Technical documentation and insights on how steamcapsule.com analyzes and presents Steam artworks.
This project aims to help developers, artists particularly, create more effective capsule art that improves visibility and connects with their target audience.
A total of 861 games were analyzed, extracting patterns in color schemes, title placement, and visual composition.
If a game has specific genre-related tags within its top 3 tags on Steam, it's marked with the corresponding genre. This approach ensures that our genre classification reflects how the Steam community and developers categorize games.
Games can belong to multiple genres.
Here's the list of all ... unique games analyzed in this project.
My methodology combines visual analysis, color theory, and compositional principles to extract insights from Steam capsule art:
The data collection process involves both API usage and manual curation:
Games are selected through a weighted scoring system:
The analysis employs several computer vision techniques in a sequential process to extract meaningful data from capsule art:
Using a multi-stage approach, I first convert RGB data to the LAB color space for more perceptually accurate clustering, then apply k-means clustering via OpenCV to extract the 5 dominant colors from each capsule. The LAB values are normalized before clustering and converted back to RGB after. When analyzing colors, I convert them to HSV color space for better color classification and naming. For each color, I calculate percentage coverage based on pixel counts, allowing for analysis of color harmony, contrast levels, and genre-specific color trends.
EasyOCR is used to detect text regions in capsules, helping to identify title placement and analyze how text integrates with the visual elements.
By dividing each capsule into a 3×3 grid (9 zones), I analyze where visual and textual elements are placed. This reveals patterns in composition, focal points, and title placement across different game genres.
These three analytical approaches work together to create a comprehensive understanding of what makes capsule art effective on Steam, providing data-driven insights for game developers.
Several enhancements are planned to improve the analysis and user experience:
The current text detection system sometimes struggles with highly stylized or "unique" fonts. Future updates will implement advanced recognition models to better detect uniquely styled text elements in capsule art.
You will be able to export detailed analysis reports based on your specific filtering criteria. For example, you'll be able to export a custom report showing color trends for roguelike games with high review scores, or a report showing zone usage statistics for games with low review scores.
Last updated: March 2025.