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A consolidation of various compiled open-source AI image/video upscaling product for a working CLI friendly image and video upscaling program.

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Holloway's Upscaler - Image & Video

Holloway's Upscaler This project is a consolidation of various compiled open-source AI image/video upscaling product for a working CLI-friendly image and video upscaling program.

Why It Matters

For these reasons:

  1. Low-cost image/video AI upscaling software - run locally in your laptop with an AI solution.
  2. Programmable - when you upscale an album or a video, the AI program has to be programmable and not restricted by any GUI's design.
  3. Reliabily working for big subject - video files are usually large and require streaming algorithm approach to prevent uncontrollable resources consumption in a simple OS system (e.g. disk space, RAM, and vRAM).
  4. I urgently need a video upscaling technologies to work locally - for both image and video without any GUI overheads.

Contributors

This repository was made possible by the following contributors:

  1. Joly0 Sponsor - Windows support via PowerShell.
  2. Cory Galyna - Repository & CI management.
  3. Jean Shuralyov - Documentations.
  4. (Holloway) Chew, Kean Ho Sponsor - FFMPEG & UNIX Support via POSIX Shell and Polygot Script.

Supported Hardware

Here are the tested hardware and operating system:

System Results Usable Processing Units
debian-amd64 (linux) PASS NVIDIA GeForce MX150, Intel(R) UHD Graphics 620 (KBL GT2)
darwin-amd64 (macOS) FAILED Binary failed to use Intel Iris Graphics iGPU and CPU.
windows-amd64 (windows) PASS Nvidia Quadro T600, Intel Iris Xe Graphics

IMPORTANT NOTES

(1)

You seriously need a compatible GPU to drastically speed up the upscaling efforts from hours to seconds for image. I tested mine against NVIDIA GeForce MX150 vs. Intel(R) UHD Graphics 620 (KBL GT2) built-in graphic hardwares in my laptop. It did a huge difference.

(2)

At the moment, the algorithm only works on constant bit rate video. Variable bit rate (VBR) video are considered but may be done in the future with proper programming language. Most (as in 99% of video) are constant bit rate video so VBR support is at least concern.

(3)

Not all images can be upscaled (e.g. some AI generated images from Stable Diffussion) due to the binary's internal image decoder bug. Tracking issue: xinntao/Real-ESRGAN#595

(4)

Re-packaging efforts are unlikely because currently it's a bad investment. It's either I spend the time study NCNN and write the whole XinTao's RealESRGAN-Vulcan program as my own codes from scratch or glued some existing programs together. At the moment, I do not have the resources to rewrite or study the NCNN (yet).

NOTE TO MacOS USERS

The binary bin/mac-amd64 is currently unsigned. Hence, you need to explictly grant the use permission in your Settings > Security & Privacy section.

Please be informed that my test result is in accordance with the Upscayl team: many CPU and iGPUs are not working and supported yet.

Dependencies

If you're working on video, you need ffmpeg and ffprobe for dissecting and reassembling a video file.

You can proceed to install them in 1 go at: https://ffmpeg.org/

Windows User

You need to install Microsoft Visual C++ Redistributable Package from their official website if you haven't do so. Usually other software may automatically include a version installed already. Please check your "Add/Remove Program" control panel to verify.

User Manual

Here are the basic user manuals:

Install

There are different ways of installing this program depending on your interested versions:

>= v0.6.0

You can download the latest version of the upscaler-[VERSION].zip package from https://github.com/hollowaykeanho/Upscaler/releases and then unzip it to an appropriate location. Note that the models are already included in this package.

For those who wants to just update the models, the upscaler-models-[VERSION].zip is made available for you. Simply overwrite the models/ directory's contents in the software.

For those who wants to run test and benchmarks for the repository, the upscaler-tests-[VERSION].zip is made available for you. Simply integrate the tests/ directory into your existing software program (the unpacked upscaler-[VERSION].zip).

< v0.6.0

You need to git clone the repository into an appropriate location.

$ git clone https://github.com/hollowaykeanho/Upscaler.git

Setup Pathing for Command [OPTIONAL, 1-Time]

We advise you to symlink the start.cmd into $PATH or %PATH% directory depending on your operating system. Example, on Debian Linux:

$ ln -s /path/to/Upscaler/start.cmd /path/to/bin/upscaler

Alternatively, on UNIX (Linux & Mac) systems, you can create a shell script that pass all arguments into the start.cmd. Example:

#!/bin/sh
/path/to/Upscaler/start.cmd "$@"

TIP: if had you decided to use the shell script approach, you can also design the command to use your default model and scaling for your programming efficiencies. Recommend you use $HOME/bin directory if it is set visible in your $PATH value.

Call for Help

This repository was unified using Holloway's Polygot Script to keep user instruction extremely simple. Hence, in any operating system (UNIX or WINDOWS), simply interact with the repository's start.cmd script will do. Example for requesting a help instruction:

$ ./Upscaler/start.cmd --help

In the help display, you generally want to take notice of the AVAILABLE MODELS list. The upscaling algorithms are solely based on the available models in the models directory. The scripts are written in a way to dynamically index each of them and present it in the help display without re-writing itself.

Upscale an Image

To upscale an image simple run start.cmd against the image:

$ ./start.cmd \
        --model ultrasharp \
        --scale 4 \
        --format webp \
        --input my-image.jpg

To determine the available models, their respective scale limits, and their output formats, simple execute the --help and look for: AVAILABLE MODELS and AVAILABLE FORMATS respectively.

If done correctly, an image based on orginal filename with a suffix -upscaled is created. If we follow the example above, it should be my-image-upscaled.webp.

Upscale a Video

Unless you're working on 8 seconds 8MB sized video, you would want to follow the instructions below to make sure your project are always in-tact and resumeable.

(1) Budget Your Hardware Storage

Please keep in mind that you need at least 3x video size storage for the job depending on the video frame rate, frame size, color schemes and etc. The minimum 3x is due to:

  1. 1 set is your original video.
  2. 1 set is for all the upscaled images (can be a lot bigger since we're doing it frame by frame; losing the video compression effect).
  3. 1 set is your output video (bigger than original of course).

Hence, please plan out your storage budget before starting a video upscaling project.

IMPORTANT

Know your hardware limitations before determining the scaling factor. A scale of 4x on a 1090p for a 12GB memory laptop can crash the entire OS (I'm referring the very stable Debian OS) during the video re-assembly phase with FFMPEG due to memory starvation.

(2) Setup Project Directory

You're advised to create a project directory for upscaling video project due to its large sized data.

Instead of executing the start.cmd straight away, please script it inside and place it in a project directory.

A simple UNIX example would be a shell script (e.g. run.sh) as follows:

#!/bin/sh
/path/to/Upscaler/start.cmd --model ultrasharp \
	--scale 4 \
	--input ./sample-vid.mp4 \
	--video

A simple WINDOWS example would be a batch script (e.g. run.bat) as follows:

@echo off
/path/to/Upscaler/start.cmd --model ultrasharp ^
	--scale 4 ^
	--input ./sample-vid.mp4 ^
	--video

This is for resuming the upscaling project in case of crashes or long hours work. A good directory looks something as follows:

/path/to/my-upscaled-project/
├── run.sh
└── sample-vid.mp4

(3) Run The Initator Script

To initiate or to resume project, simply run your initiated project:

# cd /path/to/my-upscaled-project
$ ./run.sh

The Upscaler will create a workspace to house its output frames and control values. You can inspect the frame images while Upscaler is at work as long as you're viewing the frame that it is working on.

I recommend you inpect the frames first for determining whether the AI model is suitable or otherwise. Otherwise, please stop the process and execute the next step.

(4) Resetting the Project [JUST IN CASE]

Just in case if you bump into something odd that requires to restart the project from start, you can delete the [FILENAME]-workspace directory inside the project directory. This will force the program to restart everything all over again.

The project is set to intentionally leave the workspace as it is in case you need to use the frames for other purposes (e.g. thumbnail).

Helping The Project

Star, Watch, or the best: sponsor the contributors.

Contribute Back

In case you need to contribute back:

  1. Raise an issue ticket.
  2. Fork the repository and work against the main branch.
  3. Develop your contributions and ensure your commit are GPG-signed.
  4. Once done, DO NOT raise a pull request unless instructed. Simply notify me via your ticket and I will clone your forked repo locally and cherry-pick them (I need those GPG signatures preserved where GitHub Pull Request cannot fulfill). An exception would be the you have a need to earn the GitHub Pair Extraordinaire Badge. For doing that, please add me into your forked repo and I will make it happen for you.
  5. Delete your fork repo once I notify you that the merging is completed.
  6. Thank you.

Benchmarks

Submit results of benchmarks running tests/benchmark.cmd at the root of the repository. These data serves few purposes:

  1. To test the repository's programs are running properly for both video and image upscaling.
  2. To identify what platform, OS, and hardware capable of running this project. (good for determining usability before procurement).
  3. To know about its statistical performances.

IMPORTANT NOTE

The benchmark.cmd captures wall-clock timing. Hence, please leave the system dedicated to only running the benchmark and not doing something else for maintaining results consistencies. We're capturing wall-clock timing for real time use (e.g. subjected to OS and background processes interferences).

Our recommendation is to leave it run overnight before you sleep (~400 frames) so it takes some time.

Debian-AMD64; Intel Xeon E3-1200 v6/7th Gen CPU; 12GB RAM; 2GB VRAM; NVIDIA GeForce MX150

Version Sample 1 (Video)
v0.7.0 9587 seconds
v0.6.0 9260 seconds
v0.5.0 9192 seconds
v0.4.0 10316 seconds

Windows-AMD64; AMD Ryzen 9 7950x CPU; 22GB RAM; 4GB VRAM; Nvidia Quadro T600

Version Sample 1 (Video)
v0.6.0 3649 seconds

Windows-AMD64; Intel i5-1235U CPU; 16GB RAM; 128MB VRAM; Intel Iris Xe Graphics

Version Sample 1 (Video)
v0.7.0 11633 seconds

Commands Help

In case you can't access to the help details found from the --help command, here's a copy from the UNIX side:

u0:Upscaler$ ./start.cmd --help

HOLLOWAY'S UPSCALER
-------------------
COMMAND:

$ ./start.cmd \
        --model MODEL_NAME \
        --scale SCALE_FACTOR \
        --format FORMAT \
        --parallel TOTAL_WORKING_THREADS  # only for video upscaling (coming soon) \
        --video                           # only for video upscaling \
        --input PATH_TO_FILE \
        --output PATH_TO_FILE_OR_DIR      # optional

EXAMPLES

$ ./start.cmd \
        --model ultrasharp \
        --scale 4 \
        --format webp \
        --input my-image.jpg

$ ./start.cmd \
        --model ultrasharp \
        --scale 4 \
        --format webp \
        --input my-image.jpg \
        --output my-image-upscaled.webp

$ ./start.cmd \
        --model ultrasharp \
        --scale 4 \
        --format png \
        --parallel 1 \
        --video \
        --input my-video.mp4 \
        --output my-video-upscaled.mp4

$ ./start.cmd \
        --model ultrasharp \
        --scale 4 \
        --format png \
        --parallel 1 \
        --input video/frames/input \
        --output video/frames/output

AVAILABLE FORMATS:
(1) PNG
(2) JPG
(3) ...

AVAILABLE MODELS:
...

Upstream and Source Codes

This is a binaries assembled repository. You may find the source codes from the original contributors here:

  1. Tencent's NCNN
  2. Nihui
  3. Xintao
  4. Upscayl (Nayam Amarshe & TGS963)

Test sample video in the tests/ directory was supplied by Igrid North from Pexels. Original 4k sized video is also available at origin for upscaling comparison.

License

This project is aligned to its upstream sources and is licensed under BSD-3-Clause "New or "Revised" License.

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A consolidation of various compiled open-source AI image/video upscaling product for a working CLI friendly image and video upscaling program.

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