160 lines
5.5 KiB
Plaintext
160 lines
5.5 KiB
Plaintext
# MediaPipe graph that performs iris distance computation on desktop with
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# TensorFlow Lite on CPU.
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# Used in the example in
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# mediapipie/examples/desktop/iris_tracking:iris_depth_from_image_desktop.
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# Raw image bytes. (std::string)
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input_stream: "input_image_bytes"
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# Image with all the detections rendered. (ImageFrame)
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output_stream: "output_image"
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# Estimated depth in mm from the camera to the left iris of the face (if any) in
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# the image. (float)
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output_stream: "left_iris_depth_mm"
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# Estimated depth in mm from the camera to the right iris of the face (if any)
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# in the image. (float)
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output_stream: "right_iris_depth_mm"
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# Computes the focal length in pixels based on EXIF information stored in the
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# image file. The output is an ImageFileProperties object containing relevant
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# image EXIF information along with focal length in pixels.
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node {
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calculator: "ImageFilePropertiesCalculator"
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input_stream: "input_image_bytes"
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output_side_packet: "image_file_properties"
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}
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# Converts a raw string with encoded image bytes into an ImageFrame object
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# via OpenCV so that it can be processed by downstream calculators.
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node {
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calculator: "OpenCvEncodedImageToImageFrameCalculator"
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input_stream: "input_image_bytes"
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output_stream: "input_image"
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}
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# Defines how many faces to detect. Iris tracking currently only handles one
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# face (left and right eye), and therefore this should always be set to 1.
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node {
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calculator: "ConstantSidePacketCalculator"
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output_side_packet: "PACKET:0:num_faces"
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node_options: {
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[type.googleapis.com/mediapipe.ConstantSidePacketCalculatorOptions]: {
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packet { int_value: 1 }
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}
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}
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}
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# Detects faces and corresponding landmarks.
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node {
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calculator: "FaceLandmarkFrontCpu"
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input_stream: "IMAGE:input_image"
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input_side_packet: "NUM_FACES:num_faces"
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output_stream: "LANDMARKS:multi_face_landmarks"
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output_stream: "ROIS_FROM_LANDMARKS:face_rects_from_landmarks"
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output_stream: "DETECTIONS:face_detections"
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output_stream: "ROIS_FROM_DETECTIONS:face_rects_from_detections"
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}
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# Gets the very first and only face from "multi_face_landmarks" vector.
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node {
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calculator: "SplitNormalizedLandmarkListVectorCalculator"
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input_stream: "multi_face_landmarks"
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output_stream: "face_landmarks"
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node_options: {
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[type.googleapis.com/mediapipe.SplitVectorCalculatorOptions] {
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ranges: { begin: 0 end: 1 }
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element_only: true
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}
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}
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}
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# Gets the very first and only face rect from "face_rects_from_landmarks"
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# vector.
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node {
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calculator: "SplitNormalizedRectVectorCalculator"
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input_stream: "face_rects_from_landmarks"
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output_stream: "face_rect"
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node_options: {
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[type.googleapis.com/mediapipe.SplitVectorCalculatorOptions] {
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ranges: { begin: 0 end: 1 }
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element_only: true
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}
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}
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}
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# Gets two landmarks which define left eye boundary.
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node {
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calculator: "SplitNormalizedLandmarkListCalculator"
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input_stream: "face_landmarks"
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output_stream: "left_eye_boundary_landmarks"
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node_options: {
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[type.googleapis.com/mediapipe.SplitVectorCalculatorOptions] {
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ranges: { begin: 33 end: 34 }
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ranges: { begin: 133 end: 134 }
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combine_outputs: true
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}
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}
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}
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# Gets two landmarks which define right eye boundary.
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node {
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calculator: "SplitNormalizedLandmarkListCalculator"
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input_stream: "face_landmarks"
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output_stream: "right_eye_boundary_landmarks"
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node_options: {
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[type.googleapis.com/mediapipe.SplitVectorCalculatorOptions] {
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ranges: { begin: 362 end: 363 }
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ranges: { begin: 263 end: 264 }
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combine_outputs: true
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}
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}
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}
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# Detects iris landmarks, eye contour landmarks, and corresponding rect (ROI).
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node {
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calculator: "IrisLandmarkLeftAndRightCpu"
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input_stream: "IMAGE:input_image"
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input_stream: "LEFT_EYE_BOUNDARY_LANDMARKS:left_eye_boundary_landmarks"
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input_stream: "RIGHT_EYE_BOUNDARY_LANDMARKS:right_eye_boundary_landmarks"
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output_stream: "LEFT_EYE_CONTOUR_LANDMARKS:left_eye_contour_landmarks"
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output_stream: "LEFT_EYE_IRIS_LANDMARKS:left_iris_landmarks"
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output_stream: "LEFT_EYE_ROI:left_eye_rect_from_landmarks"
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output_stream: "RIGHT_EYE_CONTOUR_LANDMARKS:right_eye_contour_landmarks"
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output_stream: "RIGHT_EYE_IRIS_LANDMARKS:right_iris_landmarks"
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output_stream: "RIGHT_EYE_ROI:right_eye_rect_from_landmarks"
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}
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node {
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calculator: "ConcatenateNormalizedLandmarkListCalculator"
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input_stream: "left_eye_contour_landmarks"
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input_stream: "right_eye_contour_landmarks"
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output_stream: "refined_eye_landmarks"
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}
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node {
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calculator: "UpdateFaceLandmarksCalculator"
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input_stream: "NEW_EYE_LANDMARKS:refined_eye_landmarks"
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input_stream: "FACE_LANDMARKS:face_landmarks"
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output_stream: "UPDATED_FACE_LANDMARKS:updated_face_landmarks"
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}
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# Renders annotations and overlays them on top of the input images.
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node {
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calculator: "IrisAndDepthRendererCpu"
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input_stream: "IMAGE:input_image"
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input_stream: "FACE_LANDMARKS:updated_face_landmarks"
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input_stream: "EYE_LANDMARKS_LEFT:left_eye_contour_landmarks"
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input_stream: "EYE_LANDMARKS_RIGHT:right_eye_contour_landmarks"
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input_stream: "IRIS_LANDMARKS_LEFT:left_iris_landmarks"
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input_stream: "IRIS_LANDMARKS_RIGHT:right_iris_landmarks"
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input_stream: "NORM_RECT:face_rect"
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input_stream: "LEFT_EYE_RECT:left_eye_rect_from_landmarks"
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input_stream: "RIGHT_EYE_RECT:right_eye_rect_from_landmarks"
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input_stream: "DETECTIONS:face_detections"
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input_side_packet: "IMAGE_FILE_PROPERTIES:image_file_properties"
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output_stream: "IRIS_LANDMARKS:iris_landmarks"
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output_stream: "IMAGE:output_image"
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output_stream: "LEFT_IRIS_DEPTH_MM:left_iris_depth_mm"
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output_stream: "RIGHT_IRIS_DEPTH_MM:right_iris_depth_mm"
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}
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