AgriTech
An app with deep learning models to predict compatibility using soil images and also assists in minimising loss at harvest time by predicting prices.
Install / Use
/learn @vermashresth/AgriTechREADME
AgriTech
An app with deep learning model to predict compatibility using soil images and also assists in minimising loss at harvest time by predicting prices. Developed at IndiaHacks 2017
Requirements
- Beautiful Soup
- Tensorflow
- Numpy
- Pandas
How To Use
- First scrape crop prices data from agmarknet.gov.in using python web scraping website beautiful soup.
python scrap_crops.py
This will give output csv file for different states, crops and over different months.
- To predict prices of crops after harvesting period, run
python ./scripts/hack1.py
This uses a random forest regressor to predict prices.
- Train an inceptionv3 model inn tensorflow using transfer learning to classify soil type by image.
python ./scripts/retrain.py --imagedir <pathtoimages>
- Complete pipeline output\ Get best crop to grow from soil image taking into consideration price prediction after harvest time.
python ./scripts/label_image.py
