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Learn how to classify natural scene images using PyTorch! This project uses the Intel Image Classification Dataset and trains a neural network model to classify images. Follow along with code and step-by-step instructions.

Classifying Intel Natural Scenes Images using PyTorch

nature scene

This project is the result of the knowledge acquired during the course Deep Learning with PyTorch: Zero to GANs offered by Jovian.ai.

For this project, was chosen the open Intel Image Classification Dataset which contains images of nature scenes sperated in 6 categories. The main goal of the project is to define, train and test a neural network model for classifying images.

System Setup

Let's begin by installing and importing the required libraries.

Requirement already up-to-date: opendatasets in /usr/local/lib/python3.6/dist-packages (0.1.10) Requirement already satisfied, skipping upgrade: tqdm in /usr/local/lib/python3.6/dist-packages (from opendatasets) (4.41.1) Requirement already satisfied, skipping upgrade: kaggle in /usr/local/lib/python3.6/dist-packages (from opendatasets) (1.5.10) Requirement already satisfied, skipping upgrade: click in /usr/local/lib/python3.6/dist-packages (from opendatasets) (7.1.2) Requirement already satisfied, skipping upgrade: requests in /usr/local/lib/python3.6/dist-packages (from kaggle->opendatasets) (2.23.0) Requirement already satisfied, skipping upgrade: urllib3 in /usr/local/lib/python3.6/dist-packages (from kaggle->opendatasets) (1.24.3) Requirement already satisfied, skipping upgrade: certifi in /usr/local/lib/python3.6/dist-packages (from kaggle->opendatasets) (2020.12.5) Requirement already satisfied, skipping upgrade: python-slugify in /usr/local/lib/python3.6/dist-packages (from kaggle->opendatasets) (4.0.1) Requirement already satisfied, skipping upgrade: python-dateutil in /usr/local/lib/python3.6/dist-packages (from kaggle->opendatasets) (2.8.1) Requirement already satisfied, skipping upgrade: six>=1.10 in /usr/local/lib/python3.6/dist-packages (from kaggle->opendatasets) (1.15.0) Requirement already satisfied, skipping upgrade: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->kaggle->opendatasets) (3.0.4) Requirement already satisfied, skipping upgrade: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->kaggle->opendatasets) (2.10) Requirement already satisfied, skipping upgrade: text-unidecode>=1.3 in /usr/local/lib/python3.6/dist-packages (from python-slugify->kaggle->opendatasets) (1.3)