28 lines
1.1 KiB
Markdown
28 lines
1.1 KiB
Markdown
# OpenVINO predict pipeline
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This is an example of simple one step pipeline implementation including OpenVINO predict component.
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It can execute predict operation for a dataset in numpy format and provided model in Intermediate Representation format.
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This format of models can be generated based on trained model from various frameworks like TensorFlow, Caffe, MXNET and Kaldi.
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Dataset in the numpy file needs to match the shape of the provided model input.
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This pipeline execute the predict operation and sends the results for each model output a numpy file with the name
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representing the output tensor name.
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*Note:* Executing this pipeline required building the docker image according to the guidelines on
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[OpenVINO predict component doc](../../../contrib/components/openvino/predict).
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The image name pushed to the docker registry should be configured in the pipeline script `numpy_predict`
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## Examples of the parameters
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model_bin - gs://<path>/model.bin
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model_xml - gs://<path>/model.xml
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input_numpy_file - gs://<path>/datasets/imgs.npy
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output_folder - gs://<path>/outputs
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