Add an extra op to rescale face stylizer generation output from [-1, 1] to [0, 1].

This conversion is to support running the model on both GPU and CPU.

PiperOrigin-RevId: 528400297

mediapipe/model_maker/python/core/utils/test_util.py

@@ -16,7 +16,8 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-from typing import List, Union
+from typing import Sequence
+from typing import Dict, List, Union
 
 # Dependency imports
 
@@ -94,6 +95,17 @@ def is_same_output(tflite_model: bytearray,
   return np.allclose(lite_output, keras_output, atol=atol)
 
 
+def run_tflite(
+    tflite_filename: str,
+    input_tensors: Union[List[tf.Tensor], Dict[str, tf.Tensor]],
+) -> Union[Sequence[tf.Tensor], tf.Tensor]:
+  """Runs TFLite model inference."""
+  with tf.io.gfile.GFile(tflite_filename, "rb") as f:
+    tflite_model = f.read()
+  lite_runner = model_util.get_lite_runner(tflite_model)
+  return lite_runner.run(input_tensors)
+
+
 def test_tflite(keras_model: tf.keras.Model,
                 tflite_model: bytearray,
                 size: Union[int, List[int]],

mediapipe/model_maker/python/vision/face_stylizer/face_stylizer.py

@@ -221,7 +221,10 @@ class FaceStylizer(object):
     inputs = tf.keras.Input(shape=(256, 256, 3))
     x = self._encoder(inputs)
     x = self._decoder({'inputs': x + self.w_avg})
-    outputs = x['image'][-1]
+    x = x['image'][-1]
+    # Scale the data range from [-1, 1] to [0, 1] to support running inference
+    # on both CPU and GPU.
+    outputs = (x + 1.0) / 2.0
     model = tf.keras.Model(inputs=inputs, outputs=outputs)
 
     tflite_model = model_util.convert_to_tflite(

mediapipe/model_maker/python/vision/face_stylizer/face_stylizer_test.py

@@ -12,8 +12,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import tensorflow as tf
 
+from mediapipe.model_maker.python.core.utils import test_util as mm_test_util
 from mediapipe.model_maker.python.vision import face_stylizer
 from mediapipe.tasks.python.test import test_utils
 
@@ -52,14 +55,28 @@ class FaceStylizerTest(tf.test.TestCase):
 
   def test_export_face_stylizer_tflite_model(self):
     with self.test_session(use_gpu=True):
+      model_enum = face_stylizer.SupportedModels.BLAZE_FACE_STYLIZER_256
       face_stylizer_options = face_stylizer.FaceStylizerOptions(
-          model=face_stylizer.SupportedModels.BLAZE_FACE_STYLIZER_256,
-          hparams=face_stylizer.HParams(epochs=0),
+          model=model_enum,
+          hparams=face_stylizer.HParams(
+              epochs=0, export_dir=self.get_temp_dir()
+          ),
       )
       model = face_stylizer.FaceStylizer.create(
           train_data=self._train_data, options=face_stylizer_options
       )
-      model.export_model()
+      tflite_model_name = 'custom_face_stylizer.tflite'
+      model.export_model(model_name=tflite_model_name)
+      face_stylizer_tflite_file = os.path.join(
+          self.get_temp_dir(), tflite_model_name
+      )
+      spec = face_stylizer.SupportedModels.get(model_enum)
+      input_image_shape = spec.input_image_shape
+      input_tensor_shape = [1] + list(input_image_shape) + [3]
+      input_tensor = mm_test_util.create_random_sample(size=input_tensor_shape)
+      output = mm_test_util.run_tflite(face_stylizer_tflite_file, input_tensor)
+      self.assertTrue((output >= 0.0).all())
+      self.assertTrue((output <= 1.0).all())
 
 
 if __name__ == '__main__':