Get inverse affine matrix.

Function: ---------- Find Similarity Transform Matrix 'cv2_trans' which could be directly used by cv2.warpAffine():

data ： dic configs

Initialize the dlib detectors and predictors.

We resize both tensors to [A,B,2] without new malloc: [A,2] -> [A,1,2] -> [A,B,2] [B,2] -> [1,B,2] -> [A,B,2] Then we compute the area of

Compute the jaccard overlap of two sets of boxes. The jaccard overlap is simply the intersection over union of two boxes. Here we operate on

load the mel filterbank matrix for projecting STFT into a Mel spectrogram. Allows decoupling librosa dependency; saved using: np.sav

Merge operation described in paper

Performs Non-Maximum Suppression (NMS) on inference results Returns: detections with shape: nx6 (x1, y1, x2, y2, conf, cls)

Compute number of time frames of spectrogram

Convert prior_boxes to (xmin, ymin, xmax, ymax) representation for comparison to point form ground truth data. Args: boxes: (tensor)

img can be image path or cv2 loaded image.

Shuffle the points left-right according to the axis of symmetry of the object. Arguments: parts {torch.tensor} -- a 3D or 4D object c

Convert path (represented as a string) or torch.tensor to a numpy.ndarray Arguments: tensor_or_path {numpy.ndarray, torch.tensor

Function: ---------- apply the inverse of affine transform 'trans' to uv Parameters: ---------- @trans: 3x3 np.array

Function: ---------- apply affine transform 'trans' to uv Parameters: ---------- @src_img: 3x3 np.array i