Cropification

Cropification is a web-based Agriculture Facilitation System, that provides object detection using YOLOv3 and trained on custom dataset(Crop RGB).

It's implemented using django framework and python libraries.

Dependencies

• Django
• Python
• OpenCV
• PostgreSQL

You also need to download the yolo6000.weights file and place it in the "yolo_v3" directory.

You can download the weights from the following link (this action may require permission):

https://drive.google.com/open?id=1-0jFXFO8xIqhgio6XgPjmmGDqIQVlfmx

Usage

Firstly, you need to create a database using postgresql, then change DATABASES values with your credentials in setting.py file. Then to activate enviormental variable in .env file you need to make a virtualenviorment with pipenv and to activate it, run following command in your cmd:

pipenv shell

To install all dependencies:

pip install -r requirements.txt

To run server:

python manage.py collectstatic
python manage.py makemigrations
python manage.py migrate
python manage.py runserver

Server will start running on localhost(127.0.0.1/8000).

Inorder to use the provided services, you need to signup.

Example

The website also shows the detection output with bounding boxes around the detected objects. There will be no box if the input doesn't contain any object.

Input (Object Detection)

Output (Object Detection)

Input (Vegetation Localization)

Output (Vegetation Localization)

TO-DO

• Make website live using Google App Engine

Contribute

If you want to contribute and/or find any bug, feel free to do a pull request!