Takes the template and probe features from two datasets and feeds them from one group

This algorithm is a sequential one. The platform will call its process() method once per data incoming on its inputs.

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.

Group: probe

Endpoint Name Data Format Nature
client_id system/uint64/1 Input
image system/array_2d_uint8/1 Input
template_ids system/array_1d_uint64/1 Input
is_positive system/boolean/1 Output
probe_image system/array_2d_uint8/1 Output
template_images system/array_3d_uint8/1 Output

Group: template

Endpoint Name Data Format Nature
template_id system/uint64/1 Input
template_image system/array_2d_uint8/1 Input

The code for this algorithm in Python
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Could not find any documentation for this object.


Updated Name Databases/Protocols Analyzers
amohammadi/amohammadi/atnt_facenet/1/atnt_facenet_1 atnt/5@idiap,facenet-20170512-110547/1@facenet-20170512-110547 amohammadi/eer_analyzer/1
amohammadi/amohammadi/atnt_eigenfaces/1/atnt1 atnt/6@idiap amohammadi/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.

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