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set different graph for solution api

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This commit is contained in:
Mautisim Munir 2022-09-26 17:39:06 +05:00
parent 517bb70212
commit 065571100c
3 changed files with 32 additions and 25 deletions
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7
mediapipe/graphs/pose_tracking/BUILD
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@ -38,6 +38,13 @@ mediapipe_binary_graph(
deps = [":pose_tracking_gpu_deps"],
)
mediapipe_binary_graph(
name = "pose_tracking_gpu_image_binary_graph",
graph = "pose_tracking_gpu_image.pbtxt",
output_name = "pose_tracking_gpu_image.binarypb",
deps = [":pose_tracking_gpu_deps"],
)
cc_library(
name = "pose_tracking_cpu_deps",
deps = [

25
mediapipe/graphs/pose_tracking/pose_tracking_gpu.pbtxt
View File

@ -1,16 +1,12 @@
# MediaPipe graph that performs pose tracking with TensorFlow Lite on GPU.
# GPU buffer. (GpuBuffer)
input_stream: "IMAGE:input_video"
input_stream: "input_video"
# Output image with rendered results. (GpuBuffer)
output_stream: "output_video"
# Pose landmarks. (NormalizedLandmarkList)
#output_stream: "pose_landmarks"
output_stream: "IMAGE:throttled_input_video"
output_stream: "DETECTION:pose_detection"
output_stream: "output_video"
output_stream: "pose_landmarks"
# Generates side packet to enable segmentation.
node {
@ -18,12 +14,11 @@ node {
output_side_packet: "PACKET:enable_segmentation"
node_options: {
[type.googleapis.com/mediapipe.ConstantSidePacketCalculatorOptions]: {
packet { bool_value: false }
packet { bool_value: true }
}
}
}
# Throttles the images flowing downstream for flow control. It passes through
# the very first incoming image unaltered, and waits for downstream nodes
# (calculators and subgraphs) in the graph to finish their tasks before it
@ -34,9 +29,6 @@ node {
# real-time mobile applications. It also eliminates unnecessarily computation,
# e.g., the output produced by a node may get dropped downstream if the
# subsequent nodes are still busy processing previous inputs.
node {
calculator: "FlowLimiterCalculator"
input_stream: "input_video"
@ -45,18 +37,9 @@ node {
tag_index: "FINISHED"
back_edge: true
}
output_stream: "throttled_input_video_cpu"
output_stream: "throttled_input_video"
}
# Converts Image to GpuBuffer for PoseLandmarkGPU to consume.
node {
calculator: "FromImageCalculator"
input_stream: "IMAGE:throttled_input_video_cpu"
output_stream: "IMAGE_GPU:throttled_input_video"
output_stream: "SOURCE_ON_GPU:is_gpu_image"
}
# Subgraph that detects poses and corresponding landmarks.
node {
calculator: "PoseLandmarkGpu"

25
mediapipe/graphs/pose_tracking/pose_tracking_solution_gpu.pbtxt → mediapipe/graphs/pose_tracking/pose_tracking_gpu_image.pbtxt
View File

@ -1,12 +1,16 @@
# MediaPipe graph that performs pose tracking with TensorFlow Lite on GPU.
# GPU buffer. (GpuBuffer)
input_stream: "input_video"
input_stream: "IMAGE:input_video"
# Output image with rendered results. (GpuBuffer)
output_stream: "output_video"
# Pose landmarks. (NormalizedLandmarkList)
output_stream: "pose_landmarks"
#output_stream: "pose_landmarks"
output_stream: "IMAGE:throttled_input_video"
output_stream: "DETECTION:pose_detection"
output_stream: "output_video"
# Generates side packet to enable segmentation.
node {
@ -14,11 +18,12 @@ node {
output_side_packet: "PACKET:enable_segmentation"
node_options: {
[type.googleapis.com/mediapipe.ConstantSidePacketCalculatorOptions]: {
packet { bool_value: true }
packet { bool_value: false }
}
}
}
# Throttles the images flowing downstream for flow control. It passes through
# the very first incoming image unaltered, and waits for downstream nodes
# (calculators and subgraphs) in the graph to finish their tasks before it
@ -29,6 +34,9 @@ node {
# real-time mobile applications. It also eliminates unnecessarily computation,
# e.g., the output produced by a node may get dropped downstream if the
# subsequent nodes are still busy processing previous inputs.
node {
calculator: "FlowLimiterCalculator"
input_stream: "input_video"
@ -37,9 +45,18 @@ node {
tag_index: "FINISHED"
back_edge: true
}
output_stream: "throttled_input_video"
output_stream: "throttled_input_video_cpu"
}
# Converts Image to GpuBuffer for PoseLandmarkGPU to consume.
node {
calculator: "FromImageCalculator"
input_stream: "IMAGE:throttled_input_video_cpu"
output_stream: "IMAGE_GPU:throttled_input_video"
output_stream: "SOURCE_ON_GPU:is_gpu_image"
}
# Subgraph that detects poses and corresponding landmarks.
node {
calculator: "PoseLandmarkGpu"