Creates a histogram model for a group of samples by averaging their feature vector histograms
Forked from ivana7c/make_hist_model/1
Algorithms have at least one input and one output. All algorithm endpoints are organized in groups. Groups are used by the platform to indicate which inputs and outputs are synchronized together. The first group is automatically synchronized with the channel defined by the block in which the algorithm is deployed.
| Endpoint Name | Data Format | Nature |
|---|---|---|
| labels | system/text/1 | Input |
| feature_vectors | system/array_1d_floats/1 | Input |
| model_hist | system/array_1d_floats/1 | Output |
The code for this algorithm in Python
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This algorithm creates a histogram model for a group of samples. For example, these samples can be real od attack samples in an anti-spoofing scenario. The input assumes sample feature vectors which are histograms. The model is created simpy by averaging the input histograms.
| Updated | Name | Databases/Protocols | Analyzers | |||
|---|---|---|---|---|---|---|
| smarcel/ivana7c/simple-antispoofing-updated/1/replay2-antispoofing-lbp-histograms-fix | replay/3@grandtest | Kanma/iqm_spoof_eer_analyzer/1 |
This table shows the number of times this algorithm has been successfully run using the given environment. Note this does not provide sufficient information to evaluate if the algorithm will run when submitted to different conditions.