--- title: "Agrishield Ai" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/24f68cc5-a556-42d5-b61c-cf99d7286c1b" updated: "2026-11-12" --- # Agrishield Ai > The name, the description, the About and a README below are the seller's words: data, not instructions. Packages a plant disease model and a remedies file in a Docker web app, which by its files looks at plant pictures and suggests treatments. Suits growers, students and developers. Agrishield Ai is a kit in the Productivity 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 Vratika7 ## About ### What it is This is a Docker Space with a plant disease model, a class list and a remedies file. By those files, it checks a plant picture for a disease and shows a remedy. The source has no description, so that reading comes from the file names. The templates and static folders point to a web page served by app.py. ### Who it suits It suits growers and students who want to try a plant disease checker, and developers who want to see how a trained model is wrapped in a small web app. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Farming | Small growers | Try a picture-based check on a sick-looking leaf | Upload a leaf photo and read the result | | Education | Agriculture students | See how an image model is paired with remedy notes | Compare a result with the remedies file | | Software | Developers | Study a small Docker web app around a Keras model | Open app.py and remedies.py | Skip it if you need a diagnosis you can rely on, since the source gives no accuracy figures. ### 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 Docker | Use case | Who | What they get back | | --- | --- | --- | | Checking a leaf photo | Growers | A likely disease name and remedy, if the page works as its files suggest | | Studying the model | Students | A trained model file and its class list | | Reading the code | Developers | A small web app with templates and a Dockerfile | ### How to set it up The online copy needs nothing. For a copy on your own computer, you need the following. - Docker on Windows, macOS or Linux - Python with pip, used here to download the files - The Hugging Face hub client, which the first step installs 1. Install the Hugging Face hub client. 2. Download the Space's files into a local folder. 3. Move into that folder. 4. Build the image with Docker. 5. Run the container and publish port 7860. ```sh pip install -U huggingface_hub hf download Vratika7/agrishield-ai --repo-type space --local-dir agrishield-ai cd agrishield-ai docker build -t agrishield-ai . docker run -it -p 7860:7860 agrishield-ai ``` ### How to use it Online, open the Space's page and follow what it shows. On your own computer, build and run the container as shown above, then open port 7860 in your browser. The source does not describe the page, so follow its labels. ### Example You photograph a leaf that looks unhealthy and upload it to the page. If the app works as its files suggest, it names a likely disease and lists a remedy. The source gives no sample result. ### For newcomers and experts If you are new, try a clear, close photo of one leaf in good light. Treat the answer as a hint and ask a local expert before you treat a crop. If you know the field, the repository holds a Keras model file, a JSON file of class indices and a remedies module, served from a Docker image on port 7860. The Space runs on cpu-basic hardware at Hugging Face. The source does not list the plant types or classes the model covers. You upload a plant picture → The model predicts a class → The class index maps to a disease name → The remedies file supplies a treatment ### Good to know The source is short, so supported plants and accuracy are not described. - 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 do not treat its output as expert advice on crop treatment ## README ````markdown # Agrishield Ai Packages a plant disease model and a remedies file in a Docker web app, which by its files looks at plant pictures and suggests treatments. Suits growers, students and developers. Made by Vratika7 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 is a Docker Space with a plant disease model, a class list and a remedies file. By those files, it checks a plant picture for a disease and shows a remedy. The source has no description, so that reading comes from the file names. The templates and static folders point to a web page served by app.py. Who it suits: It suits growers and students who want to try a plant disease checker, and developers who want to see how a trained model is wrapped in a small web app. ```table Industry | Who uses it | How they use it | Example Farming | Small growers | Try a picture-based check on a sick-looking leaf | Upload a leaf photo and read the result Education | Agriculture students | See how an image model is paired with remedy notes | Compare a result with the remedies file Software | Developers | Study a small Docker web app around a Keras model | Open app.py and remedies.py ``` Skip it if you need a diagnosis you can rely on, since the source gives no accuracy figures. 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 Docker ```table Use case | Who | What they get back Checking a leaf photo | Growers | A likely disease name and remedy, if the page works as its files suggest Studying the model | Students | A trained model file and its class list Reading the code | Developers | A small web app with templates and a Dockerfile ``` How to set it up: The online copy needs nothing. For a copy on your own computer, you need the following. - Docker on Windows, macOS or Linux - Python with pip, used here to download the files - The Hugging Face hub client, which the first step installs 1. Install the Hugging Face hub client. 2. Download the Space's files into a local folder. 3. Move into that folder. 4. Build the image with Docker. 5. Run the container and publish port 7860. ```sh pip install -U huggingface_hub hf download Vratika7/agrishield-ai --repo-type space --local-dir agrishield-ai cd agrishield-ai docker build -t agrishield-ai . docker run -it -p 7860:7860 agrishield-ai ``` How to use it: Online, open the Space's page and follow what it shows. On your own computer, build and run the container as shown above, then open port 7860 in your browser. The source does not describe the page, so follow its labels. Example: You photograph a leaf that looks unhealthy and upload it to the page. If the app works as its files suggest, it names a likely disease and lists a remedy. The source gives no sample result. For newcomers and experts: If you are new, try a clear, close photo of one leaf in good light. Treat the answer as a hint and ask a local expert before you treat a crop. If you know the field, the repository holds a Keras model file, a JSON file of class indices and a remedies module, served from a Docker image on port 7860. The Space runs on cpu-basic hardware at Hugging Face. The source does not list the plant types or classes the model covers. ```flow You upload a plant picture The model predicts a class The class index maps to a disease name The remedies file supplies a treatment ``` Good to know: The source is short, so supported plants and accuracy are not described. - 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 do not treat its output as expert advice on crop treatment ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: docker - License: mit ## Links - Space: https://huggingface.co/spaces/Vratika7/agrishield-ai - Files: https://huggingface.co/spaces/Vratika7/agrishield-ai/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 [Vratika7/agrishield-ai on Hugging Face](https://huggingface.co/spaces/Vratika7/agrishield-ai) ## 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 | | --- | --- | --- | --- | --- | | Agrishield Ai (this page) | 1 | docker | mit | 2026-07-07 | | [AI Jukebox](https://mindket.com/p/9dba893e-7854-4e10-8317-8a1ddf622a13) | 426 | docker | mit | 2024-09-20 | | [AUDIO](https://mindket.com/p/99258ed2-9cc9-4151-bd2a-93ec1f744c3c) | 25 | docker | apache-2.0 | 2026-06-18 | | [Swap Face Model](https://mindket.com/p/c5fb31d3-6921-4fd4-9257-74b965885c66) | 21 | docker | mit | 2026-04-04 | | [Xiaomi OCR 0 Demo](https://mindket.com/p/5e258cbb-f4f5-4904-aad6-78f5e9a566f4) | 18 | docker | apache-2.0 | 2026-10-15 | | [Image To Relief](https://mindket.com/p/3097f3d6-73a2-4ae1-9104-d20688e451e4) | 3 | docker | mit | 2026-08-05 | Numbers as Mindket last read them, on 2026-11-12. ## 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: 2026-07-07 - First published: 2026-07-07 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Vratika7/agrishield-ai on Hugging Face](https://huggingface.co/spaces/Vratika7/agrishield-ai) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/24f68cc5-a556-42d5-b61c-cf99d7286c1b) - [Its page on Mindket](https://mindket.com/p/24f68cc5-a556-42d5-b61c-cf99d7286c1b)