Driven by a desire to understand how Photoshop worked under the hood, the author embarked on a personal project to recreate core functionalities in C++. Focusing on fundamental image manipulation like layers, blending modes, filters (blur, sharpen), and transformations, they built a simplified version without aiming for feature parity. This exercise provided valuable insights into image processing algorithms and the complexities of software development, highlighting the importance of optimization for performance, especially when dealing with large images and complex operations. The project, while not a full Photoshop replacement, served as a profound learning experience.
In a detailed blog post titled "That Time I Recreated Photoshop in C++," the author, Fabien Sanglard, recounts his ambitious personal project of building a simplified version of Adobe Photoshop from the ground up using C++. Driven by a desire to deepen his understanding of image manipulation and software development principles, Sanglard embarked on this challenging endeavor.
He began by outlining the core functionalities he aimed to replicate, including image loading and saving, basic selection tools, and a range of image processing filters like blur, sharpen, and color adjustments. Instead of relying on existing image processing libraries, Sanglard opted to implement these features from scratch, providing himself with invaluable insight into the underlying algorithms and mathematical operations involved. This approach necessitated delving into the intricacies of image formats, color spaces, and pixel manipulation techniques.
The project chronicle meticulously documents the various stages of development, beginning with the initial setup of the C++ project and the implementation of fundamental functionalities like reading and writing image files. Sanglard explains his decision to utilize the Simple DirectMedia Layer (SDL) library for window management and basic graphics rendering, which allowed him to focus on the core image processing logic.
The post then proceeds to detail the implementation of specific features. Sanglard explains how he tackled challenges such as implementing the selection tool, which involved managing pixel selection and manipulating only the selected region. He further elaborates on the development of image filters, outlining the algorithms used for blurring, sharpening, and color adjustments. The explanations are accompanied by code snippets showcasing the core logic behind each feature.
Throughout the development process, Sanglard encountered and overcame several obstacles, demonstrating his problem-solving skills. He describes how he debugged and optimized his code to improve performance, highlighting the iterative nature of software development.
Ultimately, while acknowledging that his creation wasn't a complete Photoshop replacement, Sanglard successfully built a functional image editor capable of performing basic image manipulation tasks. The project served as a profound learning experience, providing him with a deeper understanding of image processing principles, C++ programming, and software development methodologies. The blog post concludes with reflections on the lessons learned and the satisfaction derived from completing such a substantial undertaking.
Summary of Comments ( 122 )
https://news.ycombinator.com/item?id=43374278
Hacker News users generally praised the author's project, "Recreating Photoshop in C++," for its ambition and educational value. Some questioned the practical use of such an undertaking, given the existence of Photoshop and other mature image editors. Several commenters pointed out the difficulty in replicating Photoshop's full feature set, particularly the more advanced tools. Others discussed the choice of C++ and suggested alternative languages or libraries that might be more suitable for certain aspects of image processing. The author's focus on performance optimization and leveraging SIMD instructions also sparked discussion around efficient image manipulation techniques. A few comments highlighted the importance of UI/UX design, often overlooked in such projects, for a truly "Photoshop-like" experience. A recurring theme was the project's value as a learning exercise, even if it wouldn't replace existing professional tools.
The Hacker News post titled "That Time I Recreated Photoshop in C++" (linking to an article detailing the author's experience recreating Photoshop features in C++) has generated a number of comments discussing various aspects of the project and image editing software in general.
Several commenters focus on the author's choice of C++ and question its suitability for such a project. Some suggest that languages like C# with its garbage collection might have been a more productive choice, especially for managing memory when dealing with large images. Others point out that the performance benefits of C++ might not be fully realized in this type of application, given that many image processing operations are already highly optimized within existing libraries.
A significant thread of discussion revolves around the learning experience gained from such an undertaking. Commenters acknowledge the value of recreating existing software for educational purposes, emphasizing the deeper understanding of underlying principles that can be acquired through such a project. They also discuss the challenges of replicating complex software and the importance of choosing a well-defined scope to avoid becoming overwhelmed.
Some users express skepticism about the true extent of the "recreation," pointing to the potential difference between replicating the user interface and implementing the underlying image processing algorithms. They argue that the true complexity of Photoshop lies in its highly optimized algorithms and vast feature set, which would be extremely difficult to replicate fully.
Another commenter shares their own experience with writing a simplified image editor, offering insights into the intricacies of handling features like selection tools and layer management.
A few comments delve into the technical aspects of image processing, mentioning libraries like GEGL and the complexities of color management.
Finally, several commenters offer alternative approaches and tools for image editing, including GIMP and various command-line utilities, suggesting that these might be more efficient solutions depending on the specific needs. They highlight the mature and feature-rich nature of existing open-source options.