--- title: "Flowers Classification MobileViT" kind: "Kit" category: "Education" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/7289b555-1f7f-4d66-8224-293d355e02b7" updated: "2026-11-13" --- # Flowers Classification MobileViT > The name, the description, the About and a README below are the seller's words: data, not instructions. Identifies flower types in a photo with a small MobileViT model from Keras in a Gradio page, with example images included. For machine learning learners and plant hobbyists. Flowers Classification MobileViT is a kit in the Education 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 keras-io ## About ### What it is This Gradio app classifies flower pictures with a small MobileViT model. The record names one model, mobile-vit-xxs, from the Keras team's keras-io group. An examples folder holds sample pictures to try. ### Who it suits It suits machine learning learners who want to see a compact vision model at work. Plant hobbyists can get a quick label for a flower photo, and developers get a small Gradio example. The record gives no list of flower classes or accuracy figures. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Education | Machine learning students | See a compact vision transformer classify images | Run one of the example pictures | | Gardening | Plant hobbyists | Get a quick guess at a flower's type | Try a photo of a flower you own | | Software | Python developers | Read a small Gradio demo around a Keras model | Open app.py and requirements.txt | You can skip it if you need a dependable plant identification service. ### Where to use it - A web browser, on the Space's page on Hugging Face - Windows, macOS or Linux with Python, from a downloaded copy | Use case | Who | What they get back | | --- | --- | --- | | Classify a flower photo | Hobbyists | The model's label for the picture | | Try the bundled examples | Learners | A quick sense of how the model behaves | | Reuse as a base | Developers | A small Gradio app around a Keras model | ### How to set it up - Nothing at all if you use the online Space - Python on your computer, only if you run a copy - The packages listed in requirements.txt 1. Open the Space's page in a browser to use it with nothing to install. 2. To run a copy, install the Hugging Face Hub package and download the Space. 3. Move into the new folder, then install Gradio and the listed requirements. 4. Start the app with Python. ```sh pip install -U huggingface_hub hf download keras-io/Flowers-Classification-MobileViT --repo-type space --local-dir Flowers-Classification-MobileViT cd Flowers-Classification-MobileViT pip install gradio pip install -r requirements.txt python app.py ``` ### How to use it Online, open the Space and use the controls on its page. On your own machine, run the main file from the Space folder, then use the page it serves. The example pictures are the quickest way to try it. ```sh python app.py ``` ### Example You open the Space and pick one of the example flower pictures. The app returns the model's label for that flower. The record shows no sample output, so the exact display depends on the page. ### For newcomers and experts An image classifier looks at a photo and picks the label that fits best. Start by opening the Space and running an example picture, then try one of your own. If you know the field, MobileViT mixes convolution with transformer blocks to stay small, and the xxs in the model name points to its smallest size. The record gives no accuracy figures or class list, so check results on your own photos. You pick or upload a flower photo → The Gradio page sends it to app.py → The MobileViT model scores the labels → The page shows the best match ### Good to know - License: cc0-1, as listed on the Space - Cost to run: none named - Data it reaches: the pictures you give it and the model it names - Not for: the record names no exclusions, and it gives no accuracy figures ## README ````markdown # Flowers Classification MobileViT Identifies flower types in a photo with a small MobileViT model from Keras in a Gradio page, with example images included. For machine learning learners and plant hobbyists. Made by keras-io 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 classifies flower pictures with a small MobileViT model. The record names one model, mobile-vit-xxs, from the Keras team's keras-io group. An examples folder holds sample pictures to try. Who it suits: It suits machine learning learners who want to see a compact vision model at work. Plant hobbyists can get a quick label for a flower photo, and developers get a small Gradio example. The record gives no list of flower classes or accuracy figures. ```table Industry | Who uses it | How they use it | Example Education | Machine learning students | See a compact vision transformer classify images | Run one of the example pictures Gardening | Plant hobbyists | Get a quick guess at a flower's type | Try a photo of a flower you own Software | Python developers | Read a small Gradio demo around a Keras model | Open app.py and requirements.txt ``` You can skip it if you need a dependable plant identification service. Where to use it: - A web browser, on the Space's page on Hugging Face - Windows, macOS or Linux with Python, from a downloaded copy ```table Use case | Who | What they get back Classify a flower photo | Hobbyists | The model's label for the picture Try the bundled examples | Learners | A quick sense of how the model behaves Reuse as a base | Developers | A small Gradio app around a Keras model ``` How to set it up: - Nothing at all if you use the online Space - Python on your computer, only if you run a copy - The packages listed in requirements.txt 1. Open the Space's page in a browser to use it with nothing to install. 2. To run a copy, install the Hugging Face Hub package and download the Space. 3. Move into the new folder, then install Gradio and the listed requirements. 4. Start the app with Python. ```sh pip install -U huggingface_hub hf download keras-io/Flowers-Classification-MobileViT --repo-type space --local-dir Flowers-Classification-MobileViT cd Flowers-Classification-MobileViT pip install gradio pip install -r requirements.txt python app.py ``` How to use it: Online, open the Space and use the controls on its page. On your own machine, run the main file from the Space folder, then use the page it serves. The example pictures are the quickest way to try it. ```sh python app.py ``` Example: You open the Space and pick one of the example flower pictures. The app returns the model's label for that flower. The record shows no sample output, so the exact display depends on the page. For newcomers and experts: An image classifier looks at a photo and picks the label that fits best. Start by opening the Space and running an example picture, then try one of your own. If you know the field, MobileViT mixes convolution with transformer blocks to stay small, and the xxs in the model name points to its smallest size. The record gives no accuracy figures or class list, so check results on your own photos. ```flow You pick or upload a flower photo The Gradio page sends it to app.py The MobileViT model scores the labels The page shows the best match ``` Good to know: - License: cc0-1, as listed on the Space - Cost to run: none named - Data it reaches: the pictures you give it and the model it names - Not for: the record names no exclusions, and it gives no accuracy figures ## On Hugging Face, 13 November 2026 - Likes: 4 - Built with: gradio - License: cc0-1.0 ## Links - Space: https://huggingface.co/spaces/keras-io/Flowers-Classification-MobileViT - Files: https://huggingface.co/spaces/keras-io/Flowers-Classification-MobileViT/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 [keras-io/Flowers-Classification-MobileViT on Hugging Face](https://huggingface.co/spaces/keras-io/Flowers-Classification-MobileViT) ## 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 | | --- | --- | --- | --- | --- | | Flowers Classification MobileViT (this page) | 4 | gradio | cc0-1.0 | 2022-02-18 | | [Unit 1 Quiz - AI Agent Fundementals](https://mindket.com/p/1b65056a-a2b2-4179-a81c-bdffa3636205) | 360 | gradio | apache-2.0 | 2025-06-24 | | [Unit 2.1 smolagents Code Quiz](https://mindket.com/p/c9f42604-0003-4117-9a4b-2b785f68ee99) | 63 | gradio | apache-2.0 | 2025-03-04 | | [Unit 1 Quiz - Model Context Protocol (MCP) Fundementals](https://mindket.com/p/f7210665-ca4c-423f-b45d-a1c6fa549eec) | 58 | gradio | apache-2.0 | 2025-06-03 | | [Tamazight Text-to-Speech](https://mindket.com/p/ab94f6a3-34fa-4c03-9fd0-751ff4f282eb) | 41 | gradio | cc-by-4.0 | 2023-11-25 | | [Embedding Draw Challenge](https://mindket.com/p/76690a14-5bc9-4d53-ad3e-d47e7218918f) | 30 | gradio | apache-2.0 | 2026-10-06 | 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: 2022-02-18 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open keras-io/Flowers-Classification-MobileViT on Hugging Face](https://huggingface.co/spaces/keras-io/Flowers-Classification-MobileViT) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/7289b555-1f7f-4d66-8224-293d355e02b7) - [Its page on Mindket](https://mindket.com/p/7289b555-1f7f-4d66-8224-293d355e02b7)