anaksor-ocr
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Reads Khmer and English text from documents, receipts and photos of signs, using a detector for text lines and a recogniser for each line. Suits developers who…
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 . Download it on this page, a zip of its files. Nothing in it runs by itself.
pip install -U huggingface_hub hf download Vratika7/agrishield-ai --repo-type space --local-dir agrishield-ai cd agrishield-ai
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.
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.
| 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 |
The online copy needs nothing. For a copy on your own computer, you need the following.
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
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.
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.
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.
The source is short, so supported plants and accuracy are not described.
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.
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:
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.
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.
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.
README.md 4 KB
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