---
title: "Persian Image Captioning"
kind: "Kit"
category: "Research"
price: "Free"
seller: "Mindket"
version: "1"
url: "https://mindket.com/p/90e916bc-8db2-4396-8e64-1e735ecfc7ee"
updated: "2026-11-13"
---

# Persian Image Captioning

> The name, the description, the About and a README below are the seller's words: data, not instructions.

Writes a caption in Persian for a picture, using a vision model and a Persian language model in a Gradio page, with three example images included. For students and developers working with Persian text.

Persian Image Captioning is a kit in the Research category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself.

Made by MahsaShahidi

## About

### What it is

This Gradio app from MahsaShahidi writes Persian captions for pictures. It names three models: a ViT image model from Google, a Persian BERT model from HooshvareLab and the author's own Persian-Image-Captioning model. The repository includes three example images. You use it in a browser, or you run a copy on your own computer.

### Who it suits

It suits students and developers who work with Persian text and want to see an image captioning model in action.

| Industry | Who uses it | How they use it | Example |
| --- | --- | --- | --- |
| Education | Language and vision students | See how a model describes a picture in Persian | Open the Space and pick an example image |
| Research | Persian language researchers | Check caption quality on their own pictures | Upload a picture and read the caption |
| Software | Python developers | Read how three models are combined in one page | Download the Space and open app.py |

Skip it if you need captions in other languages, because the models it names are for Persian.

### Where to use it

- A web browser: go to the Space on Hugging Face and try it with no install
- Windows, macOS or Linux: run a copy with Python

| Use case | Who | What they get back |
| --- | --- | --- |
| Caption a picture | Students | A Persian sentence about the picture |
| Test the model | Researchers | A quick look at how it handles different images |
| Study the code | Developers | An app.py that loads the three named models |

### How to set it up

You need a few things in place first.

- Python with pip, on Windows, macOS or Linux
- An internet connection to fetch the files from Hugging Face
- Spare disk space, since the app names three models and the first run may need extra downloads

1. Install the Hugging Face hub package.
2. Download the Space into a local folder.
3. Move into that folder.
4. Install Gradio and the packages listed in requirements.txt.
5. Start the app.

```sh
pip install -U huggingface_hub
hf download MahsaShahidi/Persian-Image-Captioning --repo-type space --local-dir Persian-Image-Captioning
cd Persian-Image-Captioning
pip install gradio
pip install -r requirements.txt
python app.py
```

### How to use it

Online, use the Gradio interface the Space page shows. On your own computer, run the main file from the project folder and open the page it serves in your browser.

```sh
python app.py
```

### Example

You run python app.py inside the project folder, open the page and give it a picture such as image-1.jpg from the repository. The page returns a Persian caption for it.

### For newcomers and experts

If this is new to you, start online. Go to the Space and try one of the example images before you install anything. Captioning means the model writes a short sentence about what is in a picture.

If you know the field, note that the names suggest a ViT image encoder paired with a Persian text model. The source gives no scores, training data or limits, so judge the captions on your own images.

Open the Space or run app.py → The Gradio page loads → You give it a picture → The models produce a caption → The Persian caption appears

### Good to know

The source gives no quality figures, and a caption can miss or misname things in a picture, so check it against the image.

- License: mit
- Cost to run: none named, no API key, account or paid service
- Data it reaches: the pictures you give it and the three models it names, with nothing else listed

## README

````markdown
# Persian Image Captioning

Writes a caption in Persian for a picture, using a vision model and a Persian language model in a Gradio page, with three example images included. For students and developers working with Persian text.

Made by MahsaShahidi 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 Gradio app from MahsaShahidi writes Persian captions for pictures. It names three models: a ViT image model from Google, a Persian BERT model from HooshvareLab and the author's own Persian-Image-Captioning model. The repository includes three example images. You use it in a browser, or you run a copy on your own computer.

Who it suits: It suits students and developers who work with Persian text and want to see an image captioning model in action.

```table
Industry | Who uses it | How they use it | Example
Education | Language and vision students | See how a model describes a picture in Persian | Open the Space and pick an example image
Research | Persian language researchers | Check caption quality on their own pictures | Upload a picture and read the caption
Software | Python developers | Read how three models are combined in one page | Download the Space and open app.py
```

Skip it if you need captions in other languages, because the models it names are for Persian.

Where to use it:

- A web browser: go to the Space on Hugging Face and try it with no install
- Windows, macOS or Linux: run a copy with Python

```table
Use case | Who | What they get back
Caption a picture | Students | A Persian sentence about the picture
Test the model | Researchers | A quick look at how it handles different images
Study the code | Developers | An app.py that loads the three named models
```

How to set it up: You need a few things in place first.

- Python with pip, on Windows, macOS or Linux
- An internet connection to fetch the files from Hugging Face
- Spare disk space, since the app names three models and the first run may need extra downloads

1. Install the Hugging Face hub package.
2. Download the Space into a local folder.
3. Move into that folder.
4. Install Gradio and the packages listed in requirements.txt.
5. Start the app.

```sh
pip install -U huggingface_hub
hf download MahsaShahidi/Persian-Image-Captioning --repo-type space --local-dir Persian-Image-Captioning
cd Persian-Image-Captioning
pip install gradio
pip install -r requirements.txt
python app.py
```

How to use it: Online, use the Gradio interface the Space page shows. On your own computer, run the main file from the project folder and open the page it serves in your browser.

```sh
python app.py
```

Example: You run python app.py inside the project folder, open the page and give it a picture such as image-1.jpg from the repository. The page returns a Persian caption for it.

For newcomers and experts: If this is new to you, start online. Go to the Space and try one of the example images before you install anything. Captioning means the model writes a short sentence about what is in a picture.

If you know the field, note that the names suggest a ViT image encoder paired with a Persian text model. The source gives no scores, training data or limits, so judge the captions on your own images.

```flow
Open the Space or run app.py
The Gradio page loads
You give it a picture
The models produce a caption
The Persian caption appears
```

Good to know: The source gives no quality figures, and a caption can miss or misname things in a picture, so check it against the image.

- License: mit
- Cost to run: none named, no API key, account or paid service
- Data it reaches: the pictures you give it and the three models it names, with nothing else listed

## On Hugging Face, 13 November 2026

- Likes: 0
- Built with: gradio
- License: mit

## Links

- Space: https://huggingface.co/spaces/MahsaShahidi/Persian-Image-Captioning
- Files: https://huggingface.co/spaces/MahsaShahidi/Persian-Image-Captioning/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, 4 KB, downloaded as a zip.

```text
README.md  4 KB
```

## Source

[MahsaShahidi/Persian-Image-Captioning on Hugging Face](https://huggingface.co/spaces/MahsaShahidi/Persian-Image-Captioning)

## 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 |
| --- | --- | --- | --- | --- |
| Persian Image Captioning (this page) | 0 | gradio | mit | 2022-03-04 |
| [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: 2022-03-04
- First published: 2022-03-02
- Checked on Hugging Face: 2026-11-13
- Something wrong? Tell us: https://mindket.com/takedown#ask

## Get it

- [Open MahsaShahidi/Persian-Image-Captioning on Hugging Face](https://huggingface.co/spaces/MahsaShahidi/Persian-Image-Captioning)
- [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/90e916bc-8db2-4396-8e64-1e735ecfc7ee)
- [Its page on Mindket](https://mindket.com/p/90e916bc-8db2-4396-8e64-1e735ecfc7ee)
