How do i optimize and deploy a deep learning model on an ESP32? still based on my project image recognition system that can analyze images of tissue samples, identify malignancies, and predict possible symptoms and causes. Am currently trying to deploy the trained model on the ESP32 for real-time inference.
But

    MemoryError: Model size exceeds available memory
    

How do I go about resolving this

    import tensorflow as tf
    from tensorflow.keras.models import load_model
    import tensorflow.lite as tflite

    
    model = load_model('malignant_tissue_model.h5')

   
    converter = tf.lite.TFLiteConverter.from_keras_model(model)
    tflite_model = converter.convert()

   
    with open('malignant_tissue_model.tflite', 'wb') as f:
        f.write(tflite_model)