101 lines
3.3 KiB
Python
101 lines
3.3 KiB
Python
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"""File for accessing YOLOv5 via PyTorch Hub https://pytorch.org/hub/
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Usage:
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import torch
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model = torch.hub.load('ultralytics/yolov5', 'yolov5s', pretrained=True, channels=3, classes=80)
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"""
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dependencies = ['torch', 'yaml']
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import os
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import torch
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from models.yolo import Model
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from utils import google_utils
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def create(name, pretrained, channels, classes):
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"""Creates a specified YOLOv5 model
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Arguments:
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name (str): name of model, i.e. 'yolov5s'
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pretrained (bool): load pretrained weights into the model
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channels (int): number of input channels
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classes (int): number of model classes
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Returns:
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pytorch model
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"""
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config = os.path.join(os.path.dirname(__file__), 'models', '%s.yaml' % name) # model.yaml path
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try:
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model = Model(config, channels, classes)
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if pretrained:
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ckpt = '%s.pt' % name # checkpoint filename
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google_utils.attempt_download(ckpt) # download if not found locally
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state_dict = torch.load(ckpt, map_location=torch.device('cpu'))['model'].float().state_dict() # to FP32
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state_dict = {k: v for k, v in state_dict.items() if model.state_dict()[k].shape == v.shape} # filter
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model.load_state_dict(state_dict, strict=False) # load
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return model
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except Exception as e:
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help_url = 'https://github.com/ultralytics/yolov5/issues/36'
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s = 'Cache maybe be out of date, deleting cache and retrying may solve this. See %s for help.' % help_url
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raise Exception(s) from e
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def yolov5s(pretrained=False, channels=3, classes=80):
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"""YOLOv5-small model from https://github.com/ultralytics/yolov5
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Arguments:
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pretrained (bool): load pretrained weights into the model, default=False
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channels (int): number of input channels, default=3
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classes (int): number of model classes, default=80
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Returns:
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pytorch model
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"""
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return create('yolov5s', pretrained, channels, classes)
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def yolov5m(pretrained=False, channels=3, classes=80):
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"""YOLOv5-medium model from https://github.com/ultralytics/yolov5
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Arguments:
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pretrained (bool): load pretrained weights into the model, default=False
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channels (int): number of input channels, default=3
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classes (int): number of model classes, default=80
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Returns:
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pytorch model
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"""
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return create('yolov5m', pretrained, channels, classes)
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def yolov5l(pretrained=False, channels=3, classes=80):
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"""YOLOv5-large model from https://github.com/ultralytics/yolov5
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Arguments:
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pretrained (bool): load pretrained weights into the model, default=False
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channels (int): number of input channels, default=3
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classes (int): number of model classes, default=80
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Returns:
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pytorch model
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"""
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return create('yolov5l', pretrained, channels, classes)
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def yolov5x(pretrained=False, channels=3, classes=80):
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"""YOLOv5-xlarge model from https://github.com/ultralytics/yolov5
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Arguments:
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pretrained (bool): load pretrained weights into the model, default=False
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channels (int): number of input channels, default=3
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classes (int): number of model classes, default=80
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Returns:
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pytorch model
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"""
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return create('yolov5x', pretrained, channels, classes)
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