void InputDataProcessingCPU(ImageSegmentaionModels imageSegmentaionModels, Color32[] inputImage, float[] processedInputBuffer)
{
float weight = 1f / 255f;
float bias = 0;
bool rgbRepeats = false;
switch (imageSegmentaionModels)
{
case ImageSegmentaionModels.hair_segmentation:
rgbRepeats = true;
break;
case ImageSegmentaionModels.pspnet_hair_segmentation:
InputDataProcessingCPU_PSP(inputImage, processedInputBuffer);
return;
case ImageSegmentaionModels.deeplabv3:
weight = 1f / 127.5f;
bias = -1;
break;
default:
break;
}
// flatten input data
if (rgbRepeats)
{
for (int i = 0; i < inputImage.Length; i++)
{
// rgbrgbrgb...
processedInputBuffer[i * 3 + 0] = (inputImage[i].r) * weight + bias;
processedInputBuffer[i * 3 + 1] = (inputImage[i].g) * weight + bias;
processedInputBuffer[i * 3 + 2] = (inputImage[i].b) * weight + bias;
}
}
else
{
for (int i = 0; i < inputImage.Length; i++)
{
// rrr...ggg...bbb...
processedInputBuffer[i + inputImage.Length * 0] = (inputImage[i].r) * weight + bias;
processedInputBuffer[i + inputImage.Length * 1] = (inputImage[i].g) * weight + bias;
processedInputBuffer[i + inputImage.Length * 2] = (inputImage[i].b) * weight + bias;
}
}
}
void LoadImage(ImageSegmentaionModels imageSegmentaionModels, AiliaImageSource ailiaImageSource)
{
switch (imageSegmentaionModels)
{
case ImageSegmentaionModels.HRNetV2_W18_Small_v2:
case ImageSegmentaionModels.HRNetV2_W18_Small_v1:
case ImageSegmentaionModels.HRNetV2_W48:
ailiaImageSource.CreateSource("file://" + Application.dataPath + "/AXIP/AILIA-MODELS/ImageSegmentation/SampleImage/road.png");
break;
case ImageSegmentaionModels.hair_segmentation:
ailiaImageSource.CreateSource("file://" + Application.dataPath + "/AXIP/AILIA-MODELS/ImageSegmentation/SampleImage/hair.jpg");
break;
case ImageSegmentaionModels.pspnet_hair_segmentation:
ailiaImageSource.CreateSource("file://" + Application.dataPath + "/AXIP/AILIA-MODELS/ImageSegmentation/SampleImage/hair2.jpg");
break;
case ImageSegmentaionModels.deeplabv3:
ailiaImageSource.CreateSource("file://" + Application.dataPath + "/AXIP/AILIA-MODELS/ImageSegmentation/SampleImage/couple.jpg");
break;
}
}
void SetShape(ImageSegmentaionModels imageSegmentaionModels)
{
Ailia.AILIAShape shape = null;
switch (imageSegmentaionModels)
{
case ImageSegmentaionModels.HRNetV2_W18_Small_v2:
case ImageSegmentaionModels.HRNetV2_W18_Small_v1:
case ImageSegmentaionModels.HRNetV2_W48:
case ImageSegmentaionModels.pspnet_hair_segmentation:
case ImageSegmentaionModels.deeplabv3:
shape = ailiaModel.GetInputShape();
InputWidth = (int)shape.x;
InputHeight = (int)shape.y;
InputChannel = (int)shape.z;
shape = ailiaModel.GetOutputShape();
OutputWidth = (int)shape.x;
OutputHeight = (int)shape.y;
OutputChannel = (int)shape.z;
break;
case ImageSegmentaionModels.hair_segmentation:
shape = new Ailia.AILIAShape();
shape.x = 3;
shape.y = (uint)AiliaImageSource.Width;
shape.z = (uint)AiliaImageSource.Height;
shape.w = 1;
shape.dim = 4;
ailiaModel.SetInputShape(shape);
InputWidth = AiliaImageSource.Width;
InputHeight = AiliaImageSource.Height;
InputChannel = 3;
OutputWidth = AiliaImageSource.Width;
OutputHeight = AiliaImageSource.Height;
OutputChannel = 1;
break;
}
}
void InputDataProcessing(ImageSegmentaionModels imageSegmentaionModels, Texture inputImage, float[] processedInputBuffer, bool upsideDown = false)
{
float weight = 1;
float bias = 0;
bool rgbRepeats = false;
switch (imageSegmentaionModels)
{
case ImageSegmentaionModels.hair_segmentation:
rgbRepeats = true;
break;
case ImageSegmentaionModels.pspnet_hair_segmentation:
InputDataProcessingPSP(inputImage, processedInputBuffer, upsideDown);
return;
case ImageSegmentaionModels.deeplabv3:
weight = 2;
bias = -1;
break;
default:
break;
}
if (cbuffer == null || cbuffer.count != processedInputBuffer.Length)
{
if (cbuffer != null)
{
cbuffer.Release();
}
cbuffer = new ComputeBuffer(processedInputBuffer.Length, sizeof(float));
}
int kernelIndex;
if (rgbRepeats)
{
if (upsideDown)
{
kernelIndex = channelLastUpsideDownKernel;
}
else
{
kernelIndex = channelLastKernel;
}
}
else
{
if (upsideDown)
{
kernelIndex = channelFirstUpsideDownKernel;
}
else
{
kernelIndex = channelFirstKernel;
}
}
inputDataProcessingShader.SetFloat(computeShaderWeightId, weight);
inputDataProcessingShader.SetFloat(computeShaderBiasId, bias);
inputDataProcessingShader.SetInt(computeShaderWidthId, inputImage.width);
inputDataProcessingShader.SetInt(computeShaderHeightId, inputImage.height);
inputDataProcessingShader.SetTexture(kernelIndex, computeShaderTextureId, inputImage);
inputDataProcessingShader.SetBuffer(kernelIndex, computeShaderResultId, cbuffer);
inputDataProcessingShader.Dispatch(kernelIndex, inputImage.width / 32 + 1, inputImage.height / 32 + 1, 1);
cbuffer.GetData(processedInputBuffer);
}
// Download models and Create ailiaModel
AiliaModel CreateAiliaNet(ImageSegmentaionModels modelType, bool gpu_mode = true)
{
string asset_path = Application.temporaryCachePath;
string serverFolderName = "";
string prototxtName = "";
string onnxName = "";
switch (modelType)
{
case ImageSegmentaionModels.HRNetV2_W18_Small_v2:
serverFolderName = "hrnet";
prototxtName = "HRNetV2-W18-Small-v2.onnx.prototxt";
onnxName = "HRNetV2-W18-Small-v2.onnx";
break;
case ImageSegmentaionModels.HRNetV2_W18_Small_v1:
serverFolderName = "hrnet";
prototxtName = "HRNetV2-W18-Small-v1.onnx.prototxt";
onnxName = "HRNetV2-W18-Small-v1.onnx";
break;
case ImageSegmentaionModels.HRNetV2_W48:
serverFolderName = "hrnet";
prototxtName = "HRNetV2-W48.onnx.prototxt";
onnxName = "HRNetV2-W48.onnx";
break;
case ImageSegmentaionModels.hair_segmentation:
serverFolderName = "hair_segmentation";
prototxtName = "hair_segmentation.opt.onnx.prototxt";
onnxName = "hair_segmentation.opt.onnx";
break;
case ImageSegmentaionModels.pspnet_hair_segmentation:
serverFolderName = "pspnet-hair-segmentation";
prototxtName = "pspnet-hair-segmentation.onnx.prototxt";
onnxName = "pspnet-hair-segmentation.onnx";
break;
case ImageSegmentaionModels.deeplabv3:
serverFolderName = "deeplabv3";
prototxtName = "deeplabv3.opt.onnx.prototxt";
onnxName = "deeplabv3.opt.onnx";
break;
}
ailiaModel = new AiliaModel();
if (gpu_mode)
{
// call before OpenFile
ailiaModel.Environment(Ailia.AILIA_ENVIRONMENT_TYPE_GPU);
}
AiliaDownload ailia_download = new AiliaDownload();
ailia_download.DownloaderProgressPanel = UICanvas.transform.Find("DownloaderProgressPanel").gameObject;
var urlList = new List <ModelDownloadURL>();
urlList.Add(new ModelDownloadURL()
{
folder_path = serverFolderName, file_name = prototxtName
});
urlList.Add(new ModelDownloadURL()
{
folder_path = serverFolderName, file_name = onnxName
});
StartCoroutine(ailia_download.DownloadWithProgressFromURL(urlList, () =>
{
modelPrepared = ailiaModel.OpenFile(asset_path + "/" + prototxtName, asset_path + "/" + onnxName);
}));
return(ailiaModel);
}
