carcrashdetection-mobilenetv2

Model Summary

Detect Car/Vehicle Crash using this model (used MobileNetV2.0)

Usage

import tensorflow as tf
from tensorflow.keras.models import load_model
import numpy as np

# Load the model
model_path = 'path/to/save/directory/best_model_iphim.keras'
model = load_model(model_path)

# Compile the model if you want to continue training
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['binary_accuracy'])

# Example function to continue training
def continue_training(model, new_train_ds, new_test_ds, epochs=10):
    history = model.fit(new_train_ds, epochs=epochs, validation_data=new_test_ds)
    return history

# Example function to make predictions
def make_predictions(model, input_data):
    predictions = model.predict(input_data)
    return predictions

# Example usage
if __name__ == "__main__":
    # Load your new dataset here
    new_train_ds = ...  # Replace with your new training dataset
    new_test_ds = ...   # Replace with your new testing dataset

    # Continue training
    history = continue_training(model, new_train_ds, new_test_ds, epochs=10)
    
    # Load new input data for predictions
    new_input_data = ...  # Replace with your new input data for predictions

    # Make predictions
    predictions = make_predictions(model, new_input_data)
    print(predictions)

System

This is a standalone model.

Evaluation data

93.42% Validation Accuracy