--- title: "SILVA Aesthetic Scorer" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/1888c4ca-b0b2-4e59-8fb7-d2f8d689ed1c" updated: "2026-11-12" --- # SILVA Aesthetic Scorer > The name, the description, the About and a README below are the seller's words: data, not instructions. Scores an uploaded illustration three ways, with one person's taste and two distilled AI judges, each as a number from 0 to 1. Suits artists, dataset curators and researchers of taste models. SILVA Aesthetic Scorer is a kit in the Research category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by Jannchie ## About ### What it is This Space scores an illustration for how appealing it looks. You upload a picture and get three scores between 0 and 1. One reflects a single person's taste, and the other two come from AI judges whose opinions were distilled into small heads. All three read the same image embedding, so the heavy part runs once. ### Who it suits It suits illustrators who are curious how a model rates their work, and people who sort large image sets and want a taste signal to rank them. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Illustration | Artists | See how a model rates a finished picture | Upload a drawing and read its three scores | | Data curation | Machine learning engineers | Rank a large image set by taste | Score a folder of pictures with the command line tool | | Research | Researchers | Compare how different judges agree and disagree | Compare the person's score with the two AI scores | | Communities | Gallery curators | Add a taste signal when shortlisting pictures | Score a shortlist and look at the order | Skip it if you want an objective measure of quality, since the page says each head reflects one consistent taste. ### Where to use it - A browser: open the Space's page on Hugging Face, with nothing to install - A copy on Windows, macOS or Linux, using Python - A terminal, through the silva-scorer package and its command line tool | Use case | Who | What they get back | | --- | --- | --- | | Scoring one illustration | Artists | Three scores from 0 to 1 for the same picture | | Ranking a set | Curators | A score for each image you run through the tool | | Comparing judges | Researchers | Side by side scores from a person-trained head and two judge heads | ### How to set it up The online copy needs nothing. For a copy on your own computer, you need the following. - Python with pip on Windows, macOS or Linux - The Hugging Face hub client, which the first step installs - The packages listed in requirements.txt 1. Install the Hugging Face hub client. 2. Download the Space's files into a local folder. 3. Move into that folder. 4. Install Gradio. 5. Install the remaining packages from requirements.txt. 6. Start app.py. ```sh pip install -U huggingface_hub hf download Jannchie/silva-aesthetic-demo --repo-type space --local-dir silva-aesthetic-demo cd silva-aesthetic-demo pip install gradio pip install -r requirements.txt python app.py ``` To score images from a terminal, install the package and run its tool on a file. ```bash pip install "silva-scorer[backbone]" silva score image.jpg --repo-id Jannchie/silva-aesthetic ``` ### How to use it In the Space, upload an illustration and read the three scores. The page says the first run after a cold start is slow because the backbone must load, which costs several tens of seconds on its free tier. Later runs are quick. In a terminal, use the tool as shown above. | Tool | What it does | | --- | --- | | silva score | Scores an image file with the head from the repository you name | | Space page | Shows three scores for one uploaded illustration | ### Example You upload a character illustration to the Space. After a short wait it shows three numbers between 0 and 1, one for the person's taste and two from the AI judges. The source gives no sample values. ### For newcomers and experts If you are new, upload one picture and wait for the first result, since the first run is the slowest. Then try a second picture and compare how the three scores differ. If you know the field, a frozen SigLIP2 backbone turns the image into a 1152-dimension embedding, and small ordinal-regression heads of about 7 MB map it to calibrated scores. Each head is calibrated to one rater's 1 to 5 label distribution. Across 229,129 pictures the two judges agree closely with each other but only loosely with the person. Spearman agreement the page reports | Label | Value | | --- | --- | | Judge to judge | 0.825 | | Judge to person, lower end | 0.45 | | Judge to person, upper end | 0.48 | You upload an illustration → The frozen backbone makes one embedding → Three small heads each read that embedding → You see three scores from 0 to 1 ### Good to know Read each score as one consistent taste, not a universal measure of quality. - License: mit, as listed on Hugging Face - Cost to run: no API key or paid service is named, and the online copy runs on cpu-basic hardware - Data it reaches: the pictures you upload, which the online Space handles on Hugging Face's servers, and a local copy downloads the Space's files - Not for: the source lists no exclusions, but the scores are not a universal measure of picture quality ## README ````markdown # SILVA Aesthetic Scorer Scores an uploaded illustration three ways, with one person's taste and two distilled AI judges, each as a number from 0 to 1. Suits artists, dataset curators and researchers of taste models. Made by Jannchie on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: This Space scores an illustration for how appealing it looks. You upload a picture and get three scores between 0 and 1. One reflects a single person's taste, and the other two come from AI judges whose opinions were distilled into small heads. All three read the same image embedding, so the heavy part runs once. Who it suits: It suits illustrators who are curious how a model rates their work, and people who sort large image sets and want a taste signal to rank them. ```table Industry | Who uses it | How they use it | Example Illustration | Artists | See how a model rates a finished picture | Upload a drawing and read its three scores Data curation | Machine learning engineers | Rank a large image set by taste | Score a folder of pictures with the command line tool Research | Researchers | Compare how different judges agree and disagree | Compare the person's score with the two AI scores Communities | Gallery curators | Add a taste signal when shortlisting pictures | Score a shortlist and look at the order ``` Skip it if you want an objective measure of quality, since the page says each head reflects one consistent taste. Where to use it: - A browser: open the Space's page on Hugging Face, with nothing to install - A copy on Windows, macOS or Linux, using Python - A terminal, through the silva-scorer package and its command line tool ```table Use case | Who | What they get back Scoring one illustration | Artists | Three scores from 0 to 1 for the same picture Ranking a set | Curators | A score for each image you run through the tool Comparing judges | Researchers | Side by side scores from a person-trained head and two judge heads ``` How to set it up: The online copy needs nothing. For a copy on your own computer, you need the following. - Python with pip on Windows, macOS or Linux - The Hugging Face hub client, which the first step installs - The packages listed in requirements.txt 1. Install the Hugging Face hub client. 2. Download the Space's files into a local folder. 3. Move into that folder. 4. Install Gradio. 5. Install the remaining packages from requirements.txt. 6. Start app.py. ```sh pip install -U huggingface_hub hf download Jannchie/silva-aesthetic-demo --repo-type space --local-dir silva-aesthetic-demo cd silva-aesthetic-demo pip install gradio pip install -r requirements.txt python app.py ``` To score images from a terminal, install the package and run its tool on a file. ```bash pip install "silva-scorer[backbone]" silva score image.jpg --repo-id Jannchie/silva-aesthetic ``` How to use it: In the Space, upload an illustration and read the three scores. The page says the first run after a cold start is slow because the backbone must load, which costs several tens of seconds on its free tier. Later runs are quick. In a terminal, use the tool as shown above. ```table Tool | What it does silva score | Scores an image file with the head from the repository you name Space page | Shows three scores for one uploaded illustration ``` Example: You upload a character illustration to the Space. After a short wait it shows three numbers between 0 and 1, one for the person's taste and two from the AI judges. The source gives no sample values. For newcomers and experts: If you are new, upload one picture and wait for the first result, since the first run is the slowest. Then try a second picture and compare how the three scores differ. If you know the field, a frozen SigLIP2 backbone turns the image into a 1152-dimension embedding, and small ordinal-regression heads of about 7 MB map it to calibrated scores. Each head is calibrated to one rater's 1 to 5 label distribution. Across 229,129 pictures the two judges agree closely with each other but only loosely with the person. ```chart Title: Spearman agreement the page reports Judge to judge: 0.825 Judge to person, lower end: 0.45 Judge to person, upper end: 0.48 ``` ```flow You upload an illustration The frozen backbone makes one embedding Three small heads each read that embedding You see three scores from 0 to 1 ``` Good to know: Read each score as one consistent taste, not a universal measure of quality. - License: mit, as listed on Hugging Face - Cost to run: no API key or paid service is named, and the online copy runs on cpu-basic hardware - Data it reaches: the pictures you upload, which the online Space handles on Hugging Face's servers, and a local copy downloads the Space's files - Not for: the source lists no exclusions, but the scores are not a universal measure of picture quality ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/Jannchie/silva-aesthetic-demo - Files: https://huggingface.co/spaces/Jannchie/silva-aesthetic-demo/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [Jannchie/silva-aesthetic-demo on Hugging Face](https://huggingface.co/spaces/Jannchie/silva-aesthetic-demo) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | SILVA Aesthetic Scorer (this page) | 1 | gradio | mit | 2026-09-03 | | [Open VLM Leaderboard](https://mindket.com/p/9382a913-7563-4967-88b1-0f2458cb00bc) | 1,034 | gradio | apache-2.0 | 2026-03-11 | | [Face Swap](https://mindket.com/p/92787455-1f9f-466a-b574-da22b25d6e0a) | 808 | gradio | cc-by-nc-sa-4.0 | 2024-05-22 | | [TTS Spaces Arena](https://mindket.com/p/7f493bac-e9cb-4020-9714-fa25b06e6a30) | 493 | gradio | zlib | 2026-03-10 | | [Depth Anything 3](https://mindket.com/p/c1e531c5-63e1-4315-a529-7fcae3cb7374) | 490 | gradio | cc-by-nc-4.0 | 2025-11-20 | | [BLIP](https://mindket.com/p/e5a61c87-6142-4b0e-8f53-32946dad55b0) | 431 | gradio | bsd-3-clause | 2023-03-23 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-09-03 - First published: 2026-06-04 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Jannchie/silva-aesthetic-demo on Hugging Face](https://huggingface.co/spaces/Jannchie/silva-aesthetic-demo) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/1888c4ca-b0b2-4e59-8fb7-d2f8d689ed1c) - [Its page on Mindket](https://mindket.com/p/1888c4ca-b0b2-4e59-8fb7-d2f8d689ed1c)