export declare const modelConfigure: import("@alwaysai/alwayscli/lib/types").CliLeaf, { name: import("@alwaysai/alwayscli").CliInput; framework: import("@alwaysai/alwayscli").CliInput<"tensorflow" | "caffe" | "enet" | "darknet" | "onnx" | "tensor-rt" | "hailo" | "qaic" | "torch", true>; model_file: import("@alwaysai/alwayscli").CliInput; mean: import("@alwaysai/alwayscli").CliInput; scalefactor: import("@alwaysai/alwayscli").CliInput; size: import("@alwaysai/alwayscli").CliInput; purpose: import("@alwaysai/alwayscli").CliInput<"ObjectDetection" | "InstanceSegmentation" | "Classification" | "PoseEstimation" | "SemanticSegmentation" | "ReIdentification", true>; crop: import("@alwaysai/alwayscli").CliInput; config_file: import("@alwaysai/alwayscli").CliInput; label_file: import("@alwaysai/alwayscli").CliInput; colors_file: import("@alwaysai/alwayscli").CliInput; swaprb: import("@alwaysai/alwayscli").CliInput; softmax: import("@alwaysai/alwayscli").CliInput; batch_size: import("@alwaysai/alwayscli").CliInput; output_layer_names: import("@alwaysai/alwayscli").CliInput; device: import("@alwaysai/alwayscli").CliInput<"xavier-nx" | "agx-xavier" | "agx-orin" | "orin-nx" | undefined, false>; architecture: import("@alwaysai/alwayscli").CliInput<"yolov3" | "yolov4" | "mobilenet_ssd" | "centernet" | "detr" | "yolo_x" | "rtdetr" | "yolo" | undefined, false>; quantize_input: import("@alwaysai/alwayscli").CliInput; quantize_output: import("@alwaysai/alwayscli").CliInput; input_format: import("@alwaysai/alwayscli").CliInput<"auto" | "none" | "float32" | "uint8" | "uint16" | undefined, false>; output_format: import("@alwaysai/alwayscli").CliInput<"auto" | "none" | "float32" | "uint8" | "uint16" | undefined, false>; }, import("@alwaysai/alwayscli").CliInput>; //# sourceMappingURL=configure.d.ts.map