Find font locally or download to user's configuration directory if it does not already exist. Args: font (str): Path or name of font

Sets mosaic, copy_paste and mixup options to 0.0 and builds transformations.

Sets mosaic, copy_paste and mixup options to 0.0 and builds transformations.

r"""Given the output of the TopDownMap measure, colorizes the map, draws the agent, and fits to a desired output height :param info: The outp

r"""Given the output of the TopDownMap measure, colorizes the map, draws the agent, and fits to a desired output height :param info: The outp

Copies attributes from object 'b' to object 'a', with options to include/exclude certain attributes.

Copies attributes from object 'b' to object 'a', with options to include/exclude certain attributes.

Implement Copy-Paste augmentation https://arxiv.org/abs/2012.07177, labels as nx5 np.array(cls, xyxy).

Implement Copy-Paste augmentation https://arxiv.org/abs/2012.07177, labels as nx5 np.array(cls, xyxy).

Crops bounding boxes to the size of the input image.

Crops bounding boxes to the size of the input image.

Transform distance(ltrb) to box(xywh or xyxy).

Transform distance(ltrb) to box(xywh or xyxy).

Downloads and unzips files concurrently if threads > 1, else sequentially.

Downloads and unzips files concurrently if threads > 1, else sequentially.

https://stackoverflow.com/questions/26690932/opencv-rectangle-with-dotted-or-dashed-lines style: "dotted", "dashed", or "filled"

https://stackoverflow.com/questions/26690932/opencv-rectangle-with-dotted-or-dashed-lines style: "dotted", "dashed", or "filled"

Visualize feature maps of a given model module during inference. Args: x (torch.Tensor): Features to be visualized. module_t

Visualize feature maps of a given model module during inference. Args: x (torch.Tensor): Features to be visualized. module_t

Args: pred_bboxes (torch.Tensor): [l, b, query, 4] pred_scores (torch.Tensor): [l, b, query, num_classes]

Function generates the YOLOv5 network's final layer.

Args: pred_bboxes (torch.Tensor): [l, b, query, 4] pred_scores (torch.Tensor): [l, b, query, num_classes]

Function generates the YOLOv5 network's final layer.

Positionally encode points that are not normalized to [0,1].

Positionally encode points that are not normalized to [0,1].

r"""Instantiate a pretrained pytorch model from a pre-trained model configuration. The model is set in evaluation mode by default using `

r"""Instantiate a pretrained pytorch model from a pre-trained model configuration. The model is set in evaluation mode by default using `

Fuse PyTorch Conv2d and BatchNorm2d layers.

Fuse PyTorch Conv2d and BatchNorm2d layers.

Fuse parallel convolutions.

Fuse parallel convolutions.

Compute gating distance between state distribution and measurements. A suitable distance threshold can be obtained from `chi2inv95`. If

Compute gating distance between state distribution and measurements. A suitable distance threshold can be obtained from `chi2inv95`. If

TensorFlow GraphDef model output node names.

TensorFlow GraphDef model output node names.

Generate video according to specified information. Using a custom verion instead of Habitat's that passes FPS to video maker. Args: v

Generate video according to specified information. Using a custom verion instead of Habitat's that passes FPS to video maker. Args: v

Get the authentication header for making API requests. Returns: (dict): The authentication header if id_token or API key

Get the authentication header for making API requests. Returns: (dict): The authentication header if id_token or API key

r"""Create a unified config with default values. Initialized from the habitat_baselines default config. Overwritten by values from `config_pat

Returns dataloader derived from torch.data.Dataloader.

Returns dataloader derived from torch.data.Dataloader.

Returns the positional encoding used to encode point prompts, applied to a dense set of points the shape of the image encoding.

Returns the positional encoding used to encode point prompts, applied to a dense set of points the shape of the image encoding.

Calculates the distance between tracks and detections using IOU and fuses scores.

Calculates the distance between tracks and detections using IOU and fuses scores.

Return a YOLO model's FLOPs.

Return a YOLO model's FLOPs.

Determines whether the current file is part of a git repository and if so, returns the repository root directory. If the current file is not

Determines whether the current file is part of a git repository and if so, returns the repository root directory. If the current file is not

Returns a single hash value of a list of paths (files or dirs).

Returns a single hash value of a list of paths (files or dirs).

Returns a single hash value of a list of paths (files or dirs).

Returns a single hash value of a list of paths (files or dirs).

Get and return label information from the dataset.

Get and return label information from the dataset.

Get model and raise NotImplementedError for loading cfg files.

Get model and raise NotImplementedError for loading cfg files.

Return the total number of parameters in a YOLO model.

Return the total number of parameters in a YOLO model.

Return set of symbol pairs in a word. Word is represented as tuple of symbols (symbols being variable-length strings).

Return set of symbol pairs in a word. Word is represented as tuple of symbols (symbols being variable-length strings).

Return set of symbol pairs in a word. Word is represented as tuple of symbols (symbols being variable-length strings).