train.py

import numpy as np
import os

from tflite_model_maker.config import ExportFormat, QuantizationConfig
from tflite_model_maker import model_spec
from tflite_model_maker import object_detector

from tflite_support import metadata

import tensorflow as tf
assert tf.__version__.startswith('2')

tf.get_logger().setLevel('ERROR')
from absl import logging
logging.set_verbosity(logging.ERROR)

train_data = object_detector.DataLoader.from_pascal_voc(
    'freedomtech/train',
    'freedomtech/train',
    ['obstacle', 'checkpoint']
)

val_data = object_detector.DataLoader.from_pascal_voc(
    'freedomtech/validate',
    'freedomtech/validate',
    ['obstacle', 'checkpoint']
)

spec = model_spec.get('efficientdet_lite0')

model = object_detector.create(train_data, model_spec=spec, batch_size=4, train_whole_model=True, epochs=50, validation_data=val_data)

result = model.evaluate(val_data)
print("Evaluate result: ", result)

model.export(export_dir='.', tflite_filename='best2.tflite')