From 3e6cd5d2bf403299886bfdcb77079d92c2d794b5 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Mon, 19 Dec 2022 11:54:57 -0800 Subject: [PATCH] Add support for customizing gesture recognizer layers PiperOrigin-RevId: 496456160 --- .../gesture_recognizer/gesture_recognizer.py | 15 +++++++---- .../gesture_recognizer_test.py | 26 +++++++++++++++++++ .../gesture_recognizer/model_options.py | 6 +++++ 3 files changed, 42 insertions(+), 5 deletions(-) diff --git a/mediapipe/model_maker/python/vision/gesture_recognizer/gesture_recognizer.py b/mediapipe/model_maker/python/vision/gesture_recognizer/gesture_recognizer.py index f297d8640..556d2fcd7 100644 --- a/mediapipe/model_maker/python/vision/gesture_recognizer/gesture_recognizer.py +++ b/mediapipe/model_maker/python/vision/gesture_recognizer/gesture_recognizer.py @@ -173,15 +173,20 @@ class GestureRecognizer(classifier.Classifier): batch_size=None, dtype=tf.float32, name='hand_embedding') - - x = tf.keras.layers.BatchNormalization()(inputs) - x = tf.keras.layers.ReLU()(x) + x = inputs dropout_rate = self._model_options.dropout_rate - x = tf.keras.layers.Dropout(rate=dropout_rate, name='dropout')(x) + for i, width in enumerate(self._model_options.layer_widths): + x = tf.keras.layers.BatchNormalization()(x) + x = tf.keras.layers.ReLU()(x) + x = tf.keras.layers.Dropout(rate=dropout_rate)(x) + x = tf.keras.layers.Dense(width, name=f'custom_gesture_recognizer_{i}')(x) + x = tf.keras.layers.BatchNormalization()(x) + x = tf.keras.layers.ReLU()(x) + x = tf.keras.layers.Dropout(rate=dropout_rate)(x) outputs = tf.keras.layers.Dense( self._num_classes, activation='softmax', - name='custom_gesture_recognizer')( + name='custom_gesture_recognizer_out')( x) self._model = tf.keras.Model(inputs=inputs, outputs=outputs) diff --git a/mediapipe/model_maker/python/vision/gesture_recognizer/gesture_recognizer_test.py b/mediapipe/model_maker/python/vision/gesture_recognizer/gesture_recognizer_test.py index 280fc6a82..08fda4fea 100644 --- a/mediapipe/model_maker/python/vision/gesture_recognizer/gesture_recognizer_test.py +++ b/mediapipe/model_maker/python/vision/gesture_recognizer/gesture_recognizer_test.py @@ -60,6 +60,32 @@ class GestureRecognizerTest(tf.test.TestCase): self._test_accuracy(model) + @unittest_mock.patch.object( + tf.keras.layers, 'Dense', wraps=tf.keras.layers.Dense) + def test_gesture_recognizer_model_layer_widths(self, mock_dense): + layer_widths = [64, 32] + model_options = gesture_recognizer.ModelOptions(layer_widths=layer_widths) + hparams = gesture_recognizer.HParams( + export_dir=tempfile.mkdtemp(), epochs=2) + gesture_recognizer_options = gesture_recognizer.GestureRecognizerOptions( + model_options=model_options, hparams=hparams) + model = gesture_recognizer.GestureRecognizer.create( + train_data=self._train_data, + validation_data=self._validation_data, + options=gesture_recognizer_options) + expected_calls = [ + unittest_mock.call(w, name=f'custom_gesture_recognizer_{i}') + for i, w in enumerate(layer_widths) + ] + expected_calls.append( + unittest_mock.call( + len(self._train_data.label_names), + activation='softmax', + name='custom_gesture_recognizer_out')) + self.assertLen(mock_dense.call_args_list, len(expected_calls)) + mock_dense.assert_has_calls(expected_calls) + self._test_accuracy(model) + def test_export_gesture_recognizer_model(self): model_options = gesture_recognizer.ModelOptions() hparams = gesture_recognizer.HParams( diff --git a/mediapipe/model_maker/python/vision/gesture_recognizer/model_options.py b/mediapipe/model_maker/python/vision/gesture_recognizer/model_options.py index 79a84c792..1870437d4 100644 --- a/mediapipe/model_maker/python/vision/gesture_recognizer/model_options.py +++ b/mediapipe/model_maker/python/vision/gesture_recognizer/model_options.py @@ -14,6 +14,7 @@ """Configurable model options for gesture recognizer models.""" import dataclasses +from typing import List @dataclasses.dataclass @@ -23,5 +24,10 @@ class GestureRecognizerModelOptions: Attributes: dropout_rate: The fraction of the input units to drop, used in dropout layer. + layer_widths: A list of hidden layer widths for the gesture model. Each + element in the list will create a new hidden layer with the specified + width. The hidden layers are separated with BatchNorm, Dropout, and ReLU. + Defaults to an empty list(no hidden layers). """ dropout_rate: float = 0.05 + layer_widths: List[int] = dataclasses.field(default_factory=list)