Adding A New Kind of Data Augmentation for Images (fastai#1860)

* Added RGB-randomiser

* Updated documentation to include the 'rgb_randomise' data augmentation

* Removed accidental formatting changes.

* Randomise -> Randomize

Author: rsomani95

docs_src/vision.transform.ipynb

@@ -4,7 +4,7 @@
 from .image import _affine_mult
 
 __all__ = ['brightness', 'contrast', 'crop', 'crop_pad', 'cutout', 'dihedral', 'dihedral_affine', 'flip_affine', 'flip_lr',
-           'get_transforms', 'jitter', 'pad', 'perspective_warp', 'rand_pad', 'rand_crop', 'rand_zoom', 'rotate', 'skew', 'squish',
+           'get_transforms', 'jitter', 'pad', 'perspective_warp', 'rand_pad', 'rand_crop', 'rand_zoom', 'rgb_randomize', 'rotate', 'skew', 'squish',
            'rand_resize_crop', 'symmetric_warp', 'tilt', 'zoom', 'zoom_crop']
 
 _pad_mode_convert = {'reflection':'reflect', 'zeros':'constant', 'border':'replicate'}
@@ -134,6 +134,14 @@ def _cutout(x, n_holes:uniform_int=1, length:uniform_int=40):
 
 cutout = TfmPixel(_cutout, order=20)
 
+def _rgb_randomize(x, channel:int=None, thresh:float=0.3):
+    "Randomize one of the channels of the input image"
+    if channel is None: channel = np.random.randint(0, x.shape[0] - 1)
+    x[channel] = torch.rand(x.shape[1:]) * np.random.uniform(0, thresh)
+    return x
+
+rgb_randomize = TfmPixel(_rgb_randomize)
+
 def _minus_epsilon(row_pct:float, col_pct:float, eps:float=1e-7):
     if row_pct==1.: row_pct -= 1e-7
     if col_pct==1.: col_pct -= 1e-7