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Created 3 years ago
Identify fruit species using Deep Learning and Pytorch
TODO - Introduction
We are going to do it in the following steps:
- Pick a dataset
- Download the dataset
- Import the dataset using Pytorch
- Explore the dataset
- Prepare the dataset for traning
- Move the dataset to the GPU
- Define NN
- Train the Model
- Make predictions on sample images
it's cool than lets go develop this model
Dataset
I chose this dataset because it's a bit simple. In this way, I will be able to try many methods for different stages.
Download the Dataset
Using Opendatasets and download the dataset from https://www.kaggle.com/moltean/fruits .
pip install opendatasets --upgrade --quiet Note: you may need to restart the kernel to use updated packages.
WARNING: The script slugify.exe is installed in 'C:\Users\AlptheLightning\anaconda3\Scripts' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
WARNING: The script kaggle.exe is installed in 'C:\Users\AlptheLightning\anaconda3\Scripts' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.