Table of contents
User-Friendly Interface
Cupscale offers a simplified, user-friendly interface that makes it accessible to users without extensive technical knowledge in image upscaling.
Integration with ESRGAN
It integrates ESRGAN (Enhanced Super-Resolution Generative Adversarial Networks), leveraging its powerful capabilities for high-quality image upscaling.
Custom Model Support
Allows users to use custom-trained models, providing flexibility to achieve different results based on user requirements.
Batch Processing
Supports batch processing, enabling users to upscale multiple images simultaneously, saving time and effort.
Open Source
As an open-source project, Cupscale allows users and developers to contribute, modify, and enhance the software according to their needs.
We have collected here some useful links to help you find out if Cupscale is good.
Check the traffic stats of Cupscale on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of Cupscale on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of Cupscale's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of Cupscale on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about Cupscale on Reddit. This can help you find out how popualr the product is and what people think about it.
If you want to do more, there's chaiNNer and CupScale. You need to download an AI model to use those. There are a lot of anime/cartoon models out, so pick one that you like from here. (Note: Upscaly doesn't support these custom models.). Source: over 2 years ago
I'm not 100% sure how it holds up against topaz, but I've used cupscale (a gui for ESRGAN) to upscale most of my stuff. Its free (https://github.com/n00mkrad/cupscale) and you can find a million different ESRGAN models which are focused on different kinds of images (https://upscale.wiki/wiki/Model_Database). Source: over 2 years ago
Now upscaling isn't hard to do by itself, but the setup can be difficult. As I said earlier, ERSGAN is the preferable way to do it. (https://github.com/n00mkrad/cupscale) Cupscale is my preferred tool for doing it this way. (https://www.topazlabs.com/gigapixel-ai) Gigapixel is another option that's easier for newcomers, but may not produce as good of results. They even have a free trial if you want to demo the tool. Source: over 2 years ago
I use cupscale for upscaling things. Allows chaining models and handles video. Source: over 2 years ago
Made those with cupscale using a mix of anime-tuned models. Average speed for each rendering passage on my 1080ti is about 1 minute of footage per hour. Pretty slow as you can see, which is why will upgrade to rtx4080 soon. Source: over 2 years ago
There is also cupscale which is pretty good, it's the one I've been using, uses the same ai technology (esrgan - enhanced supper resolution generative adversarial network). Source: over 2 years ago
Upscale the image and it will be fine probably, all the noise and compression will be gone too. There's lots of free tools such as this one. Source: over 2 years ago
I used NMKD's donationware software cupscale with the ESRGAN model to do this. Source: over 2 years ago
Maybe look into Cupscale. But even then it might take a while to upscale 10 minutes of video. Source: over 2 years ago
I use a program called CUPscale for this. And it works great. Please try these suggestions, I think you will be pleased to see how you can take advantage of many AI driven tools to achieve something close to what you desire to spite being limited by your hardware. I too am limited with 6GBvram and have to utilize many work arounds to get to where I need things to be. (https://github.com/n00mkrad/cupscale). Source: almost 3 years ago
Additional Info: I use NMKD GUI 1.5 and also NMKD Cupscale for upscaling. Source: almost 3 years ago
Made with NMKD Stable Diffusion GUI 1.5 and upscaled with NMKD Cupscale. Source: almost 3 years ago
I also upscaled the end result with Cupscale. Source: about 3 years ago
Made with stock SD, ran it through Upscayl or cupscale at 4x resolution. Source: about 3 years ago
I recommend checking out cupscale if you haven't. Does a convincing job upresing. https://github.com/n00mkrad/cupscale. Source: about 3 years ago
Things have moved on a considerable amount since waifu2x Try https://github.com/n00mkrad/cupscale. - Source: Hacker News / about 3 years ago
Does somebody know a project like this one which is optimized/utilizes the M1 (especially the neural engine) which can be easily used to play around with some own .mp4 files? Source: about 3 years ago
The texture files from the original mod were 1K in BC1 compression. I have cleaned all files of compression artifacts caused by these older compression formats, and then upscaled them all by 4x, to a maximum resolution of 4K with BC7 compression and generated full mipmaps. I cleaned and upscaled them using Cupscale/ESRGAN and then finalized with NVIDIA Texture Tools and Octagon. Source: about 3 years ago
I'm not entirely sure it's relevant, but cupscale seems to automatically split and rejoin to work around vram constraints. Source: about 3 years ago
Here's a betterer idea. Use a neural network like ESRGAN to upscale any image. Cupscale if you don't like the terminal. Source: about 3 years ago
I use this IA for upscaling the pixeles from the back ground image https://github.com/n00mkrad/cupscale from 972x958 to 1920x1080. Source: about 3 years ago
Based on the cumulative insights from recent discussions and product mentions, Cupscale appears to be a highly regarded tool among users who are immersed in the realm of AI-driven video and image enhancement, specifically those who require advanced upscaling capabilities. Cupscale primarily functions as a graphical user interface for ESRGAN (Enhanced Super-Resolution Generative Adversarial Networks), offering users a robust and customizable platform for improving video and image fidelity.
Cost-Effective Solution: One of Cupscale's most notable advantages is that it is available for free under the GitHub repository of NMKD. This opens up powerful upscaling capabilities to a wide audience, from hobbyists to professional artists, without the need for a significant financial investment.
Support for Custom Models: Enthusiasts favor Cupscale due to its compatibility with a broad range of ESRGAN models. Users can leverage numerous anime and cartoon-focused models available via community resources, facilitating specialized use cases such as transforming 1080p game assets to 4K fidelity.
Favorable User Comparisons: Compared to other tools in its category like Topaz Gigapixel AI, Cupscale often comes out as a preferable choice, especially when users are willing to invest time in understanding its setup. While Gigapixel AI is praised for its newcomer-friendly interface, Cupscale is described as offering superior results even though the initial setup can be complex.
Versatile Use Cases: Posts highlight Cupscale's versatile application, from enhancing video frames to cleaning image compression artifacts and upscaling textures for gaming. It demonstrates competency across diverse artistic and technical workflows, as evidenced by creative projects like upscaled comic art and video game modifications.
Resource Management: A distinct feature of Cupscale is its capacity to handle VRAM limitations efficiently. It automatically splits and rejoins images, making it accessible for users with constrained hardware resources yet desiring high-resolution outputs.
Community and Support: Its open-source nature has cultivated a supportive community, evident from mentions of resources like model databases on upscale.wiki. Users regularly share insights, tips, and personal projects, contributing to a collaborative environment.
Though Cupscale is well-received, users acknowledge that it might require a steeper learning curve, particularly for those unaccustomed to working with AI models and configurations. The software can be resource-intensive, with reports of slow processing speeds unless supported by higher-end hardware.
In summary, Cupscale stands out in the field of AI-driven upscaling due to its flexibility, cost-effectiveness, and ability to work with a variety of models. While it may not offer the plug-and-play ease of some commercial counterparts, its customization options and solid performance continue to resonate well with a technically adept user base seeking bespoke upscaling solutions.
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