Commit a66e1f3c authored by Amir MOHAMMADI's avatar Amir MOHAMMADI
Browse files

Add more options to the giant video loader

parent 72035ee5
Pipeline #19437 failed with stage
in 24 minutes and 22 seconds
from .load_utils import (
frames, number_of_frames, yield_frames, yield_faces, scale_face, blocks,
bbx_cropper, min_face_size_normalizer, the_giant_video_loader)
bbx_cropper, min_face_size_normalizer, color_augmentation,
# gets sphinx autodoc done right - don't remove it
__all__ = [_ for _ in dir() if not _.startswith('_')]
......@@ -2,6 +2,7 @@ from import min_face_size_validator
from import normalize_annotations
from import reader
from bob.ip.base import scale, block, block_output_shape
from bob.ip.color import rgb_to_yuv, rgb_to_hsv
from bob.ip.facedetect import bounding_box_from_annotation
from functools import partial
import numpy
......@@ -192,16 +193,73 @@ def blocks(data, block_size, block_overlap=(0, 0)):
return output
def color_augmentation(image, channels=('rgb',)):
"""Converts an RGB image to different color channels.
image : numpy.array
The image in RGB Bob format.
channels : tuple, optional
List of channels to convert the image to. It can be any of ``rgb``,
``yuv``, ``hsv``.
The image that contains several channels:
``(3*len(channels), height, width)``.
final_image = []
if 'rgb' in channels:
if 'yuv' in channels:
if 'hsv' in channels:
return numpy.concatenate(final_image, axis=0)
def _random_sample(A, size):
return A[numpy.random.choice(A.shape[0], size, replace=False), ...]
def the_giant_video_loader(paddb, padfile,
region='whole', scaling_factor=None, cropper=None,
generator = None
normalizer=None, patches=False,
block_size=(96, 96), block_overlap=(0, 0),
random_patches_per_frame=None, augment=None,
if region == 'whole':
generator = yield_frames(paddb, padfile)
elif region == 'crop':
generator = yield_faces(
paddb, padfile, cropper=cropper, normalizer=normalizer)
raise ValueError("Invalid region value: `{}'".format(region))
if scaling_factor is not None:
generator = (scale(frame, scaling_factor)
for frame in generator)
if patches:
if random_patches_per_frame is None:
generator = (
patch for frame in generator
for patch in blocks(frame, block_size, block_overlap))
if padfile.attack_type is None:
random_patches_per_frame *= multiple_bonafide_patches
generator = (
patch for frame in generator
for patch in _random_sample(
blocks(frame, block_size, block_overlap),
if augment is not None:
generator = (augment(frame) for frame in generator)
return generator
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment