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