TF Evaluate MNIST
This operator is an extension of the python27 operator. It runs tensorflow code that applies a previously trained model (loaded from disk) to an image message stream.
The resulting program infers the numbers from each handwriting picture, which is
based on the MNIST example https://www.tensorflow.org/tutorials/layers
Prerequisites
-
MNIST model (type binary, default: None): A pretrained MNIST model (including metadata) that was created with the experimental.ml.tensorflow.trainMnist operator (that is, artifacts prefixed with "model.ckpt" that were created with a tf.train.Saver in the repository under modeldir).
-
MNIST image (type binary, default: None): An input stream of MNIST png- or jpg- images in the correct pixel size (28x28).
Configuration Parameters
|
Parameter |
Type |
Description |
|---|---|---|
| demo | bool | Introduces additional time between each evaluation
step.
Default: true |
| logging | bool | Activate log output.
Default: true |
|
tmpdir |
string |
Contains the tmpdir parameter. Default: "/tmp/tensorflow" |
Input
|
Input |
Type |
Description |
|---|---|---|
|
inModelBlob |
blob |
It takes the model from a blob type, which will be internally translated into a python.str type. |
|
inFilename |
string |
The filename is only used for the json output. |
|
inFile |
message |
The input images are stored in a python message type. |
Output
|
Output |
Type |
Description |
|---|---|---|
|
jsonResult |
string |
Classification results separated by the newline command in a json format (image_path,result). #* |
|
stderr |
stream.base64.* |
The output frames in base64-encoded image format. |