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README-en.md edited on August 3, 2016 at 3:40pm

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 ## Image Editing
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 ## Image Editing
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-In this laboratory experience, you will work with various concepts and basic skills of image editing. We have provided a simple graphical user interface that allows the user to load an image and invert it vertically and horizontally. Your task is to create and implement a function to convert the colored image into an image with gray tones, and another function that converts the colored image into a black and white image.
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+In this laboratory experience, you will work with various concepts and basic skills of image editing. We have provided a simple graphical user interface that allows the user to load an image and invert it vertically and horizontally. Your task is to create and implement a function that converts a colored image into an image with gray tones, and another function that converts the colored image into a black and white image.
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 ### Pixels
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 ### Pixels
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-`Qt` uses the `QRgb` type to represent `RGB` values. Using certain functions that are described below we can obtain the red, green and blue components of the `QRgb` value of the pixel and manipulate the images.
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+`Qt` uses the `QRgb` type of data to represent `RGB` values. Using certain functions that are described below, we can obtain the red, green, and blue components of the `QRgb` value of the pixel and manipulate the images.
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 ### Library
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 ### Library
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-In today's laboratory experience you will use the `QImage` class. This class allows access to the data in the pixels of an image to manipulate it. The documentation for the `QImage` class can be found in http://doc.qt.io/qt-4.8/qimage.html.
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+In today's laboratory experience you will use the `QImage` class. This class allows access to the data in the pixels of an image in order to manipulate it. The documentation for the `QImage` class can be found in http://doc.qt.io/qt-4.8/qimage.html.
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 The code provided in this project contains the following objects of the `QImage` class:
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 The code provided in this project contains the following objects of the `QImage` class:
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 ### Exercise 2 - Convert a Colored Image to an Image with Gray Tones
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 ### Exercise 2 - Convert a Colored Image to an Image with Gray Tones
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-Image grayscale is an operation that is used to convert a colored image to an image with only tones of gray. To make this conversion the following formula is used in each pixel:
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+Image grayscale is an operation that is used to convert a colored image to an image with tones of gray only. To make this conversion the following formula is used in each pixel:
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  `gray = (red * 11 + green * 16 + blue * 5)/32 ;` where `red`, `green` and `blue` are the values for the tones of the red, green and blue colors in the pixel of the original colored image, and `gray` will be the assigned color to the red, green, and blue colors in the pixel of the edited image. That is,
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  `gray = (red * 11 + green * 16 + blue * 5)/32 ;` where `red`, `green` and `blue` are the values for the tones of the red, green and blue colors in the pixel of the original colored image, and `gray` will be the assigned color to the red, green, and blue colors in the pixel of the edited image. That is,
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 `editedImage.setPixel( i, j, qRgb(gray, gray, gray) )`.
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 `editedImage.setPixel( i, j, qRgb(gray, gray, gray) )`.
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 #### Instructions
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 #### Instructions
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-1. Using pseudocode, express the algorithm to convert a colored image to an image with only gray tones. The appendix in this document contains some advice about good techniques for writing pseudocode.
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+1. Using pseudocode, express the algorithm to convert a colored image to an image with gray tones only. The appendix in this document contains some advice about good techniques for writing pseudocode.
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 2. Complete the `GreyScale` function in the `filter.cpp` file to implement the grayscale algorithm. The function should produce a result similar to that in Figure 3, where the image on the left is the original image and the one on the right is the edited image.
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 2. Complete the `GreyScale` function in the `filter.cpp` file to implement the grayscale algorithm. The function should produce a result similar to that in Figure 3, where the image on the left is the original image and the one on the right is the edited image.
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