syntax = "proto2";
package mediapipe;
import "mediapipe/framework/calculator.proto";
// Full Example:
//
// node {
// calculator: "TfLiteConverterCalculator"
// input_stream: "IMAGE_IN:input_image"
// output_stream: "TENSOR_OUT:image_tensor"
// options {
// [mediapipe.TfLiteConverterCalculatorOptions.ext] {
// zero_center: true
// }
// }
// }
//
message TfLiteConverterCalculatorOptions {
extend mediapipe.CalculatorOptions {
optional TfLiteConverterCalculatorOptions ext = 245817797;
}
// Choose normalization mode for output (not applied for Matrix inputs).
// true = [-1,1]
// false = [0,1]
// Ignored if using quantization.
optional bool zero_center = 1 [default = true];
// Custom settings to override the internal scaling factors `div` and `sub`.
// Both values must be set to non-negative values. Will only take effect on
// CPU AND when |use_custom_normalization| is set to true. When these custom
// values take effect, the |zero_center| setting above will be overridden, and
// the normalized_value will be calculated as:
// normalized_value = input / custom_div - custom_sub.
optional bool use_custom_normalization = 6 [default = false];
optional float custom_div = 7 [default = -1.0];
optional float custom_sub = 8 [default = -1.0];
// Whether the input image should be flipped vertically (along the
// y-direction). This is useful, for example, when the input image is defined
// with a coordinate system where the origin is at the bottom-left corner
// (e.g., in OpenGL) whereas the ML model expects an image with a top-left
// origin.
optional bool flip_vertically = 2 [default = false];
// Controls how many channels of the input image get passed through to the
// tensor. Valid values are 1,3,4 only. Ignored for iOS GPU.
optional int32 max_num_channels = 3 [default = 3];
// The calculator expects Matrix inputs to be in column-major order. Set
// row_major_matrix to true if the inputs are in row-major order.
optional bool row_major_matrix = 4 [default = false];
// Quantization option (CPU only).
// When true, output kTfLiteUInt8 tensor instead of kTfLiteFloat32.
optional bool use_quantized_tensors = 5 [default = false];
// Normalization option.
// Setting normalization_range results in the values normalized to
// the range [output_tensor_float_range.min, output_tensor_float_range.max].
optional TensorFloatRange output_tensor_float_range = 9;
message TensorFloatRange {
optional float min = 1;
optional float max = 2;
}
}