libreyolo.LIBREYOLOOnnx

class libreyolo.LIBREYOLOOnnx[source]

Bases: object

ONNX runtime inference backend for LIBREYOLO models.

Provides the same API as LIBREYOLO8/LIBREYOLO11 but uses ONNX Runtime instead of PyTorch for inference.

Parameters:

  • onnx_path – Path to the ONNX model file.

  • nb_classes – Number of classes (default: 80 for COCO).

  • device – Device for inference. “auto” (default) uses CUDA if available, else CPU.

Example

>>> model = LIBREYOLOOnnx("model.onnx")
>>> detections = model("image.jpg", save=True)
__init__(onnx_path, nb_classes=80, device='auto')[source]
Parameters:

  • onnx_path (str)

  • nb_classes (int)

  • device (str)

Methods

__init__(onnx_path[, nb_classes, device])

predict(image[, save, output_path, ...])

Alias for __call__ method.
__init__(onnx_path, nb_classes=80, device='auto')[source]
Parameters:

  • onnx_path (str)

  • nb_classes (int)

  • device (str)

__call__(image, save=False, output_path=None, conf_thres=0.25, iou_thres=0.45, color_format='auto', batch_size=1)[source]

Run inference on an image or directory of images.

Parameters:

  • image (str | Path | Image | ndarray) – Input image or directory (file path, directory path, PIL Image, or numpy array).

  • save (bool) – If True, saves annotated image to disk.

  • output_path (str) – Optional path to save the annotated image.

  • conf_thres (float) – Confidence threshold (default: 0.25).

  • iou_thres (float) – IoU threshold for NMS (default: 0.45).

  • color_format (str) – Color format hint for NumPy/OpenCV arrays (“auto”, “rgb”, “bgr”).

  • batch_size (int) – Number of images to process per batch when handling multiple images (e.g., directories). Currently used for chunking at the Python level; true batched model inference is planned for future versions. Default: 1 (process one image at a time).

Returns:

Dictionary with boxes, scores, classes, source, and num_detections. For directory: List of dictionaries, one per image processed.

Return type:

For single image

predict(image, save=False, output_path=None, conf_thres=0.25, iou_thres=0.45, color_format='auto', batch_size=1)[source]

Alias for __call__ method.

Parameters:

  • image (str | Path | Image | ndarray) – Input image or directory.

  • save (bool) – If True, saves annotated image to disk.

  • output_path (str) – Optional path to save the annotated image.

  • conf_thres (float) – Confidence threshold (default: 0.25).

  • iou_thres (float) – IoU threshold for NMS (default: 0.45).

  • color_format (str) – Color format hint for NumPy/OpenCV arrays.

  • batch_size (int) – Number of images to process per batch when handling multiple images (e.g., directories). Default: 1.

Returns:

Dictionary containing detection results. For directory: List of dictionaries, one per image processed.

Return type:

For single image