diff --git a/mediapipe/python/BUILD b/mediapipe/python/BUILD index e5d33fb3..a7e77703 100644 --- a/mediapipe/python/BUILD +++ b/mediapipe/python/BUILD @@ -94,6 +94,7 @@ cc_library( "//mediapipe/tasks/cc/text/text_embedder:text_embedder_graph", "//mediapipe/tasks/cc/vision/face_detector:face_detector_graph", "//mediapipe/tasks/cc/vision/face_landmarker:face_landmarker_graph", + "//mediapipe/tasks/cc/vision/face_stylizer:face_stylizer_graph", "//mediapipe/tasks/cc/vision/gesture_recognizer:gesture_recognizer_graph", "//mediapipe/tasks/cc/vision/image_classifier:image_classifier_graph", "//mediapipe/tasks/cc/vision/image_embedder:image_embedder_graph", diff --git a/mediapipe/tasks/python/vision/BUILD b/mediapipe/tasks/python/vision/BUILD index 6ea87327..89a988be 100644 --- a/mediapipe/tasks/python/vision/BUILD +++ b/mediapipe/tasks/python/vision/BUILD @@ -197,3 +197,22 @@ py_library( "//mediapipe/tasks/python/vision/core:vision_task_running_mode", ], ) + +py_library( + name = "face_stylizer", + srcs = [ + "face_stylizer.py", + ], + deps = [ + "//mediapipe/python:_framework_bindings", + "//mediapipe/python:packet_creator", + "//mediapipe/python:packet_getter", + "//mediapipe/tasks/cc/vision/face_stylizer/proto:face_stylizer_graph_options_py_pb2", + "//mediapipe/tasks/python/core:base_options", + "//mediapipe/tasks/python/core:optional_dependencies", + "//mediapipe/tasks/python/core:task_info", + "//mediapipe/tasks/python/vision/core:base_vision_task_api", + "//mediapipe/tasks/python/vision/core:image_processing_options", + "//mediapipe/tasks/python/vision/core:vision_task_running_mode", + ], +) diff --git a/mediapipe/tasks/python/vision/face_stylizer.py b/mediapipe/tasks/python/vision/face_stylizer.py new file mode 100644 index 00000000..0bbd9c4d --- /dev/null +++ b/mediapipe/tasks/python/vision/face_stylizer.py @@ -0,0 +1,279 @@ +# Copyright 2023 The MediaPipe Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""MediaPipe face stylizer task.""" + +import dataclasses +from typing import Callable, Mapping, Optional + +from mediapipe.python import packet_creator +from mediapipe.python import packet_getter +from mediapipe.python._framework_bindings import image as image_module +from mediapipe.python._framework_bindings import packet as packet_module +from mediapipe.tasks.cc.vision.face_stylizer.proto import face_stylizer_graph_options_pb2 +from mediapipe.tasks.python.core import base_options as base_options_module +from mediapipe.tasks.python.core import task_info as task_info_module +from mediapipe.tasks.python.core.optional_dependencies import doc_controls +from mediapipe.tasks.python.vision.core import base_vision_task_api +from mediapipe.tasks.python.vision.core import image_processing_options as image_processing_options_module +from mediapipe.tasks.python.vision.core import vision_task_running_mode as running_mode_module + +_BaseOptions = base_options_module.BaseOptions +_FaceStylizerGraphOptionsProto = ( + face_stylizer_graph_options_pb2.FaceStylizerGraphOptions +) +_RunningMode = running_mode_module.VisionTaskRunningMode +_ImageProcessingOptions = image_processing_options_module.ImageProcessingOptions +_TaskInfo = task_info_module.TaskInfo + +_STYLIZED_IMAGE_NAME = 'stylized_image' +_STYLIZED_IMAGE_TAG = 'STYLIZED_IMAGE' +_NORM_RECT_STREAM_NAME = 'norm_rect_in' +_NORM_RECT_TAG = 'NORM_RECT' +_IMAGE_IN_STREAM_NAME = 'image_in' +_IMAGE_OUT_STREAM_NAME = 'image_out' +_IMAGE_TAG = 'IMAGE' +_TASK_GRAPH_NAME = 'mediapipe.tasks.vision.face_stylizer.FaceStylizerGraph' +_MICRO_SECONDS_PER_MILLISECOND = 1000 + + +@dataclasses.dataclass +class FaceStylizerOptions: + """Options for the face stylizer task. + + Attributes: + base_options: Base options for the face stylizer task. + running_mode: The running mode of the task. Default to the image mode. Face + stylizer task has three running modes: 1) The image mode for stylizing one + face on a single image input. 2) The video mode for stylizing one face per + frame on the decoded frames of a video. 3) The live stream mode for + stylizing one face on a live stream of input data, such as from camera. + result_callback: The user-defined result callback for processing live stream + data. The result callback should only be specified when the running mode + is set to the live stream mode. + """ + + base_options: _BaseOptions + running_mode: _RunningMode = _RunningMode.IMAGE + result_callback: Optional[ + Callable[[image_module.Image, image_module.Image, int], None] + ] = None + + @doc_controls.do_not_generate_docs + def to_pb2(self) -> _FaceStylizerGraphOptionsProto: + """Generates an FaceStylizerOptions protobuf object.""" + base_options_proto = self.base_options.to_pb2() + base_options_proto.use_stream_mode = ( + False if self.running_mode == _RunningMode.IMAGE else True + ) + return _FaceStylizerGraphOptionsProto(base_options=base_options_proto) + + +class FaceStylizer(base_vision_task_api.BaseVisionTaskApi): + """Class that performs face stylization on images.""" + + @classmethod + def create_from_model_path(cls, model_path: str) -> 'FaceStylizer': + """Creates an `FaceStylizer` object from a TensorFlow Lite model and the default `FaceStylizerOptions`. + + Note that the created `FaceStylizer` instance is in image mode, for + stylizing one face on a single image input. + + Args: + model_path: Path to the model. + + Returns: + `FaceStylizer` object that's created from the model file and the default + `FaceStylizerOptions`. + + Raises: + ValueError: If failed to create `FaceStylizer` object from the provided + file such as invalid file path. + RuntimeError: If other types of error occurred. + """ + base_options = _BaseOptions(model_asset_path=model_path) + options = FaceStylizerOptions( + base_options=base_options, running_mode=_RunningMode.IMAGE + ) + return cls.create_from_options(options) + + @classmethod + def create_from_options(cls, options: FaceStylizerOptions) -> 'FaceStylizer': + """Creates the `FaceStylizer` object from face stylizer options. + + Args: + options: Options for the face stylizer task. + + Returns: + `FaceStylizer` object that's created from `options`. + + Raises: + ValueError: If failed to create `FaceStylizer` object from + `FaceStylizerOptions` such as missing the model. + RuntimeError: If other types of error occurred. + """ + + def packets_callback(output_packets: Mapping[str, packet_module.Packet]): + if output_packets[_IMAGE_OUT_STREAM_NAME].is_empty(): + return + image = packet_getter.get_image(output_packets[_IMAGE_OUT_STREAM_NAME]) + stylized_image_packet = output_packets[_STYLIZED_IMAGE_NAME] + stylized_image = packet_getter.get_image(stylized_image_packet) + + options.result_callback( + stylized_image, + image, + stylized_image_packet.timestamp.value + // _MICRO_SECONDS_PER_MILLISECOND, + ) + + task_info = _TaskInfo( + task_graph=_TASK_GRAPH_NAME, + input_streams=[ + ':'.join([_IMAGE_TAG, _IMAGE_IN_STREAM_NAME]), + ':'.join([_NORM_RECT_TAG, _NORM_RECT_STREAM_NAME]), + ], + output_streams=[ + ':'.join([_STYLIZED_IMAGE_TAG, _STYLIZED_IMAGE_NAME]), + ':'.join([_IMAGE_TAG, _IMAGE_OUT_STREAM_NAME]), + ], + task_options=options, + ) + return cls( + task_info.generate_graph_config( + enable_flow_limiting=options.running_mode + == _RunningMode.LIVE_STREAM + ), + options.running_mode, + packets_callback if options.result_callback else None, + ) + + def stylize( + self, + image: image_module.Image, + image_processing_options: Optional[_ImageProcessingOptions] = None, + ) -> image_module.Image: + """Performs face stylization on the provided MediaPipe Image. + + Only use this method when the FaceStylizer is created with the image + running mode. + + To ensure that the output image has reasonable quality, the stylized output + image size is the smaller of the model output size and the size of the + `region_of_interest` specified in `image_processing_options`. + + Args: + image: MediaPipe Image. + image_processing_options: Options for image processing. + + Returns: + The stylized image. + + Raises: + ValueError: If any of the input arguments is invalid. + RuntimeError: If face stylization failed to run. + """ + normalized_rect = self.convert_to_normalized_rect(image_processing_options) + output_packets = self._process_image_data({ + _IMAGE_IN_STREAM_NAME: packet_creator.create_image(image), + _NORM_RECT_STREAM_NAME: packet_creator.create_proto( + normalized_rect.to_pb2() + ), + }) + return packet_getter.get_image(output_packets[_STYLIZED_IMAGE_NAME]) + + def stylize_for_video( + self, + image: image_module.Image, + timestamp_ms: int, + image_processing_options: Optional[_ImageProcessingOptions] = None, + ) -> image_module.Image: + """Performs face stylization on the provided video frames. + + Only use this method when the FaceStylizer is created with the video + running mode. It's required to provide the video frame's timestamp (in + milliseconds) along with the video frame. The input timestamps should be + monotonically increasing for adjacent calls of this method. + + To ensure that the output image has reasonable quality, the stylized output + image size is the smaller of the model output size and the size of the + `region_of_interest` specified in `image_processing_options`. + + Args: + image: MediaPipe Image. + timestamp_ms: The timestamp of the input video frame in milliseconds. + image_processing_options: Options for image processing. + + Returns: + The stylized image. + + Raises: + ValueError: If any of the input arguments is invalid. + RuntimeError: If face stylization failed to run. + """ + normalized_rect = self.convert_to_normalized_rect(image_processing_options) + output_packets = self._process_video_data({ + _IMAGE_IN_STREAM_NAME: packet_creator.create_image(image).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND + ), + _NORM_RECT_STREAM_NAME: packet_creator.create_proto( + normalized_rect.to_pb2() + ).at(timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND), + }) + return packet_getter.get_image(output_packets[_STYLIZED_IMAGE_NAME]) + + def stylize_async( + self, + image: image_module.Image, + timestamp_ms: int, + image_processing_options: Optional[_ImageProcessingOptions] = None, + ) -> None: + """Sends live image data (an Image with a unique timestamp) to perform face stylization. + + Only use this method when the FaceStylizer is created with the live stream + running mode. The input timestamps should be monotonically increasing for + adjacent calls of this method. This method will return immediately after the + input image is accepted. The results will be available via the + `result_callback` provided in the `FaceStylizerOptions`. The + `stylize_async` method is designed to process live stream data such as + camera input. To lower the overall latency, face stylizer may drop the input + images if needed. In other words, it's not guaranteed to have output per + input image. + + To ensure that the stylized image has reasonable quality, the stylized + output image size is the smaller of the model output size and the size of + the `region_of_interest` specified in `image_processing_options`. + + The `result_callback` provides: + - The stylized image. + - The input image that the face stylizer runs on. + - The input timestamp in milliseconds. + + Args: + image: MediaPipe Image. + timestamp_ms: The timestamp of the input image in milliseconds. + image_processing_options: Options for image processing. + + Raises: + ValueError: If the current input timestamp is smaller than what the face + stylizer has already processed. + """ + normalized_rect = self.convert_to_normalized_rect(image_processing_options) + self._send_live_stream_data({ + _IMAGE_IN_STREAM_NAME: packet_creator.create_image(image).at( + timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND + ), + _NORM_RECT_STREAM_NAME: packet_creator.create_proto( + normalized_rect.to_pb2() + ).at(timestamp_ms * _MICRO_SECONDS_PER_MILLISECOND), + })