Return a video writer object. Args: path (str): path to the output video file. fps (int or float): frames per

Return a video writer object. Args: path (str): path to the output video file.

Get parameters for ``crop`` for a random sized crop. Args: img (PIL Image): Image to be cropped. scale (tuple): range

Get the full path to a checkpoint file. Args: path_to_job (string): the path to the folder of the current job. step (int): th

Get the full path to a checkpoint file. Args: path_to_job (string): the path to the folder of the current job. epoch (int): t

Get the full path to a checkpoint file. Args: path_to_job (string): the path to the folder of the current job. epoch (int): t

Get the full path to a checkpoint file. Args: path_to_job (string): the path to the folder of the current job. epoch (int): t

Predict and append prediction results to each box in each keyframe in `self.pred_boxes` dictionary.

Get the rank of the current process.

Given the video index, return the list of indexs of sampled frames. Args: index (int): the video index. Returns:

Sample frames among the corresponding clip. Args: center_idx (int): center frame idx for current clip half_len (int): half o

Retrieves the stem module by name.

Retrieves the lr step index for the given epoch. Args: cfg (CfgNode): configs. Details can be found in slowfast/config/de

Retrieves the transformation module by name.

Returns weights from registered layers. Returns: weights (Python dictionary): a dictionary of the pair {layer

Get the size of the world.

Compute the GPU memory usage for the current device (GB).

Inflate 2D model weights in state_dict_2d to the 3D model weights in state_dict_3d. The details can be found in: Joao Carreira, and Andre

Inflate 2D model weights in state_dict_2d to the 3D model weights in state_dict_3d. The details can be found in: Joao Carreira, and Andre

Inflate 2D model weights in state_dict_2d to the 3D model weights in state_dict_3d. The details can be found in: Joao Carreira, and Andre

Inflate 2D model weights in state_dict_2d to the 3D model weights in state_dict_3d. The details can be found in: Joao Carreira, and Andre

Update cfg based on multigrid settings. Args: cfg (configs): configs that contains training and multigrid specific

Computes pairwise intersection-over-area between box and mask collections. Intersection-over-area (ioa) between two masks mask1 and mask2 is defi

Computes pairwise intersection-over-area between box collections. Intersection-over-area (ioa) between two boxes box1 and box2 is defined as

Loading boxes and labels from AVA bounding boxes csv files. Args: cfg (CfgNode): config. video_name (str): name of the given

Prepares the image for network input with format of CHW RGB float

Main function to spawn the train and test process.

Main function to spawn the train and test process.

Calculate the median epoch time among the recorded epochs.

This function converts target class indices to one-hot vectors, given the number of classes. Args: targets (loader): Class labels

Non maximum suppression. This op greedily selects a subset of detection bounding boxes, pruning away boxes that have high IOU (intersection o

Non maximum suppression. This op greedily selects a subset of detection bounding boxes, pruning away boxes that have high IOU (intersection o

Convert BN parameters to Sub-BN parameters if model contains Sub-BNs. Args: checkpoint_sd (OrderedDict): source dict of parameters.

Convert BN parameters to Sub-BN parameters if model contains Sub-BNs. Args: checkpoint_sd (OrderedDict): source dict of parameters.

Convert BN parameters to Sub-BN parameters if model contains Sub-BNs. Args: checkpoint_sd (OrderedDict): source dict of parameters.

Convert BN parameters to Sub-BN parameters if model contains Sub-BNs. Args: checkpoint_sd (OrderedDict): source dict of parameters.

Pad the given image with the size of pad_size. Args: image (array): image to pad. pad_size (int): size to pad. order

Compute the number of parameters. Args: model (model): model to count the number of parameters.

For classification: Perform mutli-view testing that uniformly samples N clips from a video along its temporal axis. For each clip, it tak

Given all predictions and all true labels, plot histograms of top-k most frequently predicted classes for each true class. Args:

Visualize weights/ activations tensors to Tensorboard. Args: weight_activation_dict (dict[str, tensor]): a dictionary of

Log schedule.

Extract layer names and numpy-like fancy indexing from a string. Args: layer_ls (list of strs): list of strings containing data about

Add the new task to task queue. Args: task (TaskInfo object): task object that contain the necessary info

Convert the video from its original fps to the target_fps. If the video support selective decoding (contain decoding information in the video

Decode the video with PyAV decoder. Args: container (container): PyAV container. start_pts (int): the starting Presentation T

Generates a random square bbox based on lambda value. Args: img_shape (tuple): Image shape as tuple lam (float): Cutmix lamb

Reset the metric.

Reset the metric.

Run model visualization (weights, activations and model inputs) and visualize them on Tensorboard. Args: vis_loader (loader): vid

Perform color saturation on the given image. Args: var (float): variance. image (array): image to perform color saturation.

Perfrom saturation jittering on the input images. The channels of images should be in order BGR. Args: var (float): jitter ratio

Perform color saturation on the list of given images. Args: var (float): variance. images (list): list of images to perform c

Scale box coordinates in x and y dimensions. Args: boxlist: BoxList holding N boxes y_scale: float x_scale: float Returns:

Scale the short side of the box to size. Args: size (int): size to scale the image. boxes (ndarray): bounding boxes to peform

Convert time index (in second) to frame index. 0: 900 30: 901

Sort boxes and associated fields according to a scalar field. A common use case is reordering the boxes according to descending scores. Args

Convert the Sub-BN paprameters to normal BN parameters in a state dict. There are two copies of BN layers in a Sub-BN implementation: `bn.bn`

Given the start and end frame index, sample num_samples frames between the start and end with equal interval. Args: frames (tenso

Normalize a given tensor by subtracting the mean and dividing the std. Args: tensor (tensor): tensor to normalize. mean (tens

If video_meta is not empty, perform temporal selective decoding to sample a clip from the video with TorchVision decoder. If video_meta is em

Perform the video training for one epoch. Args: train_loader (loader): video training loader. model (model): the video model

If separate==True, the transforms are returned as a tuple of 3 separate transforms for use in a mixing dataset that passes * all data th

Update predictions and labels. Args: preds (tensor): model output predictions. labels (tensor): labels.

Transpose the dimension from `channel` x `height` x `width` to `height` x `width` x `channel`. Args: image (array): image to

Transpose the dimension from `height` x `width` x `channel` to `channel` x `height` x `width`. Args: image (array): image to

Construct PyTorchVideo Charades video loader. Load Charades data (frame paths, labels, etc. ) to Charades Dataset object. The dataset cou

Construct the Kinetics video loader with a given csv file. The format of the csv file is: ``` path_to_video_1 label_1 path_to_vid

Construct PyTorchVideo Something-Something v2 SSv2 video loader. Load SSv2 data (frame paths, labels, etc. ) to SSv2 Dataset object. The

How many results are ready to be returned.

Returns the prediction results for the current task. Args: task (TaskInfo object): task object that contain

Visualize the localization maps on their corresponding inputs as heatmap, using Grad-CAM. Args: inputs (list of t

Args: img (PIL Image): Image to be cropped and resized. Returns: PIL Image: Randomly cropped and resized imag

Given the video index, return the list of frames, label, and video index if the video can be fetched and decoded successfully, otherw

Given the video index, return the list of frames, label, and video index if the video can be fetched and decoded successfully, otherw

Generate corresponding clips, boxes, labels and metadata for given idx. Args: idx (int): the video index provided by the

Given the video index, return the list of frames, label, and video index if the video can be fetched and decoded successfully, otherw

Given the video index, return the list of frames, label, and video index if the video can be fetched and decoded successfully, otherw

Given the video index, return the list of frames, label, and video index if the video frames can be fetched. Args:

Given the video index, return the list of frames, label, and video index if the video frames can be fetched. Args: