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fp:assig-01 [2021/04/26 12:19]
dmihai [2. Type-specific transformations (0.6p)] 		fp:assig-01 [2021/05/06 17:32] (current)
dmihai [Submission]
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-==== Introduction ====+**Deadline: May 7th, 23:55** 
 + 
 +===== Introduction ​=====
  
 For this assignment, we will work with images and implement some basic image manipulations. For this assignment, we will work with images and implement some basic image manipulations.
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 2.2.  **cropping with a rectangle selection** 2.2.  **cropping with a rectangle selection**
-            * your function should take a rectangle modelled by a ''​(Int,​ Int, Int, Int)''​ tuple (the first two ''​Int''​s are the coordinates of the top-right corner, the next two ''​Int''​s are the height and width of the rectangle). It should return a new image with the same height and width as the rectangle selection containing the pixels in the image which fall withing the rectangle'​s area.+            * your function should take a rectangle modelled by a ''​(Int,​ Int, Int, Int)''​ tuple (the first two ''​Int''​s are the coordinates of the top-left corner, the next two ''​Int''​s are the height and width of the rectangle). It should return a new image with the same height and width as the rectangle selection containing the pixels in the image which fall withing the rectangle'​s area.
  
 2.3.  **brightness adjustment** 2.3.  **brightness adjustment**
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 Our focus here is simply on how to program in a functional style, so we don't really aim for performance and smooth results. Our focus here is simply on how to program in a functional style, so we don't really aim for performance and smooth results.
  
-For example, the scaling algorithm presented (a form of [[https://​en.wikipedia.org/​wiki/​Nearest-neighbor_interpolation|nearest-neighbor]] ​interpolation}) is easy to write, but its results are poor.+For example, the scaling algorithm presented (a form of [[https://​en.wikipedia.org/​wiki/​Nearest-neighbor_interpolation|nearest-neighbor ​interpolation]]) is easy to write, but its results are poor.
 You can see [[https://​en.wikipedia.org/​wiki/​Comparison_gallery_of_image_scaling_algorithms|here]] a quality comparison of various algorithms. You can see [[https://​en.wikipedia.org/​wiki/​Comparison_gallery_of_image_scaling_algorithms|here]] a quality comparison of various algorithms.
  
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 For very basic testing, you can define your own test-cases. However, to give you a big-picture view and some satisfying results, we offer you a testing framework for [[https://​en.wikipedia.org/​wiki/​Netpbm#​File_formats|Netpbm]] ASCII-format images. For very basic testing, you can define your own test-cases. However, to give you a big-picture view and some satisfying results, we offer you a testing framework for [[https://​en.wikipedia.org/​wiki/​Netpbm#​File_formats|Netpbm]] ASCII-format images.
  
-Netpbm a simplistic pixel-map image format, capable of modelling both greyscale and RGB pictures.+Netpbm ​is a simplistic pixel-map image format, capable of modelling both greyscale and RGB pictures.
  
 A Netpbm image file has the following structure: A Netpbm image file has the following structure:
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   * for single image transformations (i.e. all except masking), edit line 13. The following example will configure it with a crop of a 50x50 square that starts at coordinates (30, 30):   * for single image transformations (i.e. all except masking), edit line 13. The following example will configure it with a crop of a 50x50 square that starts at coordinates (30, 30):
     * <​code>​myTransform img = crop (30, 30, 80, 80) img</​code>​     * <​code>​myTransform img = crop (30, 30, 80, 80) img</​code>​
-  * for transformations that require ​to images (just masking), line 16 is relevant; but you can leave it as it is, as there'​s only one transformation candidate.+  * for transformations that require ​two images (just masking), line 16 is relevant; but you can leave it as it is, as there'​s only one transformation candidate.
  
 After having edited ''​Main.hs''​ you can run it; depending on the number of arguments, it will choose an appropriate type of transformation (single/​multiple image); it also correctly chooses between greyscale/​RGB functions based on the actual filetype. To run the file you need the ''​runhaskell''​ binary (or ''​runghc'';​ both should come with the haskell platform), then run it from a shell: After having edited ''​Main.hs''​ you can run it; depending on the number of arguments, it will choose an appropriate type of transformation (single/​multiple image); it also correctly chooses between greyscale/​RGB functions based on the actual filetype. To run the file you need the ''​runhaskell''​ binary (or ''​runghc'';​ both should come with the haskell platform), then run it from a shell:
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 ==== Submission ==== ==== Submission ====
  
-For submission you should create a zip archive of the two files you modified: ''​Greyscale.hs''​ and ''​Color.hs''​ and a ''​README''​. The ''​README''​ should contain a succinct high-level presentation of your work. The archive name should be ''​LASTNAME_Firstname_FP_A1.zip''​ (if you have multiple firstnames, separate them by an underline "​_"​). Mail it to [[mailto:​mihai.dumitru2201@upb.ro|mihai.dumitru2201@upb.ro]].+For submission you should create a zip archive of the three files you modified: ​''​Common.hs'', ​''​Greyscale.hs''​ and ''​Color.hs''​ and a ''​README''​. The ''​README''​ should contain a succinct high-level presentation of your work. The archive name should be ''​LASTNAME_Firstname_FP_A1.zip''​ (if you have multiple firstnames, separate them by an underline "​_"​). Mail it to [[mailto:​mihai.dumitru2201@upb.ro|mihai.dumitru2201@upb.ro]].