This photo editor allows users to input a photo and apply any amount of preset filters and then save that photo to their computer. This included filters such as "black and white" and "posterize".
This project was my first ever project. It was proposed to me during my Introduction to Software Engineering class in my first year of university. The goal of the project was to create a photo editing application that using the terminal as a user interface. It would allow users to upload a photo to the software and apply one or various filters from a list of programmed filters. The user would then be able to save this filtered photo to their computer.
The project was broken down into five different types of files:
The project relied on a library called Cimpl.py. It was supplied by Carleton University and contained many functions to allow for the manipulation of images through their pixels. We mainly used the copy, the get and set colour, and the get height and width functions of the Cimpl.py library. This was all we needed to be able to manipulate the pixels of an image and return the edited image to the user.
The user interface was executed through the terminal using command lines inputted by the user. T28_interactive_ui.py contains a list of all the different colours that can be used to apply different filters to images. It also contains a dictionary of all the different image filters that a user can apply to an image. The dictionary keys are linked to the filters themselves, so when a user inputs ‘P’ for example, the posterize filter is applied to the image and returned to the user.
All the image filters are stored in T28_image_filters.py. It contains filters such as green_channel, which applies a green tint to the image supplied. All these filters create a copy of the given image, change the RGB codes on the copied image and returned the copied image to the user. T28_image_filters.py also contains a list of all the colours and a list of all the RGB codes attached to them. For example, the RGB code for black is (0, 0, 0) and both ‘black’ and ‘(0, 0, 0)’ are stored in the first position of each list so they can be indexed together.
The batch files are used for testing the image filters. T28_bath_ui.py contains all the commands needed to read the batchfile.txt file and perform all the tests included. These tests include a test image (dog.jpg) and apply three different filters to the image, checking after each filter is applied that they are correctly applied and the RGB codes are correctly modified.
There is also a designated testing file that tests every image filter, making sure they are functioning properly. Each of the filters take a subset of the images and run the tests against that subset, ensuring that each of the pixels have the intended RGB colour code.
We began this project by reading through the Cimpl.py library and familiarizing ourselves with the functions it contained and their functionality. We then learned how to use these functions in our own created functions, allowing us to create image filters that changed the RGB codes in the image provided.
We started very simple, by adding a blue, red, and green filter which gave the image a blue, red, or green tint. We did this by changing the first, second, or third RGB code (for context (0, 0, 0) is indexed 1, 2, and 3) to either blue, red, or green. For example, if we set the colour code to (0, g, 0), it would apply the green filter. Whereas if set the colour code to (r, 0, 0), it would apply the red filter. We finished off this first deliverable by creating test cases for the blue, red, and green filters and proceeded to do so with the remaining filters in this project
In the next iteration, we added the two and three tone filters, extreme contrast, sepia, and posterize filters. The two and three tone filters take colours inputted by the user and change the RGB codes, so they only contain those two or three colours. The extreme contrast filters set all the RGB codes to their maximum contrast. The sepia filter applied a grey and yellow tint to an image by multiplying the red and blue portions of an image by a percentage, depending on the already existing red scale. Finally, the posterize filter set colour of the middle pixel of the image to the rest of the image’s pixels.
In the final iteration, we added the edge detection, improved edge detection, vertical flip, and horizontal flip filters. The edge detection and improved edge detection filters enhanced pinpointed the contrast set on each of the pixels. For both filters, if a pixel was above a certain level of contrast, the pixel was automatically set to black or white. The vertical and horizontal flip filters flip the image vertically or horizontally, based on the names of the filters respectively.
We finished off by creating the batch files and user interface to interpret them. We were provided an image of a dog (dog.jpg) to do all our testing and used it in our batch.txt file for when the batch user interface read that file. We made the batch user interface so that the text file needed to supply at least one filter to a max of three filters to be applied on one image. We also made the user interface in a way that the text file could include multiple lines and various images, and each of those lines would be executed separately.
With this being my first taste of software development, I was absolutely hooked. I was full of curiosity about software and the industry since the class began and I always sat in the front so I could ask questions to get a very solid base of software knowledge.
This project let me put into practice my very limited knowledge of software at the time. I was also able to learn many different things that I didn’t know existed within software development, such as different data types and basic user interfaces through a terminal.
Since this project, I have had a knack for developing various types of software either during projects at school or on my own time. This project can be marked as the starting point to my obsession with software and its development.
