hadjerseddik / Crop_classification

Training & evaluating different experiments using Deep Learning & CNN for plant classification topic

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Crop_classification

This is a source code that tests 8 experiments of 4 datasets in the aim of classifying plants to thier crop classes

By SEDDIK Hadjer & ABLA Hanane

Supervised by Dr BRAHIMI Mohamed

Requirements :

Dependencies must called before writting your scripts :

Tensorflow , Keras , Keras_applications, Keras_models, numpy,os,pandas

--> find more details about the needed librairies in in ' Train/..DataSet/Text_experiments'

How to use !

1- Clone the repository

2- From the train folder you find four different Datasets , choose one

3- Using Google Colab create a new notebook and type your code there , find scripts in ' train/..DataSet/Test_experiments'

4- Find Datasets link in Train/..DataSet/DataSet , import it directly from Google Drive

5- About the models architectures you can use the direct drive link for each model , find it in ' train/..DataSet/Architecture '

6- And here you go ready to train your model

7- Evaluate your test experiments and store the dataframe result and the plots in a drive directory

Licence

You can use any part of this code in your projects

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Training & evaluating different experiments using Deep Learning & CNN for plant classification topic


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