Crops face bounding boxes on videos and normalises them by size
Forked from ivana7c/crop_face/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.
Parameters allow users to change the configuration of an algorithm when scheduling an experiment
|normed-height||Height of the face bounding box after size normalization||uint32||64|
|normed-width||Width of the face bounding box after size normalization||uint32||64|
|minimum-face-size||Frames with face bounding box smaller than this will be discarded||uint32||50|
The code for this algorithm in Python
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This algorithm performs pre-processing of the input videos in two steps:
This algorithm relies on the Bob library for cropping and scaling the video frame images.
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.