Reset the Meter.

Convenience function for accesssing box coordinates. Returns: a numpy array of shape [N, 4] representing box corners

Accesses data associated with the specified field in the box collection. Args: field: a string parameter used to speficy a related field to

Add a new scalar value to the deque.

Get value by key at specified index (indices) if idx == None, returns value for key at each output index if idx is an integer, return

r"""Fills the input Tensor with values drawn from a truncated normal distribution. The values are effectively drawn from the normal distributi

Calculate the current median value of the deque.

Return number of boxes held in collections.

Add data to a specified field. Args: field: a string parameter used to speficy a related field to be accessed. field_data: a numpy ar

Convenience function for accessing masks. Returns: a numpy array of shape [N, height, width] representing masks

Run 'func' on one or more GPUs, specified in cfg Args: cfg (CfgNode): configs. Details can be found in lib/config/default

Start to record time.

Update the current stats. Args: top1_err (float): top1 error rate. top5_err (float): top5 error rate.

Gather boxes from BoxList according to indices and return new BoxList. By default, gather returns boxes corresponding to the input index list, as

Constructor. Args: categories: A list of dicts, each of which has the following keys - 'id': (required) an integer id uniquely iden

Round width of filters based on width multiplier.

Add multiple scalars to Tensorboard logs. Args: data_dict (dict): key is a string specifying the tag of value.

Stop to record time.

With 50% prob, negate the value

Get path for storing checkpoints. Args: path_to_job (string): the path to the folder of the current job.

Return all non-box fields.

log the stats of the current iteration. Args: cur_epoch (int): the number of current epoch. cur_iter (int): t

ResBlock class constructs redisual blocks. More details can be found in: Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun.

Given scale, ratio, height and width, return sampled coordinates of the videos.

Converts a BoxList containing 'masks' into a BoxMaskList. Args: boxlist: An np_box_list.BoxList object. Returns: An np_box_mask_list.Box

Builds the video model. Args: cfg (configs): configs that contains the hyper-parameters to build the backbone. Details can be

Gather boxes from np_box_mask_list.BoxMaskList according to indices. By default, gather returns boxes corresponding to the input index list, as w

Convert the image to gray scale. Args: image (tensor): image to convert to gray scale. Dimension is `channel` x `height`

Load the checkpoint from the given file. If inflation is True, inflate the 2D Conv weights from the checkpoint to 3D Conv. Args:

Given the arguemnts, load and initialize the configs. Args: args (argument): arguments includes `shard_id`, `num_shards`,

Scale the short side of the image to size. Args: size (int): size to scale the image. image (array): image to perform short s

The `__init__` method of any subclass should also contain these arguments. Args: cfg (CfgNode): model buildi

Calculate and plot confusion matrix to a SummaryWriter. Args: writer (SummaryWriter): the SummaryWriter to write the matrix to.

Add heatmap to 2D tensor. Args: tensor (tensor): a 2D tensor. Tensor value must be in [0..1] range. Returns: heatmap (ten

Adds groundtruth for a single image to be used for evaluation. Args: image_id: A unique string/integer identifier for the image. grou

Computes area of boxes. Args: boxes: Numpy array with shape [N, 4] holding N boxes Returns: a numpy array with shape [N*1] representing

Computes area of masks. Args: masks: Numpy array with shape [N, height, width] holding N masks. Masks values are of type np.uint8 and val

Blend two images with a given weight alpha. Args: images1 (tensor): the first images to be blended, the dimension is `num

Blend two images with a given weight alpha. Args: images1 (tensor): the first images to be blended, the dimension is

Peform crop on the bounding boxes given the offsets. Args: boxes (ndarray or None): bounding boxes to peform crop. The dimension

Evaluate the model on the val set. Args: val_loader (loader): data loader to provide validation data. model (model): mode

Args: cfg (CfgNode): model building configs, details are in the comments of the config file. Returns: nn.Module:

Sample a clip of size clip_size from a video of size video_size and return the indices of the first and last frame of the clip. If clip_idx i

Log the stats of the current epoch. Args: cur_epoch (int): the number of current epoch.

Parse the following arguments for a default parser for PySlowFast users. Args: shard_id (int): shard id for the current machine. Star

Plot confusion matrices and histograms for eval/test set. Args: preds (tensor or list of tensors): list of predictions.

Before every epoch, check if long cycle shape should change. If it should, update cfg accordingly. Args: cfg

The `__init__` method of any subclass should also contain these arguments. Args: dim_in (int): the channel dimension of

Copies the extra fields of boxlist_to_copy_from to boxlist_to_copy_to. Args: boxlist_to_copy_to: BoxList to which extra fields are copied.

Adds detections for a single image to be used for evaluation. Args: image_id: A unique string/integer identifier for the image. detec

Build training model and its associated tools, including optimizer, dataloaders and meters. Args: cfg (CfgNode): configs. Det

Update the stats in bn layers by calculate the precise stats. Args: loader (loader): data loader to provide training data.

Perform center crop on input images. Args: size (int): size of the cropped height and width. image (array): the image to perf

Clears the state to prepare for a fresh evaluation.

Peform crop on the bounding boxes given the offsets. Args: boxes (ndarray or None): bounding boxes to peform crop. The dimension

Evaluates detections and returns a dictionary of metrics.

Filter to keep only boxes and masks with score exceeding a given threshold. This op keeps the collection of boxes and masks whose corresponding sco

Filter to keep only boxes with score exceeding a given threshold. This op keeps the collection of boxes whose corresponding scores are greater th

Obtain all activations from layers that we register hooks for. Args: input (tensors, list of tensors): the model input.

Read json file with entries {classname: index} and return an array of class names in order. If parent_path is provided, load and map all

return info dicts for specified keys (or all if None) at specified indices (or out_indices if None)

Return the targeted layer (nn.Module Object) given a hierarchical layer name, separated by /. Args: model (model): model to get l

Given the configs, retrieve the specified lr policy function. Args: lr_policy (string): the learning rate policy to use for the job.

Compute mAP for multi-label case. Args: preds (numpy tensor): num_examples x num_classes. labels (numpy tensor): num_examples

Compute statistics for the current model given the config. Args: model (model): model to perform analysis. cfg (CfgNode): con

Get the grayscale for the input images. The channels of images should be in order BGR. Args: images (tensor): the input images fo

Get the grayscale for the input images. The channels of images should be in order BGR. Args: images (tensor): the input image

Compute pairwise intersection areas between boxes. Args: boxes1: a numpy array with shape [N, 4] holding N boxes boxes2: a numpy array with

Compute pairwise intersection areas between masks. Args: masks1: a numpy array with shape [N, height, width] holding N masks. Masks value