How to Build a CNN for classifying garbage using PyTorch?
Introduction
Did you Ever Think of where does all the garbage go after you dump into your dustbin or your local garbage collection unit?
#Never!!
But, If you said Yes then you are the saviors of the universe.
As we all know, The world generates at least 1.3 billion tons of plastic and other solid waste a day, 10 times the amount a century ago, according to World Bank researchers. It is yet too difficult to imagine 1.3 billion tons of waste. That’s nearly 4 million double-decker buses worth of old computer equipment, TVs, stereos and kitchen appliances, stretching to the moon more than 3 times over!!
WE ALL KNOW HOW TO CHANGE THE EARTH BUT WE DONT KNOW WHEN AND WHO WILL START IT.
#Problem: The main issue with the garbage wastage is an improper classification which leads to a mix up of other waste which will lead to other pollution.
#Solution: To solve this issue in a better way we are going to work on this data set which will help us get a better view of the scenario.
Basic prerequisite: High School Math, Python, and Pytorch
Garbage Classification
We are going to classify garbage based on six different classes using ResNet50 to do the work.
Select the below notebook to get into the model and tune out other hyperparameters to increase the accuracy.
Notebook- Garbage-Classification-Notebook
If you feel like you are lost, please check out the resources and try to get to understand in an intuitive way.
