This algorithm performs a RGB to gray conversion followed by a face cropping
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 |
|---|---|---|
| image | system/array_3d_uint8/1 | Input |
| eye_centers | system/eye_positions/1 | Input |
| cropped_image | system/array_2d_uint8/1 | Output |
Parameters allow users to change the configuration of an algorithm when scheduling an experiment
| Name | Description | Type | Default | Range/Choices |
|---|---|---|---|---|
| crop-height | uint32 | 80 | ||
| crop-width | uint32 | 64 | ||
| right-eye-y | uint32 | 16 | ||
| right-eye-x | uint32 | 15 | ||
| left-eye-y | uint32 | 16 | ||
| left-eye-x | uint32 | 48 |
The code for this algorithm in Python
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This algorithm performs a RGB to grayscale conversion of an image followed by a face cropping, given the eye center coordinates.
This implementation relies on the Bob library.
The inputs are:
The output cropped_image is a grayscale cropped image as a two-dimensional array of floats (64 bits).
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.