Classes
class	ImageEncoder

Functions
def	_run_in_batches (f, data_dict, out, batch_size)

def	create_box_encoder (model_filename, input_name="images", output_name="features", batch_size=32)

def	extract_image_patch (image, bbox, patch_shape)

def	generate_detections (encoder, mot_dir, output_dir, detection_dir=None)

def	main ()

def	parse_args ()

Function Documentation

◆ _run_in_batches()

def generate_detections._run_in_batches	(	f,
		data_dict,
		out,
		batch_size
	)

private

Definition at line 10 of file generate_detections.py.

◆ create_box_encoder()

def generate_detections.create_box_encoder	(	model_filename,
		input_name = `"images"`,
		output_name = `"features"`,
		batch_size = `32`
	)

Definition at line 98 of file generate_detections.py.

◆ extract_image_patch()

def generate_detections.extract_image_patch	(	image,
		bbox,
		patch_shape
	)

Extract image patch from bounding box.

Parameters
----------
image : ndarray
    The full image.
bbox : array_like
    The bounding box in format (x, y, width, height).
patch_shape : Optional[array_like]
    This parameter can be used to enforce a desired patch shape
    (height, width). First, the `bbox` is adapted to the aspect ratio
    of the patch shape, then it is clipped at the image boundaries.
    If None, the shape is computed from :arg:`bbox`.

Returns
-------
ndarray | NoneType
    An image patch showing the :arg:`bbox`, optionally reshaped to
    :arg:`patch_shape`.
    Returns None if the bounding box is empty or fully outside of the image
    boundaries.

Definition at line 24 of file generate_detections.py.

◆ generate_detections()

def generate_detections.generate_detections	(	encoder,
		mot_dir,
		output_dir,
		detection_dir = `None`
	)

Generate detections with features.

Parameters
----------
encoder : Callable[image, ndarray] -> ndarray
    The encoder function takes as input a BGR color image and a matrix of
    bounding boxes in format `(x, y, w, h)` and returns a matrix of
    corresponding feature vectors.
mot_dir : str
    Path to the MOTChallenge directory (can be either train or test).
output_dir
    Path to the output directory. Will be created if it does not exist.
detection_dir
    Path to custom detections. The directory structure should be the default
    MOTChallenge structure: `[sequence]/det/det.txt`. If None, uses the
    standard MOTChallenge detections.

Definition at line 118 of file generate_detections.py.

◆ main()

def generate_detections.main ( )

Definition at line 205 of file generate_detections.py.

◆ parse_args()

def generate_detections.parse_args ( )

Parse command line arguments.

Definition at line 184 of file generate_detections.py.

Classes