- class flash.video.classification.model.VideoClassifier(num_classes, backbone='x3d_xs', backbone_kwargs=None, pretrained=True, loss_fn=torch.nn.functional.cross_entropy, optimizer='SGD', lr_scheduler=None, metrics=torchmetrics.Accuracy, learning_rate=0.001, head=None, output=None)¶
Task that classifies videos.
None]) – Metrics to compute for training and evaluation. Can either be an metric from the torchmetrics package, a custom metric inherenting from torchmetrics.Metric, a callable function or a list/dict containing a combination of the aforementioned. In all cases, each metric needs to have the signature metric(preds,target) and return a single scalar tensor. Defaults to
None]) – either a nn.Module or a callable function that converts the features extrated from the backbone into class log probabilities (assuming default loss function). If None, will default to using a single linear layer.