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A system to alert farmers of the Crop Vandalism and aid to fencing destroy. The detection works at far distance and send sms and call to the concerned farmer to take an action before an unseen incident happens.

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vishnoitanuj/Crop-Vandalism

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PROBLEM STATEMENT

Crop Vandalism by animals, namely wild boar, nilgai, monkeys and other wild animals. Animals visit the farms at time unknown. The unavailability of any patrolling, each yaer causes around 30-35% of crop losses to the farmers. High level fencing is too expensive and not durable. Treck Location: Grambharti, Ahmedabad, Gujrat.

INTRODUCTION

We present an Neural Network Solution to the above problem. The software uses image recognisation and convulation networks to detects the things its capturing live from an external capturing, here we have used a web camera patrolling the field using a rover. The precision can further be improved by using a 360 degree view camera.

PRE-REQUISITES

TENSORFLOW: GOOGLE DEEP LEARNING MODULE

DARKFLOW

DARKET

Apart from this we recommend a GPU based system(preferably NIVIDEA with CUDA installed) for smooth functioning of the project.

TENSOR FLOW INSTALLATION

Follow the official documentation at: here

DARKFLOW INSTALLTION

Dependencies : Python3, tensorflow 1.0, numpy, opencv 3.

Install Cython using pip install Cython (if not installed)

You can choose one of the following three ways to get started with darkflow.

  1. Just build the Cython extensions in place. NOTE: If installing this way you will have to use ./flow in the cloned darkflow directory instead of flow as darkflow is not installed globally.

    python3 setup.py build_ext --inplace
    
  2. Let pip install darkflow globally in dev mode (still globally accessible, but changes to the code immediately take effect)

    pip install -e .
    
  3. Install with pip globally

    pip install .
    
  4. Update

DARKNET INSTALLTION

Dependencies : Python3, opencv 3.

Follow the steps to get started with darknet.

  1. Clone the repository using the following command.

    git clone https://github.com/pjreddie/darknet
    
  2. cd darknet

  3. make

  4. Update

Testing the model.

  1. Get a pre-trained model using the following command.

    wget https://pjreddie.com/media/files/yolo.weights
    
  2. Run the detector.

    ./darknet detect cfg/yolo.cfg yolo.weights data/dog.jpg
    

Setting Up directories

Copy the darkflow installation into the darknet folder. Create a bin folder in the darknet and add the yolo.weights into it. You are good to go sweetheart!

DEVELOPERS

SAI SIDDARTHA MARAM TANUJ VISHNOI SACHIN PANDEY

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A system to alert farmers of the Crop Vandalism and aid to fencing destroy. The detection works at far distance and send sms and call to the concerned farmer to take an action before an unseen incident happens.

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