mediapipe_model_maker.image_classifier.SupportedModels

Image classifier model supported by model maker.

EFFICIENTNET_LITE0 <SupportedModels.EFFICIENTNET_LITE0: functools.partial(<class 'mediapipe_model_maker.python.vision.image_classifier.model_spec.ModelSpec'>, uri='https://tfhub.dev/tensorflow/efficientnet/lite0/feature-vector/2', name='efficientnet_lite0')>
EFFICIENTNET_LITE2 <SupportedModels.EFFICIENTNET_LITE2: functools.partial(<class 'mediapipe_model_maker.python.vision.image_classifier.model_spec.ModelSpec'>, uri='https://tfhub.dev/tensorflow/efficientnet/lite2/feature-vector/2', input_image_shape=[260, 260], name='efficientnet_lite2')>
EFFICIENTNET_LITE4 <SupportedModels.EFFICIENTNET_LITE4: functools.partial(<class 'mediapipe_model_maker.python.vision.image_classifier.model_spec.ModelSpec'>, uri='https://tfhub.dev/tensorflow/efficientnet/lite4/feature-vector/2', input_image_shape=[300, 300], name='efficientnet_lite4')>
MOBILENET_V2 <SupportedModels.MOBILENET_V2: functools.partial(<class 'mediapipe_model_maker.python.vision.image_classifier.model_spec.ModelSpec'>, uri='https://tfhub.dev/google/tf2-preview/mobilenet_v2/feature_vector/4', name='mobilenet_v2')>
MOBILENET_V2_KERAS <SupportedModels.MOBILENET_V2_KERAS: functools.partial(<class 'mediapipe_model_maker.python.vision.image_classifier.model_spec.ModelSpec'>, uri=None, name='mobilenet_v2_keras', mean_rgb=[127.5], stddev_rgb=[128.0])>