Samples#

Get ONNX models from ONNX Model Zoo

Sample - SqueezeNet#

  • Download the SqueezeNet ONNX Model

  • Use Netron to open the model.onnx

    • Look at Model Properties to find Input & Output Tensor Name (data_0 - input; softmaxout_1 - output)

    • Look at output tensor dimensions (n,c,h,w - [1,1000,1,1] for softmaxout_1)

  • Use the label file - data\Labels.txt and sample image - data\car.JPEG to run samples

winML-image.gdf - Single Image Inference#

This sample is in Graph Description Format (gdf)

usage#

runvx.exe -v winML-image.gdf

NOTE: Make the below changes in the winML-image.gdf file to run the inference

  • Add full path to the data\car.JPEG image provided in this folder in line 11

read input_image FULL_PATH_TO\data\car.JPEG

  • Add full path to the SqueezeNet ONNX model downloaded in line 21

data modelLocation = scalar:STRING,FULL_PATH_TO\squeezenet\model.onnx:view,resultWindow

data labelLocation = scalar:STRING,FULL_PATH_TO\data\Labels.txt

winML-live.gdf - Live Inference using a camera#

This sample is in Graph Description Format (gdf)

usage#

runvx.exe -frames:LIVE winML-live.gdf

NOTE: Make the below changes in the winML-live.gdf file to run the inference

  • Add full path to the SqueezeNet ONNX model downloaded in line 16

data modelLocation = scalar:STRING,FULL_PATH_TO\squeezenet\model.onnx:view,resultWindow

data labelLocation = scalar:STRING,FULL_PATH_TO\data\Labels.txt

winML-Live-MultipleModels.gdf - Live Inference using a camera#

This sample is in Graph Description Format (gdf)

usage#

runvx.exe -frames:LIVE winML-Live-MultipleModels.gdf

NOTE: Make the below changes in the winML-Live-MultipleModels.gdf file to run the inference

  • Add full path to the VGG19 ONNX model downloaded in line 17

data modelLocation_vgg = scalar:STRING,FULL_PATH_TO\vgg19\model.onnx:view,resultWindow

  • Add full path to the SqueezeNet ONNX model downloaded in line 31

data modelLocation_squeezenet = scalar:STRING,FULL_PATH_TO\squeezenet\model.onnx:view,resultWindow

data labelLocation = scalar:STRING,FULL_PATH_TO\data\Labels.txt

Sample - FER+ Emotion Recognition#

  • Download the FER+ Emotion Recognition ONNX Model

  • Use Netron to open the model.onnx

    • Look at Model Properties to find Input & Output Tensor Name (Input3 - input; Plus692_Output_0 - output)

    • Look at output tensor dimensions (n,c,h,w - [1,8] for Plus692_Output_0)

  • Use the label file - data/emotions.txt to run sample

This sample is in Graph Description Format (gdf)

usage#

runvx.exe -frames:LIVE winML-live-emotions.gdf

NOTE: Make the below changes in the winML-live-emotions.gdf file to run the inference

  • Add full path to the FER+ Emotion Recognition ONNX model downloaded in line 16

data modelLocation = scalar:STRING,FULL_PATH_TO\emotion_ferplus\model.onnx:view,inputImageWindow

  • Add full path to the data\emotions.txt provided in this folder in line 25

data labelLocation = scalar:STRING,FULL_PATH_TO\data\emotions.txt

Sample - VGG19#

  • Download the VGG-19 ONNX Model

  • Use Netron to open the model.onnx

    • Look at Model Properties to find Input & Output Tensor Name (data_0 - input; prob_1 - output)

    • Look at output tensor dimensions (n,c,h,w - [1,1000] for prob_1)

  • Use the label file - data/Labels.txt to run sample

This sample is in Graph Description Format (gdf)

usage#

runvx.exe -v winML-image-vgg19.gdf

NOTE: Make the below changes in the winML-live-vgg19.gdf file to run the inference

  • Add full path to the data\bird.JPEG image provided in this folder in line 11

read input_image FULL_PATH_TO\data\bird.JPEG

  • Add full path to the VGG 19 ONNX model downloaded in line 21

data modelLocation = scalar:STRING,FULL_PATH_TO\vgg19\model.onnx:view,resultWindow

data labelLocation = scalar:STRING,FULL_PATH_TO\data\Labels.txt