Added a guide for running crop disease detection part in Docker as well as standalone.
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# models/
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This directory holds code for AI model used for disease detection in crops.
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---
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## Requirements
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- `${FRONTEND_URI}` is used in [server.js](./models/server.js). This should be passed when creating the Docker container as an environment variable.
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- `${FRONTEND_URI}` is essentially the URI where the frontend is hosted.
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## Docker Run
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It is recommended that you use the [docker-compose.yaml](./docker-compose.yaml) file which creates all the required containers, however if you wish to run only the "models" part of this project in Docker run the following docker command.
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```shell
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docker run -tid \
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--name cropcompass-model \
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--restart always \
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-p "8081:8081" \
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-e "FRONTEND_URI=<frontend_uri>" \
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kshitijka/cropcompass-model:<version>
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```
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> [!NOTE]
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> Replace `<frontend_uri>` with the actual frontend URI such as http://localhost:3000 & `<version>` with an actual version number such as `1.1.0`.
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## Manual Run
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To run only the "models" part of this project, you will have to create a python virtual environement, followed by installing all the dependencies and then running the [server.js](./models/server.js) file using node.
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1. Install required packages (for Debian based systems):
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```shell
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sudo apt install python3 python3-pip python3.11-venv
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```
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2. Create a virtual environment:
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```shell
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python3 -m venv .
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```
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> [!NOTE]
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> Assuming you're in the `models/` directory.
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3. Install required packages using `pip`:
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```shell
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pip install -r requirements.txt
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```
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4. Run [server.js](./models/server.js):
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```shell
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node server.js
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```
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> [!NOTE]
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> Assuming you already have `node` installed on your system.
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---
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