All filename stems of the frames in the sequence

Fetch frames with the given ids. :param sample_id: Sample to get. :param frame_ids: List of frame indices in the sequence belongin

target: (4, )

mask_feats: (bs, 8, h, w) dynamic_params: (bs, n_anchor_all, 169) fpn_levels: (bs, n_anchor_all) masks: (bs, M, H//4,

mask_feats: (bs, 8, h, w) dynamic_params: (bs, n_anchor_all, 169) fpn_levels: (bs, n_anchor_all) masks: (bs, M, H//4,

Compute mean,recall and decay from per-frame evaluation. Arguments: per_frame_values (ndarray): per-frame evaluation Returns:

Args: norm (str or callable): either one of BN, SyncBN, FrozenBN, GN; or a callable that takes a channel number and returns

Number of sequences in a dataset returns: int - number of sequences in the dataset.

All objects in the sequence

Get object pixel counts, grouped by frame names

Overload this in your dataset. Should return the list of sequences in the dataset.

Sequence image shape (h,w)

returns: TensorDict - dict containing all the data blocks

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

Show the tracks on the input image.

Save indexed image as png. Used to save segmentation annotation.

Initialize assigner and sampler.

Initialize ``track_head``

Create track from unassociated measurement. Parameters ---------- measurement : ndarray Bounding box coordinates

Returns the intersection over the area of the predicted box.

Compute cost based on IoU :type atracks: list[STrack] :type btracks: list[STrack] :rtype cost_matrix np.ndarray

check if model is in parallel mode.

Returns whether the dataset is a video dataset or an image dataset returns: bool - True if a video dataset

For each frame in frames, extracts a square crop centered at box_extract, of area search_area_factor^2 times box_extract area. The extracted crop

Lists all the videos in the input set_ids. Returns a list of tuples (set_id, video_name) args: root: Root directory to TrackingNet

Import and load a single dataset.

Load annotation from COCO style annotation file. Args: ann_file (str): Path of annotation file. Returns: lis