Lagos Public Transportation Classification witth AI

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The aim of this project is to build an application that can correctly classify four main types of public transportation in Lagos state, Nigeria. These vehicles include

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• Bus Rapid Transit (BRT)

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• Danfo / Bus

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• Keke Napep / Keke Maruwa / Keke Tricycle

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• Okada Bike / Motorcycle

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The data was scraped using the Google Image Scraper tool to extract all the images from Google

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• Extracted the data

• Arranged and label the data

• Performed various Data Preprocessing techniques such as converting images into tensors and feature normalization/scaling

• Used Convolutional Neural Networks (CNN), Data Augmentation and Transfer Learning / Pretrained Model to achieved best performance

• Tuned MobileNet V2 achieved best performance with 97% traing accuracy and 95.6% test accuracy

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Model Performamce

Accuracy with Confusion Matrix was used to evaluate performance. Data Augmentated CNN performed worse than Base CNN and Pre-trained Model

• Base CNN
  • Training Accuracy : 95.7%
  • Testing Accuracy : 69.7%
  • Confusion Matrix

• Data Augmentation + Base CNN
  • Training Accuracy : 60%
  • Testing Accuracy : 66.9%
  • Confusion Matrix

• Tuned MobileNet V2
  • Training Accuracy : 99%
  • Testing Accuracy : 93.5%
  • Confusion Matrix

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Model Deployment

The final model with the best score was deployed on a web application built with Streamlit

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