Merge pull request #1 from creativeIKEP/develop

v1.0.1

Assets/Script/PoseVisuallizer.cs

@@ -6,7 +6,6 @@ public class PoseVisuallizer : MonoBehaviour
     [SerializeField] WebCamInput webCamInput;
     [SerializeField] Shader shader;
     [SerializeField] PoseDetectionResource poseDetectionResource;
-    [SerializeField] bool isUpperBodyOnly;
 
     Material material;
     PoseDetecter detecter;
@@ -33,8 +32,6 @@ public class PoseVisuallizer : MonoBehaviour
     void OnRenderObject(){
         // Get predicted pose detection result.
         material.SetBuffer("_pds", detecter.outputBuffer);
-        // Select mode, "upper body only" or "full body".
-        material.SetInt("_upperBodyOnly", (isUpperBodyOnly ? 1 : 0));
 
         // Set pose detection count as vertex shader instance count.
         ComputeBuffer.CopyCount(detecter.outputBuffer, boxDrawArgs, sizeof(uint));

Assets/Shader/Visualizer.shader

@@ -7,7 +7,6 @@
 
     #define PI 3.14159265359
 
-    uint _upperBodyOnly;
     StructuredBuffer<PoseDetection> _pds;
 
     float2x2 rot2D(float angle)
@@ -42,8 +41,8 @@
         float2 hip = pd.keyPoints[0];
         float2 shoulder = pd.keyPoints[2];
 
-        float2 center = _upperBodyOnly ? shoulder : hip;
-        float2 roi = _upperBodyOnly ? pd.keyPoints[3] : pd.keyPoints[1];
+        float2 center = hip;
+        float2 roi = pd.keyPoints[1];
 
         float sizeX = abs(roi.x - center.x);
         float sizeY = abs(roi.y - center.y);

Packages/PoseDetectionBarracuda/CHANGELOG.md

@@ -0,0 +1,5 @@
+### [1.0.1] - 2022-01-09
+- Supported ComputeBuffer input.
+
+### [1.0.0] - 2021-05-17
+This is the first release of `creativeIKEP/PoseDetectionBarracuda`(`jp.ikep.mediapipe.posedetection`).

Packages/PoseDetectionBarracuda/README.md

@@ -1,5 +1,5 @@
 # PoseDetectionBarracuda
-![demo](/screenshot/demo.png)
+![demo](https://user-images.githubusercontent.com/34697515/148678516-9b608be0-40a0-4c01-98da-c1c22d021cba.png)
 
 PoseDetectionBarracuda is a human pose detecter that runs the [Mediapipe Pose](https://google.github.io/mediapipe/solutions/pose) Detection neural network model on the [Unity Barracuda](https://docs.unity3d.com/Packages/com.unity.barracuda@latest).
 
@@ -21,7 +21,7 @@ To the `scopedRegistries` section:
 ```
 To the `dependencies` section:
 ```
-"jp.ikep.mediapipe.posedetection": "1.0.0"
+"jp.ikep.mediapipe.posedetection": "1.0.1"
 ```
 Finally, the manifest file looks like below:
 ```
@@ -34,15 +34,16 @@ Finally, the manifest file looks like below:
         }
     ],
     "dependencies": {
-        "jp.ikep.mediapipe.posedetection": "1.0.0",
+        "jp.ikep.mediapipe.posedetection": "1.0.1",
         ...
     }
 }
 ```
 
+### Install from GitHub URL
 PoseDetectionBarracuda can be installed by adding below URL on the Unity Package Manager's window.
 ```
-https://github.com/creativeIKEP/PoseDetectionBarracuda.git?path=Packages/PoseDetectionBarracuda#v1.0.0
+https://github.com/creativeIKEP/PoseDetectionBarracuda.git?path=Packages/PoseDetectionBarracuda#v1.0.1
 ```
 
 ## Demo Image

Packages/PoseDetectionBarracuda/Script/PoseDetecter.cs

@@ -53,17 +53,21 @@ public class PoseDetecter: System.IDisposable
         }
 
         public void ProcessImage(Texture inputTexture, float poseThreshold = 0.75f, float iouThreshold = 0.3f){
-            // Reset append type buffer datas of previous frame. 
-            postProcessBuffer.SetCounterValue(0);
-            outputBuffer.SetCounterValue(0);
-
             // Resize `inputTexture` texture to network model image size.
             preProcessCS.SetTexture(0, "_inputTexture", inputTexture);
             preProcessCS.SetBuffer(0, "_output", networkInputBuffer);
             preProcessCS.Dispatch(0, IMAGE_SIZE / 8, IMAGE_SIZE / 8, 1);
 
+            ProcessImage(networkInputBuffer, poseThreshold, iouThreshold);
+        }
+
+        public void ProcessImage(ComputeBuffer input, float poseThreshold = 0.75f, float iouThreshold = 0.3f){
+            // Reset append type buffer datas of previous frame. 
+            postProcessBuffer.SetCounterValue(0);
+            outputBuffer.SetCounterValue(0);
+
             //Execute neural network model.
-            var inputTensor = new Tensor(1, IMAGE_SIZE, IMAGE_SIZE, 3, networkInputBuffer);
+            var inputTensor = new Tensor(1, IMAGE_SIZE, IMAGE_SIZE, 3, input);
             woker.Execute(inputTensor);
             inputTensor.Dispose();
 

Packages/PoseDetectionBarracuda/package.json

@@ -6,7 +6,7 @@
     "name": "jp.ikep.mediapipe.posedetection",
     "displayName": "PoseDetectionBarracuda",
     "description": "Mediapipe pose detection for Unity Barracuda",
-    "version": "1.0.0",
+    "version": "1.0.1",
     "unity": "2020.3",
     "unityRelease": "6f1",
     "keywords": [

README.md

@@ -1,5 +1,5 @@
 # PoseDetectionBarracuda
-![demo](/screenshot/demo.png)
+![demo](https://user-images.githubusercontent.com/34697515/148678516-9b608be0-40a0-4c01-98da-c1c22d021cba.png)
 
 PoseDetectionBarracuda is a human pose detecter that runs the [Mediapipe Pose](https://google.github.io/mediapipe/solutions/pose) Detection neural network model on the [Unity Barracuda](https://docs.unity3d.com/Packages/com.unity.barracuda@latest).
 
@@ -21,7 +21,7 @@ To the `scopedRegistries` section:
 ```
 To the `dependencies` section:
 ```
-"jp.ikep.mediapipe.posedetection": "1.0.0"
+"jp.ikep.mediapipe.posedetection": "1.0.1"
 ```
 Finally, the manifest file looks like below:
 ```
@@ -34,7 +34,7 @@ Finally, the manifest file looks like below:
         }
     ],
     "dependencies": {
-        "jp.ikep.mediapipe.posedetection": "1.0.0",
+        "jp.ikep.mediapipe.posedetection": "1.0.1",
         ...
     }
 }
@@ -43,7 +43,7 @@ Finally, the manifest file looks like below:
 ### Install from GitHub URL
 PoseDetectionBarracuda can be installed by adding below URL on the Unity Package Manager's window.
 ```
-https://github.com/creativeIKEP/PoseDetectionBarracuda.git?path=Packages/PoseDetectionBarracuda#v1.0.0
+https://github.com/creativeIKEP/PoseDetectionBarracuda.git?path=Packages/PoseDetectionBarracuda#v1.0.1
 ```
 
 ## Demo Image