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import os
import torch
import torchvision
from ultralytics import YOLO
def build_model(nclasses: int = 2, mode: str = None, segment_model: str = None):
"""
@param[in] nclasses
@param[in] mode set mode for frame classification or uninformative part mask
"""
if mode == 'classify':
#net of Resnet18
net = torchvision.models.resnet18(num_classes = nclasses)
net.cuda()
if mode == 'mask':
net = YOLO(segment_model)
return net
net = build_model(nclasses=num_classes, mode='classify')
model_path = 'Video storyboard classification models'
# Enable multi-GPU support
net = torch.nn.DataParallel(net)
torch.backends.cudnn.benchmark = True
state = torch.load(model_path, map_location=torch.device('cuda'))
net.load_state_dict(state['net'])
net.eval()
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