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@ -1,13 +1,7 @@
# Stitch-a-ton Contest Submission # Stitch-a-ton Contest Submission
Repository moved to: https://github.com/denniskematian/GigATon
## Installation ## Installation
This project is build using .NET 9, with SixLabors.ImageSharp as the only external library.
Please refer to [install dotnet SDK on Debian](https://learn.microsoft.com/en-us/dotnet/core/install/linux-debian?tabs=dotnet9)
for details.
### 1. Build ### 1. Build
Install dependencies: Install dependencies:
@ -15,7 +9,7 @@ Install dependencies:
wget https://packages.microsoft.com/config/debian/12/packages-microsoft-prod.deb wget https://packages.microsoft.com/config/debian/12/packages-microsoft-prod.deb
sudo dpkg -i packages-microsoft-prod.deb sudo dpkg -i packages-microsoft-prod.deb
sudo apt update sudo apt update
sudo apt install -y dotnet-sdk-9.0 sudo apt install -y dotnet-sdk-8.0
``` ```
Build the project in `App` folder using command: Build the project in `App` folder using command:
@ -30,13 +24,8 @@ After publishing, enter the folder `/publish` then run
./StitchATon2.App ./StitchATon2.App
``` ```
## Ideas ## Approach
Since we only serve a static assets and the output is downscale only, I think it's good to pre-process each image to [image integral](https://en.wikipedia.org/wiki/Summed-area_table) first and then save it to another directory (eg. temp). Since we only serve a static assets and the output is downscale only, I think it's good to pre-process each image to [image integral](https://en.wikipedia.org/wiki/Summed-area_table) first and then save it to another directory (eg. temp).
Later, we can apply Box Filter averaging on the fly to output Stream (HttpResponse). Later, we can apply Box Filter averaging on the fly to output Stream (HttpResponse).
## Approach
This project is heavily depends on Memory Mapped File to reduce processing overhead and memory pressure to allow HTTP serve more request.
The MMF is used to store the Image Integral of provided asset.