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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. | |
""" | |
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] | |