OMG / inference /models /yolov5 /yolov5_instance_segmentation.py
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from typing import List, Tuple
import numpy as np
from inference.core.models.instance_segmentation_base import (
InstanceSegmentationBaseOnnxRoboflowInferenceModel,
)
class YOLOv5InstanceSegmentation(InstanceSegmentationBaseOnnxRoboflowInferenceModel):
"""YOLOv5 Instance Segmentation ONNX Inference Model.
This class is responsible for performing instance segmentation using the YOLOv5 model
with ONNX runtime.
Attributes:
weights_file (str): Path to the ONNX weights file.
"""
@property
def weights_file(self) -> str:
"""Gets the weights file for the YOLOv5 model.
Returns:
str: Path to the ONNX weights file.
"""
return "yolov5s_weights.onnx"
def predict(self, img_in: np.ndarray, **kwargs) -> Tuple[np.ndarray, np.ndarray]:
"""Performs inference on the given image using the ONNX session.
Args:
img_in (np.ndarray): Input image as a NumPy array.
Returns:
Tuple[np.ndarray, np.ndarray]: Tuple containing two NumPy arrays representing the predictions.
"""
predictions = self.onnx_session.run(None, {self.input_name: img_in})
return predictions[0], predictions[1]