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s = 'Cache maybe be out of date, deleting cache and retrying may solve this.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