TensorFlow Images Processor
The TensorFlow Images processor feeds images to a TensorFlow model you've already created and trained.
Why use the TensorFlow Images processor
Use this processor when your analytics flow needs to pass image data, rather than time-series values, into a TensorFlow model, for example, running an existing image-classification model against images captured on the factory floor.
How it works
Point Model Path at your trained TensorFlow model. Tags, Input Operation, and Output Operation must match the names used when the model was created: Tags identifies which model to load if there's more than one, and Input Operation and Output Operation identify the tensors the model expects as input and returns as output.
Use Gray to control whether images are processed in grayscale or color, and Image Format to specify the incoming images' format. Time Shift Ms shifts the output's timestamp by the specified number of milliseconds.
Parameters
Parameter | Details |
|---|---|
Model Path | The file path of the pre-trained TensorFlow model. |
Tags | Tags for loading the model. Separate multiple tags with commas. |
Input Operation | The input tensor used when the model was created, usually the dictionary of values fed to the model. |
Output Operation | The output tensor used when the model was created, usually the model's output. |
Gray | Whether images are processed in grayscale or color. |
Image Format | The format of the input images, JPG or PNG. |
Time Shift Ms | How many milliseconds to shift the current timestamp by. |
Pass Through Value | Determines whether the processor's output is the model's result or the original unchanged input value. |