AML_Classifying_distracted_drivers

Mandatory assignment for Advanced Machine Learning, ITU Spring 2024

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A Project by:

• Chrisanna K Cornish ccor@itu.dk
• Christian M Hansen chmh@itu.dk

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Data:

The data can be downloaded from Kaggle

Approx 20000 still images from 26 individuals tagged with classes 0-9:

• c0: normal driving
• c1: texting - right
• c2: talking on the phone - right
• c3: texting - left
• c4: talking on the phone - left
• c5: operating the radio
• c6: drinking
• c7: reaching behind
• c8: hair and makeup
• c9: talking to passenger

Classes are approxiamtely balanced.

According to Kaggle 'State Farm set up these experiments in a controlled environment - a truck dragging the car around on the streets - so these "drivers" weren't really driving.'

Central Problem

Image classification using tranfer learning and salience consideration

Models

• VGG16 link to trained model
• ResNet18
• ResNet50

Plan:

• 1. Fine tune a model for binary classification, distracted or not
• 2. Fine tune a model for multiclass classification, according to provided classes.

• We then want to look at what areas the model is focussing on and create some heatmaps to demonstrate this:

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Requirements:

Requirements.txt

Folder structure:

    statefarm_drivers_01.ipynb
    statefarm_drivers_02.ipynb
    statefarm_drivers_02_vgg.ipynb    
    driver_imgs_list.csv
    model
    ├───resnet50_multi_unfreeze_tune_v02.pt
    src
    ├───imgs
    │   ├───test
    │   └───train
    │       ├───c0
    │       ├───c1
    │       ├───c2
    │       ├───c3
    │       ├───c4
    │       ├───c5
    │       ├───c6
    │       ├───c7
    │       ├───c8
    │       └───c9
    ├───train
    │   ├───c0
    │   └───c1
    ├───train_m
    │   ├───c0
    │   ├───c1
    │   ├───c2
    │   ├───c3
    │   ├───c4
    │   ├───c5
    │   ├───c6
    │   ├───c7
    │   ├───c8
    │   └───c9
    ├───val
    │   ├───c0
    │   └───c1
    └───val_m
        ├───c0
        ├───c1
        ├───c2
        ├───c3
        ├───c4
        ├───c5
        ├───c6
        ├───c7
        ├───c8
        └───c9

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