Classes | Functions
generate_detections Namespace Reference

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

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

Definition at line 10 of file generate_detections.py.

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

Definition at line 99 of file generate_detections.py.

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.

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.

def generate_detections.main ( void  )

Definition at line 205 of file generate_detections.py.

def generate_detections.parse_args ( )
Parse command line arguments.

Definition at line 184 of file generate_detections.py.



jsk_perception
Author(s): Manabu Saito, Ryohei Ueda
autogenerated on Mon May 3 2021 03:03:27