Project import generated by Copybara.

GitOrigin-RevId: bbbbcb4f5174dea33525729ede47c770069157cd

mediapipe/modules/hand_landmark/BUILD

@@ -22,16 +22,30 @@ licenses(["notice"])
 package(default_visibility = ["//visibility:public"])
 
 exports_files([
-    "hand_landmark.tflite",
+    "hand_landmark_full.tflite",
+    "hand_landmark_lite.tflite",
     "hand_landmark_sparse.tflite",
     "handedness.txt",
 ])
 
+mediapipe_simple_subgraph(
+    name = "hand_landmark_model_loader",
+    graph = "hand_landmark_model_loader.pbtxt",
+    register_as = "HandLandmarkModelLoader",
+    deps = [
+        "//mediapipe/calculators/core:constant_side_packet_calculator",
+        "//mediapipe/calculators/tflite:tflite_model_calculator",
+        "//mediapipe/calculators/util:local_file_contents_calculator",
+        "//mediapipe/framework/tool:switch_container",
+    ],
+)
+
 mediapipe_simple_subgraph(
     name = "hand_landmark_cpu",
     graph = "hand_landmark_cpu.pbtxt",
     register_as = "HandLandmarkCpu",
     deps = [
+        ":hand_landmark_model_loader",
         "//mediapipe/calculators/core:gate_calculator",
         "//mediapipe/calculators/core:split_vector_calculator",
         "//mediapipe/calculators/tensor:image_to_tensor_calculator",
@@ -50,6 +64,7 @@ mediapipe_simple_subgraph(
     graph = "hand_landmark_gpu.pbtxt",
     register_as = "HandLandmarkGpu",
     deps = [
+        ":hand_landmark_model_loader",
         "//mediapipe/calculators/core:gate_calculator",
         "//mediapipe/calculators/core:split_vector_calculator",
         "//mediapipe/calculators/tensor:image_to_tensor_calculator",

mediapipe/modules/hand_landmark/hand_landmark_cpu.pbtxt

@@ -8,6 +8,11 @@ input_stream: "IMAGE:image"
 # (NormalizedRect)
 input_stream: "ROI:hand_rect"
 
+# Complexity of the hand landmark model: 0 or 1. Landmark accuracy as well as
+# inference latency generally go up with the model complexity. If unspecified,
+# functions as set to 1. (int)
+input_side_packet: "MODEL_COMPLEXITY:model_complexity"
+
 # 21 hand landmarks within the given ROI. (NormalizedLandmarkList)
 # NOTE: if a hand is not present within the given ROI, for this particular
 # timestamp there will not be an output packet in the LANDMARKS stream. However,
@@ -40,16 +45,23 @@ node {
   }
 }
 
+# Loads the hand landmark TF Lite model.
+node {
+  calculator: "HandLandmarkModelLoader"
+  input_side_packet: "MODEL_COMPLEXITY:model_complexity"
+  output_side_packet: "MODEL:model"
+}
+
 # Runs a TensorFlow Lite model on CPU that takes an image tensor and outputs a
 # vector of tensors representing, for instance, detection boxes/keypoints and
 # scores.
 node {
   calculator: "InferenceCalculator"
+  input_side_packet: "MODEL:model"
   input_stream: "TENSORS:input_tensor"
   output_stream: "TENSORS:output_tensors"
   options: {
     [mediapipe.InferenceCalculatorOptions.ext] {
-      model_path: "mediapipe/modules/hand_landmark/hand_landmark.tflite"
       delegate {
         xnnpack {}
       }

mediapipe/modules/hand_landmark/hand_landmark_gpu.pbtxt

@@ -8,6 +8,11 @@ input_stream: "IMAGE:image"
 # (NormalizedRect)
 input_stream: "ROI:hand_rect"
 
+# Complexity of the hand landmark model: 0 or 1. Landmark accuracy as well as
+# inference latency generally go up with the model complexity. If unspecified,
+# functions as set to 1. (int)
+input_side_packet: "MODEL_COMPLEXITY:model_complexity"
+
 # 21 hand landmarks within the given ROI. (NormalizedLandmarkList)
 # NOTE: if a hand is not present within the given ROI, for this particular
 # timestamp there will not be an output packet in the LANDMARKS stream. However,
@@ -41,18 +46,21 @@ node {
   }
 }
 
+# Loads the hand landmark TF Lite model.
+node {
+  calculator: "HandLandmarkModelLoader"
+  input_side_packet: "MODEL_COMPLEXITY:model_complexity"
+  output_side_packet: "MODEL:model"
+}
+
 # Runs a TensorFlow Lite model on GPU that takes an image tensor and outputs a
 # vector of tensors representing, for instance, detection boxes/keypoints and
 # scores.
 node {
   calculator: "InferenceCalculator"
+  input_side_packet: "MODEL:model"
   input_stream: "TENSORS:input_tensor"
   output_stream: "TENSORS:output_tensors"
-  options: {
-    [mediapipe.InferenceCalculatorOptions.ext] {
-      model_path: "mediapipe/modules/hand_landmark/hand_landmark.tflite"
-    }
-  }
 }
 
 # Splits a vector of tensors to multiple vectors according to the ranges

mediapipe/modules/hand_landmark/hand_landmark_model_loader.pbtxt

@@ -0,0 +1,63 @@
+# MediaPipe graph to load a selected hand landmark TF Lite model.
+
+type: "HandLandmarkModelLoader"
+
+# Complexity of the hand landmark model: 0 or 1. Landmark accuracy as well as
+# inference latency generally go up with the model complexity. If unspecified,
+# functions as set to 1. (int)
+input_side_packet: "MODEL_COMPLEXITY:model_complexity"
+
+# TF Lite model represented as a FlatBuffer.
+# (std::unique_ptr<tflite::FlatBufferModel, std::function<void(tflite::FlatBufferModel*)>>)
+output_side_packet: "MODEL:model"
+
+# Determines path to the desired pose landmark model file.
+node {
+  calculator: "SwitchContainer"
+  input_side_packet: "SELECT:model_complexity"
+  output_side_packet: "PACKET:model_path"
+  options: {
+    [mediapipe.SwitchContainerOptions.ext] {
+      select: 1
+      contained_node: {
+        calculator: "ConstantSidePacketCalculator"
+        options: {
+          [mediapipe.ConstantSidePacketCalculatorOptions.ext]: {
+            packet {
+              string_value: "mediapipe/modules/hand_landmark/hand_landmark_lite.tflite"
+            }
+          }
+        }
+      }
+      contained_node: {
+        calculator: "ConstantSidePacketCalculator"
+        options: {
+          [mediapipe.ConstantSidePacketCalculatorOptions.ext]: {
+            packet {
+              string_value: "mediapipe/modules/hand_landmark/hand_landmark_full.tflite"
+            }
+          }
+        }
+      }
+    }
+  }
+}
+
+# Loads the file in the specified path into a blob.
+node {
+  calculator: "LocalFileContentsCalculator"
+  input_side_packet: "FILE_PATH:model_path"
+  output_side_packet: "CONTENTS:model_blob"
+  options: {
+    [mediapipe.LocalFileContentsCalculatorOptions.ext]: {
+      text_mode: false
+    }
+  }
+}
+
+# Converts the input blob into a TF Lite model.
+node {
+  calculator: "TfLiteModelCalculator"
+  input_side_packet: "MODEL_BLOB:model_blob"
+  output_side_packet: "MODEL:model"
+}

mediapipe/modules/hand_landmark/hand_landmark_tracking_cpu.pbtxt

@@ -14,6 +14,11 @@ input_stream: "IMAGE:image"
 # Max number of hands to detect/track. (int)
 input_side_packet: "NUM_HANDS:num_hands"
 
+# Complexity of the hand landmark model: 0 or 1. Landmark accuracy as well as
+# inference latency generally go up with the model complexity. If unspecified,
+# functions as set to 1. (int)
+input_side_packet: "MODEL_COMPLEXITY:model_complexity"
+
 # Whether landmarks on the previous image should be used to help localize
 # landmarks on the current image. (bool)
 input_side_packet: "USE_PREV_LANDMARKS:use_prev_landmarks"
@@ -177,6 +182,7 @@ node {
 # Detect hand landmarks for the specific hand rect.
 node {
   calculator: "HandLandmarkCpu"
+  input_side_packet: "MODEL_COMPLEXITY:model_complexity"
   input_stream: "IMAGE:image_for_landmarks"
   input_stream: "ROI:single_hand_rect"
   output_stream: "LANDMARKS:single_hand_landmarks"

mediapipe/modules/hand_landmark/hand_landmark_tracking_cpu_image.pbtxt

@@ -14,6 +14,11 @@ input_stream: "IMAGE:image"
 # Max number of hands to detect/track. (int)
 input_side_packet: "NUM_HANDS:num_hands"
 
+# Complexity of the hand landmark model: 0 or 1. Landmark accuracy as well as
+# inference latency generally go up with the model complexity. If unspecified,
+# functions as set to 1. (int)
+input_side_packet: "MODEL_COMPLEXITY:model_complexity"
+
 # Whether landmarks on the previous image should be used to help localize
 # landmarks on the current image. (bool)
 input_side_packet: "USE_PREV_LANDMARKS:use_prev_landmarks"
@@ -85,6 +90,7 @@ node {
   calculator: "HandLandmarkTrackingCpu"
   input_stream: "IMAGE:image_frame"
   input_side_packet: "NUM_HANDS:num_hands"
+  input_side_packet: "MODEL_COMPLEXITY:model_complexity"
   input_side_packet: "USE_PREV_LANDMARKS:use_prev_landmarks"
   output_stream: "LANDMARKS:multi_hand_landmarks"
   output_stream: "HANDEDNESS:multi_handedness"

mediapipe/modules/hand_landmark/hand_landmark_tracking_gpu.pbtxt

@@ -14,6 +14,11 @@ input_stream: "IMAGE:image"
 # Max number of hands to detect/track. (int)
 input_side_packet: "NUM_HANDS:num_hands"
 
+# Complexity of the hand landmark model: 0 or 1. Landmark accuracy as well as
+# inference latency generally go up with the model complexity. If unspecified,
+# functions as set to 1. (int)
+input_side_packet: "MODEL_COMPLEXITY:model_complexity"
+
 # Whether landmarks on the previous image should be used to help localize
 # landmarks on the current image. (bool)
 input_side_packet: "USE_PREV_LANDMARKS:use_prev_landmarks"
@@ -178,6 +183,7 @@ node {
 # Detect hand landmarks for the specific hand rect.
 node {
   calculator: "HandLandmarkGpu"
+  input_side_packet: "MODEL_COMPLEXITY:model_complexity"
   input_stream: "IMAGE:image_for_landmarks"
   input_stream: "ROI:single_hand_rect"
   output_stream: "LANDMARKS:single_hand_landmarks"

mediapipe/modules/hand_landmark/hand_landmark_tracking_gpu_image.pbtxt

@@ -14,6 +14,11 @@ input_stream: "IMAGE:image"
 # Max number of hands to detect/track. (int)
 input_side_packet: "NUM_HANDS:num_hands"
 
+# Complexity of the hand landmark model: 0 or 1. Landmark accuracy as well as
+# inference latency generally go up with the model complexity. If unspecified,
+# functions as set to 1. (int)
+input_side_packet: "MODEL_COMPLEXITY:model_complexity"
+
 # Whether landmarks on the previous image should be used to help localize
 # landmarks on the current image. (bool)
 input_side_packet: "USE_PREV_LANDMARKS:use_prev_landmarks"
@@ -85,6 +90,7 @@ node {
   calculator: "HandLandmarkTrackingGpu"
   input_stream: "IMAGE:gpu_buffer"
   input_side_packet: "NUM_HANDS:num_hands"
+  input_side_packet: "MODEL_COMPLEXITY:model_complexity"
   input_side_packet: "USE_PREV_LANDMARKS:use_prev_landmarks"
   output_stream: "LANDMARKS:multi_hand_landmarks"
   output_stream: "HANDEDNESS:multi_handedness"

mediapipe/modules/holistic_landmark/holistic_landmark_cpu.pbtxt

@@ -7,8 +7,8 @@
 # - "face_landmark.tflite" is available at
 # "mediapipe/modules/face_landmark/face_landmark.tflite"
 #
-# - "hand_landmark.tflite" is available at
-# "mediapipe/modules/hand_landmark/hand_landmark.tflite"
+# - "hand_landmark_full.tflite" is available at
+# "mediapipe/modules/hand_landmark/hand_landmark_full.tflite"
 #
 # - "hand_recrop.tflite" is available at
 # "mediapipe/modules/holistic_landmark/hand_recrop.tflite"

mediapipe/modules/holistic_landmark/holistic_landmark_gpu.pbtxt

@@ -7,8 +7,8 @@
 # - "face_landmark.tflite" is available at
 # "mediapipe/modules/face_landmark/face_landmark.tflite"
 #
-# - "hand_landmark.tflite" is available at
-# "mediapipe/modules/hand_landmark/hand_landmark.tflite"
+# - "hand_landmark_full.tflite" is available at
+# "mediapipe/modules/hand_landmark/hand_landmark_full.tflite"
 #
 # - "hand_recrop.tflite" is available at
 # "mediapipe/modules/holistic_landmark/hand_recrop.tflite"

mediapipe/modules/objectron/calculators/filter_detection_calculator.cc

@@ -237,7 +237,7 @@ absl::Status FilterDetectionCalculator::Process(CalculatorContext* cc) {
 }
 
 bool FilterDetectionCalculator::IsValidLabel(const std::string& label) {
-  bool match = !limit_labels_ || ContainsKey(allowed_labels_, label);
+  bool match = !limit_labels_ || allowed_labels_.contains(label);
   if (!match) {
     // If no exact match is found, check for regular expression
     // comparions in the allowed_labels.