model.parseResult Method

Parses the raw inference results of some commonly used models, such as classification, SSD, and segmentation models, which are not compiled with Neo. For customized models, you write your own parsing functions.

Request Syntax

import awscam
model = awscam.Model(model_topology_file, loading_config)
raw_infer_result = model.doInference(video_frame)
result = model.parseResult(model_type, raw_infer_result)

Parameters

• model_type—String that identifies the model type to use to generate the inference. Required.

  Valid values: classification, ssd, and segmentation

  Note

  When deploying an SageMaker-trained SSD model, you must first run deploy.py (available from https://github.com/apache/incubator-mxnet/tree/v1.x/example/ssd/) to convert the model artifact into a deployable model. After cloning or downloading the MXNet repository, run the git reset --hard 73d88974f8bca1e68441606fb0787a2cd17eb364 command before calling deploy.py to convert the model, if the latest version does not work.

• raw_infer_result—The output of the function model.doInference(video_frame). Required.

Return Type

• dict

Returns

Returns a dict with a single entry of key-value pair. The key is the model_type value. The value is a list of dict objects. Each of the returned dict objects contains the probability calculated by the model for a specified label. For some model types, such as ssd, the returned dict object also contains other information, such as the location and size of the bounding box the inferred image object is located in.

Sample output:

For the raw inference performed in the Intel DLDT runtime, the parsed inference result on a classification model type has the following format:

{
    "classification":[
        {"label":"318", "prob":0.5},
        {"label":"277", "prob":0.3},
        ...,
        {"label":"433", "prob":0.001}
    ]
}

The corresponding parsed inference result on an ssd model type contains bounding box information and has the following format:

{
    "ssd": [
        {"label": "318", "xmin": 124, "xmax": 245, "ymin": 10,  "ymax": 142, "prob": 0.5},
        {"label": "277", "xmin": 89,  "xmax": 166, "ymin": 233, "ymax": 376, "prob": 0.3},
        ...,
        {"label": "433", "xmin": 355, "xmax": 468, "ymin": 210, "ymax": 266, "prob": 0.001}
    ]
}

For inferences performed in the Neo runtime, the parsed inference result is the same as the raw inference result.