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GitOrigin-RevId: ff83882955f1a1e2a043ff4e71278be9d7217bbe
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MediaPipe Team
2021-05-05 14:56:16 -04:00
committed by chuoling
parent ecb5b5f44a
commit a9b643e0f5
210 changed files with 5312 additions and 3838 deletions
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mediapipe/modules/pose_landmark/pose_landmark_by_roi_cpu.pbtxt
+43 -67
View File
@@ -1,18 +1,18 @@
# MediaPipe graph to detect/predict upper-body pose landmarks. (CPU input, and
# inference is executed on CPU.)
# MediaPipe graph to detect/predict pose landmarks. (CPU input, and inference is
# executed on CPU.)
#
# It is required that "pose_landmark_full_body.tflite" or
# "pose_landmark_upper_body.tflite" is available at
# "mediapipe/modules/pose_landmark/pose_landmark_full_body.tflite"
# or
# "mediapipe/modules/pose_landmark/pose_landmark_upper_body.tflite"
# It is required that "pose_landmark_lite.tflite" or
# "pose_landmark_full.tflite" or "pose_landmark_heavy.tflite" is available at
# "mediapipe/modules/pose_landmark/pose_landmark_lite.tflite" or
# "mediapipe/modules/pose_landmark/pose_landmark_full.tflite" or
# "mediapipe/modules/pose_landmark/pose_landmark_heavy.tflite"
# path respectively during execution, depending on the specification in the
# UPPER_BODY_ONLY input side packet.
# MODEL_COMPLEXITY input side packet.
#
# EXAMPLE:
# node {
# calculator: "PoseLandmarkByRoiCpu"
# input_side_packet: "UPPER_BODY_ONLY:upper_body_only"
# input_side_packet: "MODEL_COMPLEXITY:model_complexity"
# input_stream: "IMAGE:image"
# input_stream: "ROI:roi"
# output_stream: "LANDMARKS:landmarks"
@@ -26,16 +26,14 @@ input_stream: "IMAGE:image"
# (NormalizedRect)
input_stream: "ROI:roi"
# Whether to detect/predict the full set of pose landmarks (see below), or only
# those on the upper body. If unspecified, functions as set to false. (bool)
# Note that upper-body-only prediction may be more accurate for use cases where
# the lower-body parts are mostly out of view.
input_side_packet: "UPPER_BODY_ONLY:upper_body_only"
# Complexity of the pose landmark model: 0, 1 or 2. Landmark accuracy as well as
# inference latency generally go up with the model complexity. If unspecified,
# functions as set to 0. (int)
input_side_packet: "MODEL_COMPLEXITY:model_complexity"
# Pose landmarks within the given ROI. (NormalizedLandmarkList)
# We have 33 landmarks (see pose_landmark_full_body_topology.svg) with the
# first 25 fall on the upper body (see pose_landmark_upper_body_topology.svg),
# and there are other auxiliary key points.
# We have 33 landmarks (see pose_landmark_topology.svg) and there are other
# auxiliary key points.
# 0 - nose
# 1 - left eye (inner)
# 2 - left eye
@@ -104,7 +102,7 @@ node: {
# Loads the pose landmark TF Lite model.
node {
calculator: "PoseLandmarkModelLoader"
input_side_packet: "UPPER_BODY_ONLY:upper_body_only"
input_side_packet: "MODEL_COMPLEXITY:model_complexity"
output_side_packet: "MODEL:model"
}
@@ -128,10 +126,12 @@ node {
input_stream: "output_tensors"
output_stream: "landmark_tensors"
output_stream: "pose_flag_tensor"
output_stream: "heatmap_tensor"
options: {
[mediapipe.SplitVectorCalculatorOptions.ext] {
ranges: { begin: 0 end: 1 }
ranges: { begin: 1 end: 2 }
ranges: { begin: 3 end: 4 }
}
}
}
@@ -168,36 +168,29 @@ node {
# Decodes the landmark tensors into a vector of landmarks, where the landmark
# coordinates are normalized by the size of the input image to the model.
node {
calculator: "SwitchContainer"
input_side_packet: "ENABLE:upper_body_only"
calculator: "TensorsToLandmarksCalculator"
input_stream: "TENSORS:ensured_landmark_tensors"
output_stream: "NORM_LANDMARKS:raw_landmarks"
options: {
[mediapipe.SwitchContainerOptions.ext] {
contained_node: {
calculator: "TensorsToLandmarksCalculator"
options: {
[mediapipe.TensorsToLandmarksCalculatorOptions.ext] {
num_landmarks: 35
input_image_width: 256
input_image_height: 256
visibility_activation: SIGMOID
presence_activation: SIGMOID
}
}
}
contained_node: {
calculator: "TensorsToLandmarksCalculator"
options: {
[mediapipe.TensorsToLandmarksCalculatorOptions.ext] {
num_landmarks: 27
input_image_width: 256
input_image_height: 256
visibility_activation: SIGMOID
presence_activation: SIGMOID
}
}
}
[mediapipe.TensorsToLandmarksCalculatorOptions.ext] {
num_landmarks: 39
input_image_width: 256
input_image_height: 256
visibility_activation: SIGMOID
presence_activation: SIGMOID
}
}
}
# Refines landmarks with the heatmap tensor.
node {
calculator: "RefineLandmarksFromHeatmapCalculator"
input_stream: "NORM_LANDMARKS:raw_landmarks"
input_stream: "TENSORS:heatmap_tensor"
output_stream: "NORM_LANDMARKS:refined_landmarks"
options: {
[mediapipe.RefineLandmarksFromHeatmapCalculatorOptions.ext] {
kernel_size: 7
}
}
}
@@ -208,7 +201,7 @@ node {
# image before image transformation).
node {
calculator: "LandmarkLetterboxRemovalCalculator"
input_stream: "LANDMARKS:raw_landmarks"
input_stream: "LANDMARKS:refined_landmarks"
input_stream: "LETTERBOX_PADDING:letterbox_padding"
output_stream: "LANDMARKS:adjusted_landmarks"
}
@@ -225,31 +218,14 @@ node {
# Splits the landmarks into two sets: the actual pose landmarks and the
# auxiliary landmarks.
node {
calculator: "SwitchContainer"
input_side_packet: "ENABLE:upper_body_only"
calculator: "SplitNormalizedLandmarkListCalculator"
input_stream: "all_landmarks"
output_stream: "landmarks"
output_stream: "auxiliary_landmarks"
options: {
[mediapipe.SwitchContainerOptions.ext] {
contained_node: {
calculator: "SplitNormalizedLandmarkListCalculator"
options: {
[mediapipe.SplitVectorCalculatorOptions.ext] {
ranges: { begin: 0 end: 33 }
ranges: { begin: 33 end: 35 }
}
}
}
contained_node: {
calculator: "SplitNormalizedLandmarkListCalculator"
options: {
[mediapipe.SplitVectorCalculatorOptions.ext] {
ranges: { begin: 0 end: 25 }
ranges: { begin: 25 end: 27 }
}
}
}
[mediapipe.SplitVectorCalculatorOptions.ext] {
ranges: { begin: 0 end: 33 }
ranges: { begin: 33 end: 35 }
}
}
}