detections/_docs/02_document/modules/onnx_engine.md

Module: onnx_engine

Purpose

ONNX Runtime-based inference engine — CPU/CUDA fallback when TensorRT is unavailable.

Public Interface

Class: OnnxEngine (extends InferenceEngine)

Method	Signature	Description
__init__	(bytes model_bytes, int batch_size=1, **kwargs)	Loads ONNX model from bytes, creates InferenceSession with CUDA > CPU provider priority. Reads input shape and batch size from model metadata.
get_input_shape	() -> tuple	Returns (height, width) from input tensor shape
get_batch_size	() -> int	Returns batch size (from model if not dynamic, else from constructor)
run	(input_data) -> list	Runs session inference, returns output tensors

Internal Logic

• Provider order: ["CUDAExecutionProvider", "CPUExecutionProvider"] — ONNX Runtime selects the best available.
• If the model's batch dimension is dynamic (-1), uses the constructor's batch_size parameter.
• Logs model input metadata and custom metadata map at init.

Dependencies

• External: onnxruntime
• Internal: inference_engine (base class), constants_inf (logging)

Consumers

• inference — instantiated when no compatible NVIDIA GPU is found

Data Models

None (wraps onnxruntime.InferenceSession).

Configuration

None.

External Integrations

None directly — model bytes are provided by caller (loaded via loader_http_client).

Security

None.

Tests

None found.