv.blur(img, (10,10))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Blur', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n4 . Run it, and see output. \n![1.gif](https://im5.ezgif.com/tmp/ezgif-5-ee3d95cc01.gif)\n\n###### Explanation Code:\n```\nblur = cv.blur(img, (10,10))\n```\nIn the above code, two arguments are (10,10) where the intent of 2 argument that is to regulate how high rate of bleeding to be obtained. The high value will result in the higher blur effect.\n\n##### Gaussian Blur\nAnother blur effect that can be used is Gaussian Blur which in OpenCV can be present through the **GaussianBlur ()** function. The most basic Gaussian Blur structure is as follows:\n```\ncv.GaussianBlur (src (sigmaX, sigmaY), border)\n```\n- src = image to be blurred.\n- sigmaX = sets the number of standard deviations based on the gaussian blur filter on the X-axis.\n- sigmaY = sets the number of standard deviations based on the Gaussian blur filter on the Y-axis.\n- border = set the resulting border due to using this filter. The default is in condition 0.\n\n###### Example Program:\n\n1. Create new Python file on your PYCharm with name gaussian-blur.\n\n2. Copy an image to folder project.\n\n3. Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nblur = cv.GaussianBlur(img, (5,5),0)\ncv.imshow('Old Image', img)\ncv.imshow('Image After Gaussian Blur', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n4 . Run it, and see output. \n![2.gif](https://im2.ezgif.com/tmp/ezgif-2-03446334ad.gif)\n###### Explanation Code:\n```\nblur = cv.GaussianBlur(img, (5,5),0)\n```\nthe same explanation as above just this function add border function which set default 0\n\n##### Median Blur\nMedian Blur can be used to minimize noise effects on the image. This blur technique can be used using the **medianBlur ()** function.\n\n###### Example Program:\n\n1. Create new Python file on your PYCharm with name median-blur.\n\n2. Copy an image to folder project. ***Attention! use noise-effect images for this technique.***\n\n3. Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('noise.jpg',1)\nblur = cv.medianBlur(img,5)\ncv.imshow('Old Image', img)\ncv.imshow('Image After Gaussian Blur', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n4 . Run it, and see output.\n![3.gif](https://im2.ezgif.com/tmp/ezgif-2-a8fc425466.gif)\n\n###### Explanation Code:\n```\nblur = cv.medianBlur(img,5)\n```\nJust use the two arguments src as img and its value is 5 to set the strength of the resulting blur.\n\n##### Edge Detection\n\nEdge Detection is an algorithm that serves to detect the object line. One of the functions that can be used for Edge Detection is **Canny ()**.\nThe structure for this Edge Detection function itself as follows:\n```\ncv.Canny (src, minVal, maxVal)\n```\n- src = image file that will be used for Edge Detection function.\n- minVal = the value that governs the intensity of the gradient on the object.\n- maxVal = value that regulates the intensity of the gradient on the object.\n\nIf you enter a low number in minVal or maxVal, the edge that will be in shape is much more detailed in than with the high inserted value.\n###### Example Program:\n\n1. Create new Python file on your PYCharm with name edge-detection.\n\n2. Copy an image to folder project. ***Attention! use noise-effect images for this technique.***\n\n3. Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nblur = cv.Canny(img,50,60)\ncv.imshow('Old Image', img)\ncv.imshow('Image After Edge Detection', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n4 . Run it, and see output.\n![4.gif](https://im2.ezgif.com/tmp/ezgif-2-147f96ca88.gif)\n\n###### Explanation Code:\n```\nblur = cv.Canny(img,50,60)\n```\nValue 50 as minVal.<br>\nValue 60 as maxVal.<br>\nIf the value in fox becomes smaller, then the edge will be much more detail.\n\nOkay until here first learning about Python Digital Imaging with OpenCV [Blur Effect - Part 2]. For the third part will discuss how to draw with python language using OpenCV package.\n#### Curriculum\n\n- [Learn Python Digital Imaging with OpenCV [Resize - Part 1]](https://utopian.io/utopian-io/@farahulfa/learn-python-digital-imaging-with-opencv-resize-part-1)\n- [How To install and Open Image with OpenCV Package](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv)\n\n<br /><hr/><em>Posted on <a href=\"https://utopian.io/utopian-io/@farahulfa/learn-python-digital-imaging-with-opencv-blur-effect-part-2\">Utopian.io -  Rewarding Open Source Contributors</a></em><hr/>",
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      "body": "Your contribution cannot be approved because it does not follow the [Utopian Rules](https://utopian.io/rules).\n\n- The content of this tutorial is well documented in the OpenCV documentation. You can check it <a href=\"https://docs.opencv.org/3.0-beta/modules/imgproc/doc/geometric_transformations.html?highlight=resize#cv2.resize\">here</a> and <a href=\"https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_imgproc/py_geometric_transformations/py_geometric_transformations.html#geometric-transformations\">here</a>\n\nYou can contact us on [Discord](https://discord.gg/uTyJkNm).\n**[[utopian-moderator]](https://utopian.io/moderators)**",
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      "body": "\n#### What Will I Learn?\n\n- You will learn Python\n- You will learn OpenCV\n- You will learn PYCharm\n\n#### Requirements\n\n- PYCharm\n- OpenCV Package\n- NumPY Package\n\n#### Difficulty\n\n- Intermediate\n\n#### Tutorial Contents\n\n##### What is Digital Imaging?\nFrom [wikipedia](https://en.wikipedia.org/wiki/Digital_imaging), Digital imaging or digital image acquisition is the creation of photographic images, such as of a physical scene or of the interior structure of an object. The term is often assumed to imply or include the processing, compression, storage, printing, and display of such images.\n\n##### What is OpenCV?\nFrom [wikipedia](https://en.wikipedia.org/wiki/OpenCV), OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real-time computer vision.[1] Originally developed by Intel, it was later supported by Willow Garage then Itseez (which was later acquired by Intel[2]). The library is cross-platform and free for use under the open-source BSD license.\n\n##### What is Resize?\nResize is the process of resizing the size of an image, whether enlarged or scaled to help that purpose, OpenCV provides resize functionality. This function has several arguments as follows:\n1. **src1** : the first image file to be resized\n2. **width**  : setting the width of the new image.\n3. **height**  : setting the height of the new image.\n4. **interpolation**  : the type of interpolation used. There are two options that can be used, namely INTER_AREA commonly used to shrink the image or INTER_CUBIC & INTER_LINEAR to enlarge the image. If not set, then by default INTER_LINEAR will be used.\n\n\n##### Resize Example Program.\n###### Zoom\n1 . Create new Python file on your PYCharm with name resize-zoom.\n\n2 . Copy an image to folder project. \n\n3 . Write the source code below.\n``` \nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nsizex, sizey = img.shape[0]*1, img.shape[0]*1\nimg_new =cv.resize(img, (sizex, sizey))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Resize', img_new)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n4 . Run it, and see output.\n![zoom.gif](https://im2.ezgif.com/tmp/ezgif-2-1ce7030209.gif)\n\n**Explaination Code:**\n```\nsizex, sizey = img.shape[0]*1, img.shape[0]*1\nimg_new =cv.resize(img, (sizex, sizey))\n```\nTo know the dimensions or the physical size of the image and the number of channels in it you can use the **shape**, this code img.shape img.shape[0]*1, img.shape[0]*1 width and height will multiply 1.  And then, **resize()** function for change size image.\n\n\n###### Shrink\n1 . Create new Python file on your PYCharm with name resize-shrink.\n\n2 . Copy an image to folder project. \n\n3 . Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nsizex, sizey = img.shape[0]/2, img.shape[0]/2\nimg_new =cv.resize(img, (sizex, sizey))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Shrink', img_new)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n\n4 . Run it, and see output.\n![shrink.gif](https://im2.ezgif.com/tmp/ezgif-2-def40b721c.gif)\n\n**Explanation Code:**\n```\nimg = cv.imread('test.jpg',1)\n```\nThis code to call image file.\n\n```\nsizex, sizey = img.shape[0]/2, img.shape[0]/2\nimg_new =cv.resize(img, (sizex, sizey))\n```\nTo know the dimensions or the physical size of the image and the number of channels in it you can use the **shape**, this code img.shape img.shape[0]/2, img.shape[0]/2 width and height will divided 2.  And then, **resize()** function for change size image.\n\n##### Transformation Image\nOpenCV has several functions to help image transformations such as Rotate, shift (translation), create perspectives, etc. These functions are **warpAffine** and **warpPerspective**. The difference lies in the use of matrix when transforming where warpAffile uses 2x3 matrix, while warpPerspective uses 3x3 matrix.\n\n##### Tranformation Example Program.\n###### Rotate and Flip\n1 . Create new Python file on your PYCharm with name rotate-flip.\n\n2 . Copy an image to folder project. \n\n3 . Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nwidth, height = img.shape[0], img.shape[1]\nrotate = cv.getRotationMatrix2D((width/2, height/2), 90,1)\nimg_flip = cv.flip(img,0)\nimg_rotate = cv.warpAffine(img, rotate, (width, height))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Rotate', img_rotate)\ncv.imshow('Image After Flip', img_flip)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n\n4 . Run it, and see the output.\n![rotate-flip.gif](https://im2.ezgif.com/tmp/ezgif-2-a93f40f8ce.gif)\n\n**Explanation Code:**\n\n```\nrotate = cv.getRotationMatrix2D((width/2, height/2), 90,1)\n```\nTo rotate image you can using this function **getRotationMatrix2D **, argument width / 2, height / 2 means we want the rotation axis image is in the middle of the image, while 90 indicates the desired rotation degree.\n\n```\nimg_rotate = cv.warpAffine(img, rotate, (width, height))\n```\nthe image rotation process is performed using the **warpAffine** function according to the value received by the **rotate** variable. Then the rotated image (in img_rotate variable) is displayed using **imshow**\n\n```\nimg_flip = cv.flip(img,0)\n```\nOf the code above 0 is the flip value.\n1 = if you want to flip horizontally.\n0 = if you want to flip vertically.\n-1 = if you want to flip horizontally and vertically.\n\n###### Translation\n\n1 . Create new Python file on your PYCharm with name translation.\n\n2 . Copy an image to folder project. \n\n3 . Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nwidth, height = img.shape[0], img.shape[1]\ntrans = np.float32([[1,0,100],[0,1,50]])\nimg_trans = cv.warpAffine(img, trans,(height,width))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Translation', img_trans)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n\n4 . Run it, and see the output.\n![Translation.gif](https://im2.ezgif.com/tmp/ezgif-2-8c732720e0.gif)\n\n**Explanation Code:**\n\n```\ntrans = np.float32([[1,0,100],[0,1,50]])\nimg_trans = cv.warpAffine(img, trans,(height,width))\n```\nTo get the new x and y positions on the image so that it seems to shift, we can take advantage of float32 function from NumPY. Basically, this function is a simplification of the matrix to get a new position that will be used to shift the image. The position you want to get is the axis x = 100 and y = 50.\nThe value will then be used for the warpAffine function to perform translation (shift), while (height, width) determines the size of the window obtained from the image property itself.\n\nwill continue [Resize- Part 2]\n\n#### Curriculum\n\n- [How To install and Open Image with OpenCV Package](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv)\n\n\n<br /><hr/><em>Posted on <a href=\"https://utopian.io/utopian-io/@farahulfa/learn-python-digital-imaging-with-opencv-resize-part-1\">Utopian.io -  Rewarding Open Source Contributors</a></em><hr/>",
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      "body": "This is cool - looks like a better option for me than Imagemagick :)",
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      "body": "\n#### What Will I Learn?\n\n- You will learn Python\n- You will learn OpenCV\n- You will learn Digital Imaging\n\n#### Requirements\n\n- PYCharm\n- OpenCV Package\n- NumPY Package\n\n#### Difficulty\n\n- Intermediate\n\n#### Tutorial Contents\n\n##### What Is Blur Effect?\nThe blur effect is an effect that results in a blurred image, out of focus, blur, and things like that.\nBut with OpenCV, we can recognize the code structure to make the image blur, and there are several techniques to blur an image that we will discuss in this part include:\n- Averaging\n- Gaussian Blur\n- Median Blur\n- Edge Detection\n\n##### Averaging\n\nThe first technique is called averaging because the process of blurring the image is done by taking the average of the entire image and changing it to a new value.\nTo get a blur effect with this technique, we can use the function **blur()**\n\n###### Example Program:\n\n1. Create new Python file on your PYCharm with name averaging.\n\n2. Copy an image to folder project.\n\n3. Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nblur = cv.blur(img, (10,10))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Blur', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n4 . Run it, and see output. \n![1.gif](https://im5.ezgif.com/tmp/ezgif-5-ee3d95cc01.gif)\n\n###### Explanation Code:\n```\nblur = cv.blur(img, (10,10))\n```\nIn the above code, two arguments are (10,10) where the intent of 2 argument that is to regulate how high rate of bleeding to be obtained. The high value will result in the higher blur effect.\n\n##### Gaussian Blur\nAnother blur effect that can be used is Gaussian Blur which in OpenCV can be present through the **GaussianBlur ()** function. The most basic Gaussian Blur structure is as follows:\n```\ncv.GaussianBlur (src (sigmaX, sigmaY), border)\n```\n- src = image to be blurred.\n- sigmaX = sets the number of standard deviations based on the gaussian blur filter on the X-axis.\n- sigmaY = sets the number of standard deviations based on the gaussian blur filter on the Y-axis.\n- border = set the resulting border due to using this filter. The default is in condition 0.\n\n###### Example Program:\n\n1. Create new Python file on your PYCharm with name gaussian-blur.\n\n2. Copy an image to folder project.\n\n3. Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nblur = cv.GaussianBlur(img, (5,5),0)\ncv.imshow('Old Image', img)\ncv.imshow('Image After Gaussian Blur', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n4 . Run it, and see output. \n![2.gif](https://im2.ezgif.com/tmp/ezgif-2-03446334ad.gif)\n###### Explanation Code:\n```\nblur = cv.GaussianBlur(img, (5,5),0)\n```\nthe same explanation as above just this function add border function which set default 0\n\n##### Median Blur\nMedian Blur can be used to minimize noise effects on the image. This blur technique can be used using the **medianBlur ()** function.\n\n###### Example Program:\n\n1. Create new Python file on your PYCharm with name median-blur.\n\n2. Copy an image to folder project. ***Attention! use noise-effect images for this technique.***\n\n3. Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('noise.jpg',1)\nblur = cv.medianBlur(img,5)\ncv.imshow('Old Image', img)\ncv.imshow('Image After Gaussian Blur', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n4 . Run it, and see output.\n![3.gif](https://im2.ezgif.com/tmp/ezgif-2-a8fc425466.gif)\n\n###### Explanation Code:\n```\nblur = cv.medianBlur(img,5)\n```\nJust use the two arguments src as img and its value is 5 to set the strength of the resulting blur.\n\n##### Edge Detection\n\nEdge Detection is an algorithm that serves to detect the object line. One of the functions that can be used for Edge Detection is **Canny ()**.\nThe structure for this Edge Detection function itself as follows:\n```\ncv.Canny (src, minVal, maxVal)\n```\nsrc = image file that will be used for Edge Detection function\nminVal = the value that governs the intensity of the gradient on the object\nmaxVal = value that regulates the intensity of the gradient on the object\n\nIf you enter a low number in minVal or maxVal, the edge that will be in shape is much more detailed in than with the high inserted value.\n###### Example Program:\n\n1. Create new Python file on your PYCharm with name edge-detection.\n\n2. Copy an image to folder project. ***Attention! use noise-effect images for this technique.***\n\n3. Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nblur = cv.Canny(img,50,60)\ncv.imshow('Old Image', img)\ncv.imshow('Image After Edge Detection', blur)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n4 . Run it, and see output.\n![4.gif](https://im2.ezgif.com/tmp/ezgif-2-147f96ca88.gif)\n\n###### Explanation Code:\n```\nblur = cv.Canny(img,50,60)\n```\nvalue 50 as minVal\nvalue 60 as maxVal\nif the value in fox becomes smaller then edge will be much more detail.\n\nOkay until here first learning about Python Digital Imaging with OpenCV [Blur Effect - Part 2]. For the third part will discuss how to draw with python language using OpenCV package.\n#### Curriculum\n\n- [Learn Python Digital Imaging with OpenCV [Resize - Part 1]](https://utopian.io/utopian-io/@farahulfa/learn-python-digital-imaging-with-opencv-resize-part-1)\n- [How To install and Open Image with OpenCV Package](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv)\n\n<br /><hr/><em>Posted on <a href=\"https://utopian.io/utopian-io/@farahulfa/learn-python-digital-imaging-with-opencv-blur-effect-part-2\">Utopian.io -  Rewarding Open Source Contributors</a></em><hr/>",
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      "body": "\n#### What Will I Learn?\n\n- You will learn Python\n- You will learn OpenCV\n- You will learn PYCharm\n\n#### Requirements\n\n- PYCharm\n- OpenCV Package\n- NumPY Package\n\n#### Difficulty\n\n- Intermediate\n\n#### Tutorial Contents\n\n##### What is Digital Imaging?\nFrom [wikipedia](https://en.wikipedia.org/wiki/Digital_imaging), Digital imaging or digital image acquisition is the creation of photographic images, such as of a physical scene or of the interior structure of an object. The term is often assumed to imply or include the processing, compression, storage, printing, and display of such images.\n\n##### What is OpenCV?\nFrom [wikipedia](https://en.wikipedia.org/wiki/OpenCV), OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real-time computer vision.[1] Originally developed by Intel, it was later supported by Willow Garage then Itseez (which was later acquired by Intel[2]). The library is cross-platform and free for use under the open-source BSD license.\n\n##### What is Resize?\nResize is the process of resizing the size of an image, whether enlarged or scaled to help that purpose, OpenCV provides resize functionality. This function has several arguments as follows:\n1. **src1** : the first image file to be resized\n2. **width**  : setting the width of the new image.\n3. **height**  : setting the height of the new image.\n4. **interpolation**  : the type of interpolation used. There are two options that can be used, namely INTER_AREA commonly used to shrink the image or INTER_CUBIC & INTER_LINEAR to enlarge the image. If not set, then by default INTER_LINEAR will be used.\n\n\n##### Resize Example Program.\n###### Zoom\n1 . Create new Python file on your PYCharm with name resize-zoom.\n\n2 . Copy an image to folder project. \n\n3 . Write the source code below.\n``` \nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nsizex, sizey = img.shape[0]*1, img.shape[0]*1\nimg_new =cv.resize(img, (sizex, sizey))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Resize', img_new)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n4 . Run it, and see output.\n![zoom.gif](https://im2.ezgif.com/tmp/ezgif-2-1ce7030209.gif)\n\n**Explaination Code:**\n```\nsizex, sizey = img.shape[0]*1, img.shape[0]*1\nimg_new =cv.resize(img, (sizex, sizey))\n```\nTo know the dimensions or the physical size of the image and the number of channels in it you can use the **shape**, this code img.shape img.shape[0]*1, img.shape[0]*1 width and height will multiply 1.  And then, **resize()** function for change size image.\n\n\n###### Shrink\n1 . Create new Python file on your PYCharm with name resize-shrink.\n\n2 . Copy an image to folder project. \n\n3 . Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nsizex, sizey = img.shape[0]/2, img.shape[0]/2\nimg_new =cv.resize(img, (sizex, sizey))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Shrink', img_new)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n\n4 . Run it, and see output.\n![shrink.gif](https://im2.ezgif.com/tmp/ezgif-2-def40b721c.gif)\n\n**Explaination Code:**\n```\nimg = cv.imread('test.jpg',1)\n```\nThis code to call image file.\n\n```\nsizex, sizey = img.shape[0]/2, img.shape[0]/2\nimg_new =cv.resize(img, (sizex, sizey))\n```\nTo know the dimensions or the physical size of the image and the number of channels in it you can use the **shape**, this code img.shape img.shape[0]/2, img.shape[0]/2 width and height will divided 2.  And then, **resize()** function for change size image.\n\n##### Tranformation Image\nOpenCV has several functions to help image transformations such as Rotate, shift (translation), create perspectives, and etc. These functions are **warpAffine** and **warpPerspective**. The difference lies in the use of matrix when transforming where warpAffile uses 2x3 matrix, while warpPerspective uses 3x3 matrix.\n\n##### Tranformation Example Program.\n###### Rotate and Flip\n1 . Create new Python file on your PYCharm with name rotate-flip.\n\n2 . Copy an image to folder project. \n\n3 . Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nwidth, height = img.shape[0], img.shape[1]\nrotate = cv.getRotationMatrix2D((width/2, height/2), 90,1)\nimg_flip = cv.flip(img,0)\nimg_rotate = cv.warpAffine(img, rotate, (width, height))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Rotate', img_rotate)\ncv.imshow('Image After Flip', img_flip)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n\n4 . Run it, and see output.\n![rotate-flip.gif](https://im2.ezgif.com/tmp/ezgif-2-a93f40f8ce.gif)\n\n**Explaination Code:**\n\n```\nrotate = cv.getRotationMatrix2D((width/2, height/2), 90,1)\n```\nTo rotate image you can using this function **getRotationMatrix2D **, argument width / 2, height / 2 means we want the rotation axis image is in the middle of the image, while 90 indicates the desired rotation degree.\n\n```\nimg_rotate = cv.warpAffine(img, rotate, (width, height))\n```\nthe image rotation process is performed using the **warpAffine** function according to the value received by the **rotate** variable. Then the rotated image (in img_rotate variable) is displayed using **imshow**\n\n```\nimg_flip = cv.flip(img,0)\n```\nof the code above 0 is the flip value.\n1 = if you want to flip horizontally.\n0 = if you want to flip vertically.\n-1 = if you want to flip horizontally and vertically.\n\n###### Translation\n\n1 . Create new Python file on your PYCharm with name translation.\n\n2 . Copy an image to folder project. \n\n3 . Write the source code below.\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\nwidth, height = img.shape[0], img.shape[1]\ntrans = np.float32([[1,0,100],[0,1,50]])\nimg_trans = cv.warpAffine(img, trans,(height,width))\ncv.imshow('Old Image', img)\ncv.imshow('Image After Translation', img_trans)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n\n4 . Run it, and see output.\n![Translation.gif](https://im2.ezgif.com/tmp/ezgif-2-8c732720e0.gif)\n\n**Explaination Code:**\n\n```\ntrans = np.float32([[1,0,100],[0,1,50]])\nimg_trans = cv.warpAffine(img, trans,(height,width))\n```\nTo get the new x and y positions on the image so that it seems to shift, we can take advantage of float32 function from NumPY. Basically, this function is a simplification of the matrix to get a new position that will be used to shift the image. The position you want to get is the axis x = 100 and y = 50.\nThe value will then be used for the warpAffine function to perform translation (shift), while (height, width) determines the size of the window obtained from the image property itself.\n\nwill continue on [Resize- Part 2]\n\n#### Curriculum\n\n- [How To install and Open Image with OpenCV Package](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv)\n\n\n<br /><hr/><em>Posted on <a href=\"https://utopian.io/utopian-io/@farahulfa/learn-python-digital-imaging-with-opencv-resize-part-1\">Utopian.io -  Rewarding Open Source Contributors</a></em><hr/>",
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      "body": "\n#### What Will I Learn?\nWrite here briefly the details of what the user is going to learn in a bullet list.\n\n- You will learn Python\n- You will learn Numpy\n- You will learn Pychram\n\n#### Requirements\n\n- Package Numpy\n- Pychram\n\n#### Difficulty\n\n- Basic\n\n#### Tutorial Contents\nHello All of member Utopian, now I wanna make tutorial how to make \"Application Face Detection and Digital Imaging with Python\" but first you must know, what is numpy? \n###### Explanation Numpy\nNumpy is the module needed for OpenCV to work properly. Numpy itself is an abbreviation of Numerical python, is a library package that provides various routines to process multidimensional arrays.\n\n##### Add  Numpy Package on PYChram\n**1 . Open Your PYChram.**\n\n**2 . Add New Project With Name facedetector.**\n\n**3 . Add Numpy Library. Follow me to get install numpy library on your Pychram.**\n\n![1.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962814/nk4iwnxvqpwcd0wgj5lu.png)\n\n![2.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962838/ytld4rl89ckpsijm59er.png)\n\n![3.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962925/rnj1pbpkquopaomivnd7.png)\n\n![4.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963046/i9759czzvtnoi8y2iqdd.png)\n\n##### Project First Numpy.\n\n**1 .  Add new python file. click right on project name > new > Python file.**\n![5.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963305/hcvdu9bzjrrithepnpnf.png)\n\n**2 .  Set with name tes-numpy.**\n\n![6.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963700/sy54yi3ce3arobn5trkm.png)\n\n**3 . Write this source code.**\n``` \nimport numpy as num\nnumber = num.array([1,2,3])\nprint (number)\n```\n**4 . Run that program.  right click > Run 'tes-numpy,**\nand you got that program result.\n![7.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963990/qfaxque8xgtzzrjteyhk.png)\n\n##### Explain Source Code.\nThis code to call numpy package to program.\n```\nimport numpy as num\n```\nThis code to make variable number with Array value ([1,2,3]).\n```\nnumber = num.array([1,2,3])\n```\nThis code to print value on variable number.\n```\nprint (number)\n```\nOkay this tutorial to be continue  to part 2 how to install OpenCV on PYChram and run it.\n\n<br /><hr/><em>Posted on <a href=\"https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy\">Utopian.io -  Rewarding Open Source Contributors</a></em><hr/>",
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      "body": "thanks dude\ni was in a hurry",
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      "author": "farahulfa",
      "body": "@@ -88,18 +88,18 @@\n arn Pych\n-r\n a\n+r\n m%0A%0A#### \n@@ -118,18 +118,18 @@\n %0A%0A- Pych\n-r\n a\n+r\n m%0A- Pack\n@@ -869,18 +869,18 @@\n  on PYCh\n-r\n a\n+r\n m %5Blinux\n@@ -1082,18 +1082,18 @@\n our PYCh\n-r\n a\n+r\n m. Click\n@@ -1818,18 +1818,18 @@\n  on PYCh\n-r\n a\n+r\n m %5BWindo\n@@ -2281,18 +2281,18 @@\n our PYCh\n-r\n a\n+r\n m and re\n@@ -2612,34 +2612,34 @@\n packages on PYCh\n-r\n a\n+r\n m%0A%0A**1 . copy an\n@@ -3826,18 +3826,18 @@\n  on PYCh\n-r\n a\n+r\n m%0A%0A**1 .\n",
      "json_metadata": "{\"community\":\"utopian\",\"app\":\"utopian/1.0.0\",\"format\":\"markdown\",\"repository\":{\"id\":5108051,\"name\":\"opencv\",\"full_name\":\"opencv/opencv\",\"html_url\":\"https://github.com/opencv/opencv\",\"fork\":false,\"owner\":{\"login\":\"opencv\"}},\"pullRequests\":[],\"platform\":\"github\",\"type\":\"tutorials\",\"tags\":[\"utopian-io\",\"python\",\"opencv\",\"steemit\"],\"users\":[\"farahulfa\"],\"links\":[\"https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965220/fidbnon9tblf91aoqtps.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965738/fm22fj6iqv9ogdr5ifhz.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965831/osdiaquxyav8w45ng7h6.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521966077/brxt4j0e8nxo6j0tqfqy.png\",\"https://opencv.org/opencv-3.3.html\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521967203/kgdavhzakp52ecoodm7i.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521967585/tk0grzbiqgtoerhu7atp.png\",\"https://im.ezgif.com/tmp/ezgif-1-c6e4a3fb94.gif\"],\"image\":[\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965220/fidbnon9tblf91aoqtps.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965738/fm22fj6iqv9ogdr5ifhz.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965831/osdiaquxyav8w45ng7h6.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521966077/brxt4j0e8nxo6j0tqfqy.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521967203/kgdavhzakp52ecoodm7i.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521967585/tk0grzbiqgtoerhu7atp.png\",\"https://im.ezgif.com/tmp/ezgif-1-c6e4a3fb94.gif\"]}",
      "parent_author": "",
      "parent_permlink": "utopian-io",
      "permlink": "application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv",
      "title": "Open and Save Image file with Python Language, Numpy and OpenCV Packages on PYCharm"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2018-03-25T09:48:30",
  "trx_id": "ac7b59d52c61d5b1d6918689397773029ee49781",
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{
  "block": 20980563,
  "op": [
    "comment",
    {
      "author": "farahulfa",
      "body": "@@ -60,21 +60,22 @@\n l learn \n-Numpy\n+OpenCV\n %0A- You w\n@@ -4616,14 +4616,25 @@\n  to \n-part 3\n+another tutorials\n .%0A%0A#\n@@ -4651,99 +4651,44 @@\n ulum\n+ \n %0A%0A- %5B\n-Application Face Detection and Digital Imaging with Python on PYChram %5Bpart1%5D %5B\n+Install And learn About \n NumPY%5D\n-%5D\n (htt\n",
      "json_metadata": "{\"community\":\"utopian\",\"app\":\"utopian/1.0.0\",\"format\":\"markdown\",\"repository\":{\"id\":5108051,\"name\":\"opencv\",\"full_name\":\"opencv/opencv\",\"html_url\":\"https://github.com/opencv/opencv\",\"fork\":false,\"owner\":{\"login\":\"opencv\"}},\"pullRequests\":[],\"platform\":\"github\",\"type\":\"tutorials\",\"tags\":[\"utopian-io\",\"python\",\"opencv\",\"steemit\"],\"users\":[\"farahulfa\"],\"links\":[\"https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965220/fidbnon9tblf91aoqtps.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965738/fm22fj6iqv9ogdr5ifhz.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965831/osdiaquxyav8w45ng7h6.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521966077/brxt4j0e8nxo6j0tqfqy.png\",\"https://opencv.org/opencv-3.3.html\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521967203/kgdavhzakp52ecoodm7i.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521967585/tk0grzbiqgtoerhu7atp.png\",\"https://im.ezgif.com/tmp/ezgif-1-c6e4a3fb94.gif\"],\"image\":[\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965220/fidbnon9tblf91aoqtps.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965738/fm22fj6iqv9ogdr5ifhz.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965831/osdiaquxyav8w45ng7h6.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521966077/brxt4j0e8nxo6j0tqfqy.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521967203/kgdavhzakp52ecoodm7i.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521967585/tk0grzbiqgtoerhu7atp.png\",\"https://im.ezgif.com/tmp/ezgif-1-c6e4a3fb94.gif\"]}",
      "parent_author": "",
      "parent_permlink": "utopian-io",
      "permlink": "application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv",
      "title": "Open and Save Image file with Python Language, Numpy and OpenCV Packages on PYChram"
    }
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{
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  "op": [
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    {
      "author": "nafestw",
      "body": "Its PyCharm, not PYChram.",
      "json_metadata": "{\"tags\":[\"utopian-io\"],\"app\":\"steemit/0.1\"}",
      "parent_author": "farahulfa",
      "parent_permlink": "application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv",
      "permlink": "re-farahulfa-application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv-20180325t094514911z",
      "title": ""
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2018-03-25T09:45:15",
  "trx_id": "dc736d23d308c41b28d6c94c55f69d6080a069c9",
  "trx_in_block": 22,
  "virtual_op": 0
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{
  "block": 20980260,
  "op": [
    "comment",
    {
      "author": "farahulfa",
      "body": "@@ -2189,420 +2189,59 @@\n  to \n-%5B\n part 2\n-%5D(https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv) how to install OpenCV on PYChram and run it.%0A%0A#### Curriculum%0A%0A- %5BApplication Face Detection and Digital Imaging with Python on PYChram %5Bpart2%5D %5BOpenCV%5D%5D(https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv)\n+ how to install OpenCV on PYChram and run it.\n %0A%0A%3Cb\n",
      "json_metadata": "{\"community\":\"utopian\",\"app\":\"utopian/1.0.0\",\"format\":\"markdown\",\"repository\":{\"id\":908607,\"name\":\"numpy\",\"full_name\":\"numpy/numpy\",\"html_url\":\"https://github.com/numpy/numpy\",\"fork\":false,\"owner\":{\"login\":\"numpy\"}},\"pullRequests\":[],\"platform\":\"github\",\"type\":\"tutorials\",\"tags\":[\"utopian-io\",\"python\",\"numpy\",\"steemit\"],\"users\":[\"farahulfa\"],\"links\":[\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962814/nk4iwnxvqpwcd0wgj5lu.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962838/ytld4rl89ckpsijm59er.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962925/rnj1pbpkquopaomivnd7.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963046/i9759czzvtnoi8y2iqdd.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963305/hcvdu9bzjrrithepnpnf.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963700/sy54yi3ce3arobn5trkm.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963990/qfaxque8xgtzzrjteyhk.png\"],\"image\":[\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962814/nk4iwnxvqpwcd0wgj5lu.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962838/ytld4rl89ckpsijm59er.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962925/rnj1pbpkquopaomivnd7.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963046/i9759czzvtnoi8y2iqdd.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963305/hcvdu9bzjrrithepnpnf.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963700/sy54yi3ce3arobn5trkm.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963990/qfaxque8xgtzzrjteyhk.png\"]}",
      "parent_author": "",
      "parent_permlink": "utopian-io",
      "permlink": "application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy",
      "title": "Application Face Detection and Digital Imaging with Python on PYChram [part1] [NumPY]"
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{
  "block": 20980248,
  "op": [
    "comment",
    {
      "author": "farahulfa",
      "body": "\n#### What Will I Learn?\nWrite here briefly the details of what the user is going to learn in a bullet list.\n\n- You will learn Python\n- You will learn Numpy\n- You will learn Pychram\n\n#### Requirements\n\n- Package Numpy\n- Pychram\n\n#### Difficulty\n\n- Basic\n\n#### Tutorial Contents\nHello All of member Utopian, now I wanna make tutorial how to make \"Application Face Detection and Digital Imaging with Python\" but first you must know, what is numpy? \n###### Explanation Numpy\nNumpy is the module needed for OpenCV to work properly. Numpy itself is an abbreviation of Numerical python, is a library package that provides various routines to process multidimensional arrays.\n\n##### Add  Numpy Package on PYChram\n**1 . Open Your PYChram.**\n\n**2 . Add New Project With Name facedetector.**\n\n**3 . Add Numpy Library. Follow me to get install numpy library on your Pychram.**\n\n![1.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962814/nk4iwnxvqpwcd0wgj5lu.png)\n\n![2.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962838/ytld4rl89ckpsijm59er.png)\n\n![3.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962925/rnj1pbpkquopaomivnd7.png)\n\n![4.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963046/i9759czzvtnoi8y2iqdd.png)\n\n##### Project First Numpy.\n\n**1 .  Add new python file. click right on project name > new > Python file.**\n![5.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963305/hcvdu9bzjrrithepnpnf.png)\n\n**2 .  Set with name tes-numpy.**\n\n![6.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963700/sy54yi3ce3arobn5trkm.png)\n\n**3 . Write this source code.**\n``` \nimport numpy as num\nnumber = num.array([1,2,3])\nprint (number)\n```\n**4 . Run that program.  right click > Run 'tes-numpy,**\nand you got that program result.\n![7.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963990/qfaxque8xgtzzrjteyhk.png)\n\n##### Explain Source Code.\nThis code to call numpy package to program.\n```\nimport numpy as num\n```\nThis code to make variable number with Array value ([1,2,3]).\n```\nnumber = num.array([1,2,3])\n```\nThis code to print value on variable number.\n```\nprint (number)\n```\nOkay this tutorial to be continue  to [part 2](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv) how to install OpenCV on PYChram and run it.\n\n#### Curriculum\n\n- [Application Face Detection and Digital Imaging with Python on PYChram [part2] [OpenCV]](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv)\n\n<br /><hr/><em>Posted on <a href=\"https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy\">Utopian.io -  Rewarding Open Source Contributors</a></em><hr/>",
      "json_metadata": "{\"community\":\"utopian\",\"app\":\"utopian/1.0.0\",\"format\":\"markdown\",\"repository\":{\"id\":908607,\"name\":\"numpy\",\"full_name\":\"numpy/numpy\",\"html_url\":\"https://github.com/numpy/numpy\",\"fork\":false,\"owner\":{\"login\":\"numpy\"}},\"pullRequests\":[],\"platform\":\"github\",\"type\":\"tutorials\",\"tags\":[\"utopian-io\",\"utopian-io\",\"python\",\"numpy\",\"steemit\"],\"users\":[\"farahulfa\"],\"links\":[\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962814/nk4iwnxvqpwcd0wgj5lu.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962838/ytld4rl89ckpsijm59er.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962925/rnj1pbpkquopaomivnd7.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963046/i9759czzvtnoi8y2iqdd.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963305/hcvdu9bzjrrithepnpnf.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963700/sy54yi3ce3arobn5trkm.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963990/qfaxque8xgtzzrjteyhk.png\",\"https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv\"],\"image\":[\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962814/nk4iwnxvqpwcd0wgj5lu.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962838/ytld4rl89ckpsijm59er.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962925/rnj1pbpkquopaomivnd7.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963046/i9759czzvtnoi8y2iqdd.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963305/hcvdu9bzjrrithepnpnf.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963700/sy54yi3ce3arobn5trkm.png\",\"https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963990/qfaxque8xgtzzrjteyhk.png\"],\"moderator\":{\"account\":\"amosbastian\",\"time\":\"2018-03-25T09:22:13.855Z\",\"flagged\":true,\"reviewed\":false,\"pending\":false},\"questions\":[],\"score\":null}",
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      "parent_permlink": "utopian-io",
      "permlink": "application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy",
      "title": "Application Face Detection and Digital Imaging with Python on PYChram [part1] [NumPY]"
    }
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{
  "block": 20980230,
  "op": [
    "comment",
    {
      "author": "amosbastian",
      "body": "Your contribution cannot be approved because it does not follow the [Utopian Rules](https://utopian.io/rules).\n\nHi, this is the reason your contribution was rejected\n\n* The tutorial is too trivial to be accepted and has nothing to do with the title of your tutorial. You only install `numpy`, create an array and print it - this is much too little information and simply too trivial to be a valuable contribution.\n\nI recommend you focus on the non-trivial aspects of face detection using `numpy`, of which there are more than enough.\n\nYou can contact us on [Discord](https://discord.gg/uTyJkNm).\n**[[utopian-moderator]](https://utopian.io/moderators)**",
      "json_metadata": "{\"tags\":[\"utopian-io\"],\"community\":\"utopian\",\"app\":\"utopian/1.0.0\"}",
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      "permlink": "re-farahulfa-application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy-20180325t092918447z",
      "title": ""
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  "timestamp": "2018-03-25T09:29:18",
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{
  "block": 20980179,
  "op": [
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    {
      "author": "farahulfa",
      "body": "\n#### What Will I Learn?\nWrite here briefly the details of what the user is going to learn in a bullet list.\n\n- You will learn Python\n- You will learn Numpy\n- You will learn Pychram\n\n#### Requirements\n\n- Package Numpy\n- Pychram\n\n#### Difficulty\n\n- Basic\n\n#### Tutorial Contents\nHello All of member Utopian, now I wanna make tutorial how to make \"Application Face Detection and Digital Imaging with Python\" but first you must know, what is numpy? \n###### Explanation Numpy\nNumpy is the module needed for OpenCV to work properly. Numpy itself is an abbreviation of Numerical python, is a library package that provides various routines to process multidimensional arrays.\n\n##### Add  Numpy Package on PYChram\n**1 . Open Your PYChram.**\n\n**2 . Add New Project With Name facedetector.**\n\n**3 . Add Numpy Library. Follow me to get install numpy library on your Pychram.**\n\n![1.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962814/nk4iwnxvqpwcd0wgj5lu.png)\n\n![2.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962838/ytld4rl89ckpsijm59er.png)\n\n![3.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962925/rnj1pbpkquopaomivnd7.png)\n\n![4.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963046/i9759czzvtnoi8y2iqdd.png)\n\n##### Project First Numpy.\n\n**1 .  Add new python file. click right on project name > new > Python file.**\n![5.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963305/hcvdu9bzjrrithepnpnf.png)\n\n**2 .  Set with name tes-numpy.**\n\n![6.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963700/sy54yi3ce3arobn5trkm.png)\n\n**3 . Write this source code.**\n``` \nimport numpy as num\nnumber = num.array([1,2,3])\nprint (number)\n```\n**4 . Run that program.  right click > Run 'tes-numpy,**\nand you got that program result.\n![7.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963990/qfaxque8xgtzzrjteyhk.png)\n\n##### Explain Source Code.\nThis code to call numpy package to program.\n```\nimport numpy as num\n```\nThis code to make variable number with Array value ([1,2,3]).\n```\nnumber = num.array([1,2,3])\n```\nThis code to print value on variable number.\n```\nprint (number)\n```\nOkay this tutorial to be continue  to [part 2](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv) how to install OpenCV on PYChram and run it.\n\n#### Curriculum\n\n- [Application Face Detection and Digital Imaging with Python on PYChram [part2] [OpenCV]](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv)\n\n<br /><hr/><em>Posted on <a href=\"https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy\">Utopian.io -  Rewarding Open Source Contributors</a></em><hr/>",
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      "body": "\n#### What Will I Learn?\n\n- You will learn Python\n- You will learn Numpy\n- You will learn Pychram\n\n#### Requirements\n\n- Pychram\n- Package Numpy\n- Package OpenCV\n\n#### Difficulty\n\n- Basic\n\n#### Tutorial Contents\nHello All of member Utopian, now I wanna make tutorial how to make \"Application Face Detection and Digital Imaging with Python\" but first you must know, what is numpy and read my [previous tutorials](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy) to understand in this tutorial.\n\n##### Explanation OpenCV\n\nOpenCV is the main module used to perform processing on the creation of \"Application Face Detection and Digital Imaging with Python\". OpenCV can perform many tasks, from reading image files, performing color ediings, to detecting faces effectively.\n\n##### Add Numpy Package on PYChram [linux].\n\n**1 . Open your Terminal. write this command *sudo pip install opencv-python***\n\n![1.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965220/fidbnon9tblf91aoqtps.png)\n\n**2 . Open your PYChram. Click File > Settings > Project: facedetector > Project Interpreter > click +.**\n\n![2.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965738/fm22fj6iqv9ogdr5ifhz.png)\n\n**3 . search opencv-python > click install package.**\n\n![3.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521965831/osdiaquxyav8w45ng7h6.png)\n\n**4 . Test your OpenCV package. Click right on project facedetector > new > Python file > Set Name file with tes-opencv > write this code.**\n```\nimport cv2\nprint (cv2.__version__)\n```\n\n**5 . Run it. if success, congritulation your OpenCV package allready installed.**\n\n![4.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521966077/brxt4j0e8nxo6j0tqfqy.png)\n\n##### Add Numpy Package on PYChram [Windows].\n\n1. open this [link](https://opencv.org/opencv-3.3.html)\n2. Select ***sourceforge*** on line ***Windows self-extracting archive*** and download it.\n3. Search the file you downloaded and extract the opencv file.\n4. Open folder ***opencv\\build\\python\\2.7\\x86*** and then copy file ***cv2***.\n5. Open folder ***C:\\Python27\\DLLs*** and paste file ***cv2***.\n6. Open folder ***C:\\Python27\\Lib\\site-packages*** and paste file ***cv2***.\n7. Open your PYChram and restart it.\n8. Test your OpenCV package. Click right on project name > new > Python file > Set Name file with tes-opencv > write this code.\n```\nimport cv2\nprint (cv2.__version__)\n```\n9 . Run it. if success, congritulation your OpenCV package allready installed.\n\n##### Open image file with python, OpenCV and NumPY packages on PYChram\n\n**1 . copy an image file to project facedetector folder.**\n![5.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521967203/kgdavhzakp52ecoodm7i.png)\n\n**2 . Create New python file, set name with load-image.**\n**3 . Write this code.**\n```\nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',1)\ncv.imshow('image',img)\ncv.waitKey(0)\ncv.destroyAllWindows()\n```\n**4 . Run it, and see that result.**\n![6.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521967585/tk0grzbiqgtoerhu7atp.png)\n\n##### Explain Source Code.\n**This code to call numpy and opencv packages.**\n``` \nimport numpy as np\nimport cv2 as cv\n```\n\n**This code to make variable img and use opencv to read test.jpg image file and  1 to read  image as full color, if  0 to read image as grayscale, if -1 will be opened as is.**\n```\nimg = cv.imread('test.jpg',1)\n```\n\n**This code to show image on variable img.**\n```\ncv.imshow('image',img)\n```\n\n**This code to close window after you click any button. 0 intends to close the window within 0 milliseconds.**\n```\ncv.waitKey(0)\n\n```\n\n**This code to close all open windows.**\n```\ncv.destroyAllWindows()\n```\n\n##### Save image file with python, OpenCV and NumPY packages on PYChram\n\n**1 . Create New fpython file one project facedetector, and set name *save-image***\n**2 . Write this code.**\n``` \nimport numpy as np\nimport cv2 as cv\n\nimg = cv.imread('test.jpg',0)\ncv.imshow('image',img)\ncv.waitKey(0)\ncv.imwrite('test2.jpg',img)\ncv.destroyAllWindows()\n```\n **3 .  Run it, and see result.**\n\n![result.gif](https://im.ezgif.com/tmp/ezgif-1-c6e4a3fb94.gif)\n\n##### Explain Source Code.\n\n**This code to make variable img and use opencv to read test.jpg image file and  0 to read image as grayscale, if 1 to read  image as full color, if  -1 will be opened as is.**\n```\nimg = cv.imread('test.jpg',0)\n```\n\n**This code to save a new image file with name test2.jpg after you click any button**.\n```\ncv.imwrite('test2.jpg',img)\n```\n\nOkay all this tutorial to be continue to part 3.\n\n#### Curriculum\n\n- [Application Face Detection and Digital Imaging with Python on PYChram [part1] [NumPY]](https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy)\n\n\n<br /><hr/><em>Posted on <a href=\"https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part2-opencv\">Utopian.io -  Rewarding Open Source Contributors</a></em><hr/>",
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      "body": "@@ -2189,59 +2189,417 @@\n  to \n+%5B\n part 2\n- how to install OpenCV on PYChram and run it.\n+%5D(https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy) how to install OpenCV on PYChram and run it.%0A%0A#### Curriculum%0A%0A- %5BApplication Face Detection and Digital Imaging with Python on PYChram %5Bpart1%5D %5BNumPY%5D%5D(https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy)\n %0A%0A%3Cb\n",
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      "body": "\n#### What Will I Learn?\nWrite here briefly the details of what the user is going to learn in a bullet list.\n\n- You will learn Python\n- You will learn Numpy\n- You will learn Pychram\n\n#### Requirements\n\n- Package Numpy\n- Pychram\n\n#### Difficulty\n\n- Basic\n\n#### Tutorial Contents\nHello All of member Utopian, now I wanna make tutorial how to make \"Application Face Detection and Digital Imaging with Python\" but first you must know, what is numpy? \n###### Explanation Numpy\nNumpy is the module needed for OpenCV to work properly. Numpy itself is an abbreviation of Numerical python, is a library package that provides various routines to process multidimensional arrays.\n\n##### Add  Numpy Package on PYChram\n**1 . Open Your PYChram.**\n\n**2 . Add New Project With Name facedetector.**\n\n**3 . Add Numpy Library. Follow me to get install numpy library on your Pychram.**\n\n![1.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962814/nk4iwnxvqpwcd0wgj5lu.png)\n\n![2.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962838/ytld4rl89ckpsijm59er.png)\n\n![3.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521962925/rnj1pbpkquopaomivnd7.png)\n\n![4.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963046/i9759czzvtnoi8y2iqdd.png)\n\n##### Project First Numpy.\n\n**1 .  Add new python file. click right on project name > new > Python file.**\n![5.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963305/hcvdu9bzjrrithepnpnf.png)\n\n**2 .  Set with name tes-numpy.**\n\n![6.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963700/sy54yi3ce3arobn5trkm.png)\n\n**3 . Write this source code.**\n``` \nimport numpy as num\nnumber = num.array([1,2,3])\nprint (number)\n```\n**4 . Run that program.  right click > Run 'tes-numpy,**\nand you got that program result.\n![7.png](https://res.cloudinary.com/hpiynhbhq/image/upload/v1521963990/qfaxque8xgtzzrjteyhk.png)\n\n##### Explain Source Code.\nThis code to call numpy package to program.\n```\nimport numpy as num\n```\nThis code to make variable number with Array value ([1,2,3]).\n```\nnumber = num.array([1,2,3])\n```\nThis code to print value on variable number.\n```\nprint (number)\n```\nOkay this tutorial to be continue  to part 2 how to install OpenCV on PYChram and run it.\n\n<br /><hr/><em>Posted on <a href=\"https://utopian.io/utopian-io/@farahulfa/application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy\">Utopian.io -  Rewarding Open Source Contributors</a></em><hr/>",
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      "permlink": "application-face-detection-and-digital-imaging-with-python-on-pychram-part1-numpy",
      "title": "Application Face Detection and Digital Imaging with Python on PYChram [part1] [NumPY]"
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