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65 lines
2.0 KiB
65 lines
2.0 KiB
from typing import Union
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from roboflow import Roboflow
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from swarms.models.base_multimodal_model import BaseMultiModalModel
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class RoboflowMultiModal(BaseMultiModalModel):
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"""
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Initializes the RoboflowModel with the given API key, project ID, and version.
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Args:
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api_key (str): The API key for Roboflow.
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project_id (str): The ID of the project.
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version (str): The version of the model.
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confidence (int, optional): The confidence threshold. Defaults to 50.
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overlap (int, optional): The overlap threshold. Defaults to 25.
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"""
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def __init__(
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self,
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api_key: str,
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project_id: str,
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version: str,
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confidence: int = 50,
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overlap: int = 25,
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hosted: bool = False,
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*args,
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**kwargs,
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):
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super().__init__(*args, **kwargs)
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self.api_key = api_key
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self.project_id = project_id
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self.verison = version
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self.confidence = confidence
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self.overlap = overlap
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self.hosted = hosted
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try:
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rf = Roboflow(api_key=api_key, *args, **kwargs)
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project = rf.workspace().project(project_id)
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self.model = project.version(version).model
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self.model.confidence = confidence
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self.model.overlap = overlap
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except Exception as e:
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print(f"Error initializing RoboflowModel: {str(e)}")
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def __call__(self, img: Union[str, bytes]):
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"""
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Runs inference on an image and retrieves predictions.
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Args:
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img (Union[str, bytes]): The path to the image or the URL of the image.
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hosted (bool, optional): Whether the image is hosted. Defaults to False.
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Returns:
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Optional[roboflow.Prediction]: The prediction or None if an error occurs.
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"""
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try:
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prediction = self.model.predict(img, hosted=self.hosted)
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return prediction
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except Exception as e:
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print(f"Error running inference: {str(e)}")
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return None
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