size mismatch for classifier.4.weight: copying a param with shape torch.Size([7, 256]) from checkpoint, the shape in current model is torch.Size([751, 256]).
size mismatch for classifier.4.bias: copying a param with shape torch.Size([7]) from checkpoint, the shape in current model is torch.Size([751]).

Training the tracking weight of deepsort. The default data set is market1501. Replace it with your own data set. Test the weight and report an error. As above, change the num_Class in model.py is changed to the number of its own classes. (for example, my num_class is 7, and market1501 defaults to 751.)

class Net(nn.Module):
    def __init__(self, num_classes=751, reid=False):#Change the number of training classes