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AIO Aux Preprocessor node using MediaPIpe-FaceMesh as preprocessor error #501

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fafayqa opened this issue Jan 10, 2025 · 1 comment
Open

AIO Aux Preprocessor node using MediaPIpe-FaceMesh as preprocessor error #501

fafayqa opened this issue Jan 10, 2025 · 1 comment

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@fafayqa
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fafayqa commented Jan 10, 2025

ComfyUI Error Report

Error Details

  • Node ID: 161
  • Node Type: AIO_Preprocessor
  • Exception Type: RuntimeError
  • Exception Message: Failed to parse: node {
    calculator: "ImagePropertiesCalculator"
    input_stream: "IMAGE:image"
    output_stream: "SIZE:image_size"
    }
    node {
    calculator: "PreviousLoopbackCalculator"
    input_stream: "MAIN:image"
    input_stream: "LOOP:face_rects_from_landmarks"
    output_stream: "PREV_LOOP:prev_face_rects_from_landmarks"
    input_stream_info {
    tag_index: "LOOP"
    back_edge: true
    }
    }
    node {
    calculator: "GateCalculator"
    input_stream: "prev_face_rects_from_landmarks"
    output_stream: "gated_prev_face_rects_from_landmarks"
    input_side_packet: "ALLOW:use_prev_landmarks"
    options {
    [mediapipe.GateCalculatorOptions.ext] {
    allow: true
    }
    }
    }
    node {
    calculator: "NormalizedRectVectorHasMinSizeCalculator"
    input_stream: "ITERABLE:gated_prev_face_rects_from_landmarks"
    output_stream: "prev_has_enough_faces"
    input_side_packet: "num_faces"
    }
    node {
    calculator: "GateCalculator"
    input_stream: "image"
    input_stream: "DISALLOW:prev_has_enough_faces"
    output_stream: "gated_image"
    options {
    [mediapipe.GateCalculatorOptions.ext] {
    empty_packets_as_allow: true
    }
    }
    }
    node {
    calculator: "ImagePropertiesCalculator"
    input_stream: "IMAGE:gated_image"
    output_stream: "SIZE:gated_image_size"
    }
    node {
    name: "facelandmarkcpu__TfLiteCustomOpResolverCalculator"
    calculator: "TfLiteCustomOpResolverCalculator"
    output_side_packet: "OP_RESOLVER:facelandmarkcpu__op_resolver"
    }
    node {
    name: "facedetectionshortrangecpu__facedetectionshortrange__facedetection__ToImageCalculator"
    calculator: "ToImageCalculator"
    input_stream: "IMAGE:gated_image"
    output_stream: "IMAGE:facedetectionshortrangecpu__facedetectionshortrange__facedetection__multi_backend_image"
    }
    node {
    name: "facedetectionshortrangecpu__facedetectionshortrange__facedetection__ImageToTensorCalculator"
    calculator: "ImageToTensorCalculator"
    input_stream: "IMAGE:facedetectionshortrangecpu__facedetectionshortrange__facedetection__multi_backend_image"
    output_stream: "TENSORS:facedetectionshortrangecpu__facedetectionshortrange__facedetection__input_tensors"
    output_stream: "MATRIX:facedetectionshortrangecpu__facedetectionshortrange__facedetection__transform_matrix"
    node_options {
    type_url: "type.googleapis.com/mediapipe.ImageToTensorCalculatorOptions"
    value: "\030\001"\n\r\000\000\200\277\025\000\000\200?0\001\010\200\001\020\200\001"
    }
    }
    node {
    name: "facedetectionshortrangecpu__facedetectionshortrange__facedetection__SsdAnchorsCalculator"
    calculator: "SsdAnchorsCalculator"
    output_side_packet: "facedetectionshortrangecpu__facedetectionshortrange__facedetection__anchors"
    node_options {
    type_url: "type.googleapis.com/mediapipe.SsdAnchorsCalculatorOptions"
    value: "\035\000\000\030>%\000\000@?-\000\000\000?5\000\000\000?]\000\000\200?p\001\010\200\001\020\200\0018\004P\010P\020P\020P\020m\000\000\200?"
    }
    }
    node {
    name: "facelandmarkcpu__facelandmarksmodelloader__switchcontainer__SwitchDemuxCalculator"
    calculator: "SwitchDemuxCalculator"
    input_side_packet: "ENABLE:with_attention"
    options {
    [mediapipe.SwitchContainerOptions.ext] {
    }
    }
    }
    node {
    name: "facelandmarkcpu__facelandmarksmodelloader__switchcontainer__ConstantSidePacketCalculator_1"
    calculator: "ConstantSidePacketCalculator"
    output_side_packet: "PACKET:facelandmarkcpu__facelandmarksmodelloader__switchcontainer__c0__facelandmarkcpu__facelandmarksmodelloader__model_path"
    options {
    [mediapipe.ConstantSidePacketCalculatorOptions.ext] {
    packet {
    string_value: "mediapipe/modules/face_landmark/face_landmark.tflite"
    }
    }
    }
    }
    node {
    name: "facelandmarkcpu__facelandmarksmodelloader__switchcontainer__ConstantSidePacketCalculator_2"
    calculator: "ConstantSidePacketCalculator"
    output_side_packet: "PACKET:facelandmarkcpu__facelandmarksmodelloader__switchcontainer__c1__facelandmarkcpu__facelandmarksmodelloader__model_path"
    options {
    [mediapipe.ConstantSidePacketCalculatorOptions.ext] {
    packet {
    string_value: "mediapipe/modules/face_landmark/face_landmark_with_attention.tflite"
    }
    }
    }
    }
    node {
    name: "facelandmarkcpu__facelandmarksmodelloader__switchcontainer__SwitchMuxCalculator"
    calculator: "SwitchMuxCalculator"
    input_side_packet: "ENABLE:with_attention"
    input_side_packet: "C0__PACKET:facelandmarkcpu__facelandmarksmodelloader__switchcontainer__c0__facelandmarkcpu__facelandmarksmodelloader__model_path"
    input_side_packet: "C1__PACKET:facelandmarkcpu__facelandmarksmodelloader__switchcontainer__c1__facelandmarkcpu__facelandmarksmodelloader__model_path"
    output_side_packet: "PACKET:facelandmarkcpu__facelandmarksmodelloader__model_path"
    options {
    [mediapipe.SwitchContainerOptions.ext] {
    }
    }
    }
    node {
    name: "facelandmarkcpu__facelandmarksmodelloader__ResourceProviderCalculator"
    calculator: "ResourceProviderCalculator"
    input_side_packet: "RESOURCE_ID:facelandmarkcpu__facelandmarksmodelloader__model_path"
    output_side_packet: "RESOURCE:facelandmarkcpu__facelandmarksmodelloader__model_resource"
    }
    node {
    name: "facelandmarkcpu__facelandmarksmodelloader__TfLiteModelCalculator"
    calculator: "TfLiteModelCalculator"
    input_side_packet: "MODEL_RESOURCE:facelandmarkcpu__facelandmarksmodelloader__model_resource"
    output_side_packet: "MODEL:facelandmarkcpu__model"
    }
    node {
    name: "facedetectionshortrangecpu__facedetectionshortrange__facedetection__inferencecalculator__facedetectionshortrangecpu__facedetectionshortrange__facedetection__InferenceCalculator"
    calculator: "InferenceCalculatorCpu"
    input_stream: "TENSORS:facedetectionshortrangecpu__facedetectionshortrange__facedetection__input_tensors"
    output_stream: "TENSORS:facedetectionshortrangecpu__facedetectionshortrange__facedetection__detection_tensors"
    node_options {
    type_url: "type.googleapis.com/mediapipe.InferenceCalculatorOptions"
    value: "*\002"\000\nBmediapipe/modules/face_detection/face_detection_short_range.tflite"
    }
    }
    node {
    name: "facedetectionshortrangecpu__facedetectionshortrange__facedetection__TensorsToDetectionsCalculator"
    calculator: "TensorsToDetectionsCalculator"
    input_stream: "TENSORS:facedetectionshortrangecpu__facedetectionshortrange__facedetection__detection_tensors"
    output_stream: "DETECTIONS:facedetectionshortrangecpu__facedetectionshortrange__facedetection__unfiltered_detections"
    input_side_packet: "ANCHORS:facedetectionshortrangecpu__facedetectionshortrange__facedetection__anchors"
    node_options {
    type_url: "type.googleapis.com/mediapipe.TensorsToDetectionsCalculatorOptions"
    value: "\010\001\020\200\007\030\020%\000\000\000C-\000\000\000C5\000\000\000C=\000\000\000CH\004P\006X\002`\000p\001x\001\205\001\000\000\310B\235\001\000\000\000?"
    }
    }
    node {
    name: "facedetectionshortrangecpu__facedetectionshortrange__facedetection__NonMaxSuppressionCalculator"
    calculator: "NonMaxSuppressionCalculator"
    input_stream: "facedetectionshortrangecpu__facedetectionshortrange__facedetection__unfiltered_detections"
    output_stream: "facedetectionshortrangecpu__facedetectionshortrange__facedetection__filtered_detections"
    options {
    [mediapipe.NonMaxSuppressionCalculatorOptions.ext] {
    min_suppression_threshold: 0.3
    overlap_type: INTERSECTION_OVER_UNION
    algorithm: WEIGHTED
    }
    }
    }
    node {
    name: "facedetectionshortrangecpu__facedetectionshortrange__facedetection__DetectionProjectionCalculator"
    calculator: "DetectionProjectionCalculator"
    input_stream: "DETECTIONS:facedetectionshortrangecpu__facedetectionshortrange__facedetection__filtered_detections"
    input_stream: "PROJECTION_MATRIX:facedetectionshortrangecpu__facedetectionshortrange__facedetection__transform_matrix"
    output_stream: "DETECTIONS:all_face_detections"
    }
    node {
    calculator: "ClipDetectionVectorSizeCalculator"
    input_stream: "all_face_detections"
    output_stream: "face_detections"
    input_side_packet: "num_faces"
    }
    node {
    calculator: "BeginLoopDetectionCalculator"
    input_stream: "ITERABLE:face_detections"
    input_stream: "CLONE:gated_image_size"
    output_stream: "ITEM:face_detection"
    output_stream: "CLONE:detections_loop_image_size"
    output_stream: "BATCH_END:detections_loop_end_timestamp"
    }
    node {
    name: "facedetectionfrontdetectiontoroi__DetectionsToRectsCalculator"
    calculator: "DetectionsToRectsCalculator"
    input_stream: "DETECTION:face_detection"
    input_stream: "IMAGE_SIZE:detections_loop_image_size"
    output_stream: "NORM_RECT:facedetectionfrontdetectiontoroi__initial_roi"
    options {
    [mediapipe.DetectionsToRectsCalculatorOptions.ext] {
    rotation_vector_start_keypoint_index: 0
    rotation_vector_end_keypoint_index: 1
    rotation_vector_target_angle_degrees: 0
    }
    }
    }
    node {
    name: "facedetectionfrontdetectiontoroi__RectTransformationCalculator"
    calculator: "RectTransformationCalculator"
    input_stream: "NORM_RECT:facedetectionfrontdetectiontoroi__initial_roi"
    input_stream: "IMAGE_SIZE:detections_loop_image_size"
    output_stream: "face_rect_from_detection"
    options {
    [mediapipe.RectTransformationCalculatorOptions.ext] {
    scale_x: 1.5
    scale_y: 1.5
    square_long: true
    }
    }
    }
    node {
    calculator: "EndLoopNormalizedRectCalculator"
    input_stream: "ITEM:face_rect_from_detection"
    input_stream: "BATCH_END:detections_loop_end_timestamp"
    output_stream: "ITERABLE:face_rects_from_detections"
    }
    node {
    calculator: "AssociationNormRectCalculator"
    input_stream: "face_rects_from_detections"
    input_stream: "gated_prev_face_rects_from_landmarks"
    output_stream: "face_rects"
    options {
    [mediapipe.AssociationCalculatorOptions.ext] {
    min_similarity_threshold: 0.5
    }
    }
    }
    node {
    calculator: "BeginLoopNormalizedRectCalculator"
    input_stream: "ITERABLE:face_rects"
    input_stream: "CLONE:0:image"
    input_stream: "CLONE:1:image_size"
    output_stream: "ITEM:face_rect"
    output_stream: "CLONE:0:landmarks_loop_image"
    output_stream: "CLONE:1:landmarks_loop_image_size"
    output_stream: "BATCH_END:landmarks_loop_end_timestamp"
    }
    node {
    name: "facelandmarkcpu__ImageToTensorCalculator"
    calculator: "ImageToTensorCalculator"
    input_stream: "IMAGE:landmarks_loop_image"
    input_stream: "NORM_RECT:face_rect"
    output_stream: "TENSORS:facelandmarkcpu__input_tensors"
    options {
    [mediapipe.ImageToTensorCalculatorOptions.ext] {
    output_tensor_width: 192
    output_tensor_height: 192
    output_tensor_float_range {
    min: 0
    max: 1
    }
    }
    }
    }
    node {
    name: "facelandmarkcpu__inferencecalculator__facelandmarkcpu__InferenceCalculator"
    calculator: "InferenceCalculatorCpu"
    input_stream: "TENSORS:facelandmarkcpu__input_tensors"
    output_stream: "TENSORS:facelandmarkcpu__output_tensors"
    input_side_packet: "MODEL:facelandmarkcpu__model"
    input_side_packet: "OP_RESOLVER:facelandmarkcpu__op_resolver"
    options {
    [mediapipe.InferenceCalculatorOptions.ext] {
    delegate {
    xnnpack {
    }
    }
    }
    }
    }
    node {
    name: "facelandmarkcpu__switchcontainer_1__SwitchDemuxCalculator"
    calculator: "SwitchDemuxCalculator"
    input_stream: "facelandmarkcpu__output_tensors"
    output_stream: "C0__:facelandmarkcpu__switchcontainer_1__c0__facelandmarkcpu__output_tensors"
    output_stream: "C1__:facelandmarkcpu__switchcontainer_1__c1__facelandmarkcpu__output_tensors"
    input_side_packet: "ENABLE:with_attention"
    options {
    [mediapipe.SwitchContainerOptions.ext] {
    }
    }
    }
    node {
    name: "facelandmarkcpu__switchcontainer_1__SplitTensorVectorCalculator_1"
    calculator: "SplitTensorVectorCalculator"
    input_stream: "facelandmarkcpu__switchcontainer_1__c0__facelandmarkcpu__output_tensors"
    output_stream: "facelandmarkcpu__switchcontainer_1__c0__facelandmarkcpu__landmark_tensors"
    output_stream: "facelandmarkcpu__switchcontainer_1__c0__facelandmarkcpu__face_flag_tensor"
    options {
    [mediapipe.SplitVectorCalculatorOptions.ext] {
    ranges {
    begin: 0
    end: 1
    }
    ranges {
    begin: 1
    end: 2
    }
    }
    }
    }
    node {
    name: "facelandmarkcpu__switchcontainer_1__SplitTensorVectorCalculator_2"
    calculator: "SplitTensorVectorCalculator"
    input_stream: "facelandmarkcpu__switchcontainer_1__c1__facelandmarkcpu__output_tensors"
    output_stream: "facelandmarkcpu__switchcontainer_1__c1__facelandmarkcpu__landmark_tensors"
    output_stream: "facelandmarkcpu__switchcontainer_1__c1__facelandmarkcpu__face_flag_tensor"
    options {
    [mediapipe.SplitVectorCalculatorOptions.ext] {
    ranges {
    begin: 0
    end: 6
    }
    ranges {
    begin: 6
    end: 7
    }
    }
    }
    }
    node {
    name: "facelandmarkcpu__switchcontainer_1__SwitchMuxCalculator"
    calculator: "SwitchMuxCalculator"
    input_stream: "C0__:facelandmarkcpu__switchcontainer_1__c0__facelandmarkcpu__landmark_tensors"
    input_stream: "C0__:1:facelandmarkcpu__switchcontainer_1__c0__facelandmarkcpu__face_flag_tensor"
    input_stream: "C1__:facelandmarkcpu__switchcontainer_1__c1__facelandmarkcpu__landmark_tensors"
    input_stream: "C1__:1:facelandmarkcpu__switchcontainer_1__c1__facelandmarkcpu__face_flag_tensor"
    output_stream: "facelandmarkcpu__landmark_tensors"
    output_stream: "facelandmarkcpu__face_flag_tensor"
    input_side_packet: "ENABLE:with_attention"
    options {
    [mediapipe.SwitchContainerOptions.ext] {
    }
    }
    }
    node {
    name: "facelandmarkcpu__TensorsToFloatsCalculator"
    calculator: "TensorsToFloatsCalculator"
    input_stream: "TENSORS:facelandmarkcpu__face_flag_tensor"
    output_stream: "FLOAT:facelandmarkcpu__face_presence_score"
    options {
    [mediapipe.TensorsToFloatsCalculatorOptions.ext] {
    activation: SIGMOID
    }
    }
    }
    node {
    name: "facelandmarkcpu__ThresholdingCalculator"
    calculator: "ThresholdingCalculator"
    input_stream: "FLOAT:facelandmarkcpu__face_presence_score"
    output_stream: "FLAG:facelandmarkcpu__face_presence"
    options {
    [mediapipe.ThresholdingCalculatorOptions.ext] {
    threshold: 0.5
    }
    }
    }
    node {
    name: "facelandmarkcpu__GateCalculator"
    calculator: "GateCalculator"
    input_stream: "facelandmarkcpu__landmark_tensors"
    input_stream: "ALLOW:facelandmarkcpu__face_presence"
    output_stream: "facelandmarkcpu__ensured_landmark_tensors"
    }
    node {
    name: "facelandmarkcpu__switchcontainer_2__SwitchDemuxCalculator"
    calculator: "SwitchDemuxCalculator"
    input_stream: "TENSORS:facelandmarkcpu__ensured_landmark_tensors"
    output_stream: "C0__TENSORS:facelandmarkcpu__switchcontainer_2__c0__facelandmarkcpu__ensured_landmark_tensors"
    output_stream: "C1__TENSORS:facelandmarkcpu__switchcontainer_2__c1__facelandmarkcpu__ensured_landmark_tensors"
    input_side_packet: "ENABLE:with_attention"
    options {
    [mediapipe.SwitchContainerOptions.ext] {
    }
    }
    }
    node {
    name: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarks__TensorsToLandmarksCalculator"
    calculator: "TensorsToLandmarksCalculator"
    input_stream: "TENSORS:facelandmarkcpu__switchcontainer_2__c0__facelandmarkcpu__ensured_landmark_tensors"
    output_stream: "NORM_LANDMARKS:facelandmarkcpu__switchcontainer_2__c0__facelandmarkcpu__landmarks"
    options {
    [mediapipe.TensorsToLandmarksCalculatorOptions.ext] {
    num_landmarks: 468
    input_image_width: 192
    input_image_height: 192
    }
    }
    }
    node {
    name: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__SplitTensorVectorCalculator"
    calculator: "SplitTensorVectorCalculator"
    input_stream: "facelandmarkcpu__switchcontainer_2__c1__facelandmarkcpu__ensured_landmark_tensors"
    output_stream: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__mesh_tensor"
    output_stream: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__lips_tensor"
    output_stream: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__left_eye_tensor"
    output_stream: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__right_eye_tensor"
    output_stream: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__left_iris_tensor"
    output_stream: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__right_iris_tensor"
    options {
    [mediapipe.SplitVectorCalculatorOptions.ext] {
    ranges {
    begin: 0
    end: 1
    }
    ranges {
    begin: 1
    end: 2
    }
    ranges {
    begin: 2
    end: 3
    }
    ranges {
    begin: 3
    end: 4
    }
    ranges {
    begin: 4
    end: 5
    }
    ranges {
    begin: 5
    end: 6
    }
    }
    }
    }
    node {
    name: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__TensorsToLandmarksCalculator_1"
    calculator: "TensorsToLandmarksCalculator"
    input_stream: "TENSORS:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__mesh_tensor"
    output_stream: "NORM_LANDMARKS:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__mesh_landmarks"
    options {
    [mediapipe.TensorsToLandmarksCalculatorOptions.ext] {
    num_landmarks: 468
    input_image_width: 192
    input_image_height: 192
    }
    }
    }
    node {
    name: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__TensorsToLandmarksCalculator_2"
    calculator: "TensorsToLandmarksCalculator"
    input_stream: "TENSORS:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__lips_tensor"
    output_stream: "NORM_LANDMARKS:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__lips_landmarks"
    options {
    [mediapipe.TensorsToLandmarksCalculatorOptions.ext] {
    num_landmarks: 80
    input_image_width: 192
    input_image_height: 192
    }
    }
    }
    node {
    name: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__TensorsToLandmarksCalculator_3"
    calculator: "TensorsToLandmarksCalculator"
    input_stream: "TENSORS:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__left_eye_tensor"
    output_stream: "NORM_LANDMARKS:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__left_eye_landmarks"
    options {
    [mediapipe.TensorsToLandmarksCalculatorOptions.ext] {
    num_landmarks: 71
    input_image_width: 192
    input_image_height: 192
    }
    }
    }
    node {
    name: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__TensorsToLandmarksCalculator_4"
    calculator: "TensorsToLandmarksCalculator"
    input_stream: "TENSORS:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__right_eye_tensor"
    output_stream: "NORM_LANDMARKS:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__right_eye_landmarks"
    options {
    [mediapipe.TensorsToLandmarksCalculatorOptions.ext] {
    num_landmarks: 71
    input_image_width: 192
    input_image_height: 192
    }
    }
    }
    node {
    name: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__TensorsToLandmarksCalculator_5"
    calculator: "TensorsToLandmarksCalculator"
    input_stream: "TENSORS:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__left_iris_tensor"
    output_stream: "NORM_LANDMARKS:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__left_iris_landmarks"
    options {
    [mediapipe.TensorsToLandmarksCalculatorOptions.ext] {
    num_landmarks: 5
    input_image_width: 192
    input_image_height: 192
    }
    }
    }
    node {
    name: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__TensorsToLandmarksCalculator_6"
    calculator: "TensorsToLandmarksCalculator"
    input_stream: "TENSORS:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__right_iris_tensor"
    output_stream: "NORM_LANDMARKS:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__right_iris_landmarks"
    options {
    [mediapipe.TensorsToLandmarksCalculatorOptions.ext] {
    num_landmarks: 5
    input_image_width: 192
    input_image_height: 192
    }
    }
    }
    node {
    name: "facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__LandmarksRefinementCalculator"
    calculator: "LandmarksRefinementCalculator"
    input_stream: "LANDMARKS:0:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__mesh_landmarks"
    input_stream: "LANDMARKS:1:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__lips_landmarks"
    input_stream: "LANDMARKS:2:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__left_eye_landmarks"
    input_stream: "LANDMARKS:3:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__right_eye_landmarks"
    input_stream: "LANDMARKS:4:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__left_iris_landmarks"
    input_stream: "LANDMARKS:5:facelandmarkcpu__switchcontainer_2__tensorstofacelandmarkswithattention__right_iris_landmarks"
    output_stream: "REFINED_LANDMARKS:facelandmarkcpu__switchcontainer_2__c1__facelandmarkcpu__landmarks"
    options {
    [mediapipe.LandmarksRefinementCalculatorOptions.ext] {
    refinement {
    indexes_mapping: 0
    indexes_mapping: 1
    indexes_mapping: 2
    indexes_mapping: 3
    indexes_mapping: 4
    indexes_mapping: 5
    indexes_mapping: 6
    indexes_mapping: 7
    indexes_mapping: 8
    indexes_mapping: 9
    indexes_mapping: 10
    indexes_mapping: 11
    indexes_mapping: 12
    indexes_mapping: 13
    indexes_mapping: 14
    indexes_mapping: 15
    indexes_mapping: 16
    indexes_mapping: 17
    indexes_mapping: 18
    indexes_mapping: 19
    indexes_mapping: 20
    indexes_mapping: 21
    indexes_mapping: 22
    indexes_mapping: 23
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    input_stream: "IMAGE_SIZE:landmarks_loop_image_size"
    output_stream: "NORM_RECT:facelandmarklandmarkstoroi__face_rect_from_landmarks"
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    node {
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    output_stream: "face_rect_from_landmarks"
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    output_stream: "ITERABLE:face_rects_from_landmarks"
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    input_stream: "IMAGE:image"
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    output_stream: "ROIS_FROM_LANDMARKS:face_rects_from_landmarks"
    output_stream: "ROIS_FROM_DETECTIONS:face_rects_from_detections"
    input_side_packet: "NUM_FACES:num_faces"
    input_side_packet: "USE_PREV_LANDMARKS:use_prev_landmarks"
    input_side_packet: "WITH_ATTENTION:with_attention"
    type: "FaceLandmarkFrontCpu"

Stack Trace

  File "Z:\_PSTART_\_APPS_\_AI_\ComfyUI_windows_portable\ComfyUI\execution.py", line 327, in execute
    output_data, output_ui, has_subgraph = get_output_data(obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)
                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "Z:\_PSTART_\_APPS_\_AI_\ComfyUI_windows_portable\ComfyUI\execution.py", line 202, in get_output_data
    return_values = _map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "Z:\_PSTART_\_APPS_\_AI_\ComfyUI_windows_portable\ComfyUI\execution.py", line 174, in _map_node_over_list
    process_inputs(input_dict, i)

  File "Z:\_PSTART_\_APPS_\_AI_\ComfyUI_windows_portable\ComfyUI\execution.py", line 163, in process_inputs
    results.append(getattr(obj, func)(**inputs))
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "Z:\_PSTART_\_APPS_\_AI_\ComfyUI_windows_portable\ComfyUI\custom_nodes\comfyui_controlnet_aux\__init__.py", line 120, in execute
    return getattr(aux_class(), aux_class.FUNCTION)(**params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "Z:\_PSTART_\_APPS_\_AI_\ComfyUI_windows_portable\ComfyUI\custom_nodes\comfyui_controlnet_aux\node_wrappers\mediapipe_face.py", line 31, in detect
    return (common_annotator_call(MediapipeFaceDetector(), image, max_faces=max_faces, min_confidence=min_confidence, resolution=resolution), )
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "Z:\_PSTART_\_APPS_\_AI_\ComfyUI_windows_portable\ComfyUI\custom_nodes\comfyui_controlnet_aux\utils.py", line 85, in common_annotator_call
    np_result = model(np_image, output_type="np", detect_resolution=detect_resolution, **kwargs)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "Z:\_PSTART_\_APPS_\_AI_\ComfyUI_windows_portable\ComfyUI\custom_nodes\comfyui_controlnet_aux\src\custom_controlnet_aux\mediapipe_face\__init__.py", line 25, in __call__
    detected_map = generate_annotation(detected_map, max_faces, min_confidence)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "Z:\_PSTART_\_APPS_\_AI_\ComfyUI_windows_portable\ComfyUI\custom_nodes\comfyui_controlnet_aux\src\custom_controlnet_aux\mediapipe_face\mediapipe_face_common.py", line 98, in generate_annotation
    with mp_face_mesh.FaceMesh(
         ^^^^^^^^^^^^^^^^^^^^^^

  File "Z:\_PSTART_\_APPS_\_AI_\ComfyUI_windows_portable\python_embeded\Lib\site-packages\mediapipe\python\solutions\face_mesh.py", line 95, in __init__
    super().__init__(

  File "Z:\_PSTART_\_APPS_\_AI_\ComfyUI_windows_portable\python_embeded\Lib\site-packages\mediapipe\python\solution_base.py", line 248, in __init__
    self._graph = calculator_graph.CalculatorGraph(
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

System Information

  • ComfyUI Version: v0.3.10-20-g79eea51
  • Arguments: ComfyUI\main.py --windows-standalone-build
  • OS: nt
  • Python Version: 3.12.7 (tags/v3.12.7:0b05ead, Oct 1 2024, 03:06:41) [MSC v.1941 64 bit (AMD64)]
  • Embedded Python: true
  • PyTorch Version: 2.5.1+cu124

Devices

  • Name: cuda:0 NVIDIA GeForce RTX 3060 : cudaMallocAsync
    • Type: cuda
    • VRAM Total: 12884377600
    • VRAM Free: 11564880538
    • Torch VRAM Total: 201326592
    • Torch VRAM Free: 12718746

Logs


...EXTREMELLY LONG ERROR LOG FILE, had to remove the rest! :-(
@snoopyterry110
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I had a similar error, but now I have solved the problem. This may be a version problem.
You can try to downgrade the version of mediapipe
The last versions I used were mediapipe-0.10.14 numpy-1.26.4 protobuf-4.25.5

@ltdrdata ltdrdata mentioned this issue Jan 25, 2025
Closed
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@fafayqa @snoopyterry110