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Fix Translate + TF loader

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Harle, Antoine (Contracteur) 2020-02-14 13:57:17 -05:00
parent 79de0191a8
commit b170af076f
9 changed files with 674 additions and 40 deletions
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19
higher/smart_aug/transformations.py
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@ -19,9 +19,9 @@ import kornia
import random
#TF that don't have use for magnitude parameter.
TF_no_mag={'Identity', 'FlipUD', 'FlipLR', 'Random', 'RandBlend'}
TF_no_mag={'Identity', 'FlipUD', 'FlipLR', 'Random', 'RandBlend', 'identity', 'flipUD', 'flipLR'}
#TF which implemetation doesn't allow gradient propagaition.
TF_no_grad={'Solarize', 'Posterize', '=Solarize', '=Posterize'}
TF_no_grad={'Solarize', 'Posterize', '=Solarize', '=Posterize', 'posterize','solarize'}
#TF for which magnitude should be ignored (Magnitude fixed).
TF_ignore_mag= TF_no_mag | TF_no_grad
@ -30,6 +30,7 @@ PARAMETER_MAX = 1
# What is the min 'level' a transform could be predicted
PARAMETER_MIN = 0.1
'''
# Dictionnary mapping tranformations identifiers to their function.
# Each value of the dict should be a lambda function taking a (batch of data, magnitude of transformations) tuple as input and returns a batch of data.
TF_dict={ #Dataugv5+
@ -38,8 +39,8 @@ TF_dict={ #Dataugv5+
'FlipUD' : (lambda x, mag: flipUD(x)),
'FlipLR' : (lambda x, mag: flipLR(x)),
'Rotate': (lambda x, mag: rotate(x, angle=rand_floats(size=x.shape[0], mag=mag, maxval=30))),
'TranslateX': (lambda x, mag: translate(x, translation=zero_stack(rand_floats(size=(x.shape[0],), mag=mag, maxval=x.shape[1]*0.33), zero_pos=0))),
'TranslateY': (lambda x, mag: translate(x, translation=zero_stack(rand_floats(size=(x.shape[0],), mag=mag, maxval=x.shape[2]*0.33), zero_pos=1))),
'TranslateX': (lambda x, mag: translate(x, translation=zero_stack(rand_floats(size=(x.shape[0],), mag=mag, maxval=x.shape[2]*0.33), zero_pos=0))),
'TranslateY': (lambda x, mag: translate(x, translation=zero_stack(rand_floats(size=(x.shape[0],), mag=mag, maxval=x.shape[3]*0.33), zero_pos=1))),
'TranslateXabs': (lambda x, mag: translate(x, translation=zero_stack(rand_floats(size=(x.shape[0],), mag=mag, maxval=20), zero_pos=0))),
'TranslateYabs': (lambda x, mag: translate(x, translation=zero_stack(rand_floats(size=(x.shape[0],), mag=mag, maxval=20), zero_pos=1))),
'ShearX': (lambda x, mag: shear(x, shear=zero_stack(rand_floats(size=(x.shape[0],), mag=mag, maxval=0.3), zero_pos=0))),
@ -49,7 +50,7 @@ TF_dict={ #Dataugv5+
'Contrast': (lambda x, mag: contrast(x, contrast_factor=rand_floats(size=x.shape[0], mag=mag, minval=0.1, maxval=1.9))),
'Color':(lambda x, mag: color(x, color_factor=rand_floats(size=x.shape[0], mag=mag, minval=0.1, maxval=1.9))),
'Brightness':(lambda x, mag: brightness(x, brightness_factor=rand_floats(size=x.shape[0], mag=mag, minval=0.1, maxval=1.9))),
'Sharpness':(lambda x, mag: sharpeness(x, sharpness_factor=rand_floats(size=x.shape[0], mag=mag, minval=0.1, maxval=1.9))),
'Sharpness':(lambda x, mag: sharpness(x, sharpness_factor=rand_floats(size=x.shape[0], mag=mag, minval=0.1, maxval=1.9))),
'Posterize': (lambda x, mag: posterize(x, bits=rand_floats(size=x.shape[0], mag=mag, minval=4., maxval=8.))),#Perte du gradient
'Solarize': (lambda x, mag: solarize(x, thresholds=rand_floats(size=x.shape[0], mag=mag, minval=1/256., maxval=256/256.))), #Perte du gradient #=>Image entre [0,1]
@ -57,11 +58,11 @@ TF_dict={ #Dataugv5+
'+Contrast': (lambda x, mag: contrast(x, contrast_factor=rand_floats(size=x.shape[0], mag=mag, minval=1.0, maxval=1.9))),
'+Color':(lambda x, mag: color(x, color_factor=rand_floats(size=x.shape[0], mag=mag, minval=1.0, maxval=1.9))),
'+Brightness':(lambda x, mag: brightness(x, brightness_factor=rand_floats(size=x.shape[0], mag=mag, minval=1.0, maxval=1.9))),
'+Sharpness':(lambda x, mag: sharpeness(x, sharpness_factor=rand_floats(size=x.shape[0], mag=mag, minval=1.0, maxval=1.9))),
'+Sharpness':(lambda x, mag: sharpness(x, sharpness_factor=rand_floats(size=x.shape[0], mag=mag, minval=1.0, maxval=1.9))),
'-Contrast': (lambda x, mag: contrast(x, contrast_factor=invScale_rand_floats(size=x.shape[0], mag=mag, minval=0.1, maxval=1.0))),
'-Color':(lambda x, mag: color(x, color_factor=invScale_rand_floats(size=x.shape[0], mag=mag, minval=0.1, maxval=1.0))),
'-Brightness':(lambda x, mag: brightness(x, brightness_factor=invScale_rand_floats(size=x.shape[0], mag=mag, minval=0.1, maxval=1.0))),
'-Sharpness':(lambda x, mag: sharpeness(x, sharpness_factor=invScale_rand_floats(size=x.shape[0], mag=mag, minval=0.1, maxval=1.0))),
'-Sharpness':(lambda x, mag: sharpness(x, sharpness_factor=invScale_rand_floats(size=x.shape[0], mag=mag, minval=0.1, maxval=1.0))),
'=Posterize': (lambda x, mag: posterize(x, bits=invScale_rand_floats(size=x.shape[0], mag=mag, minval=4., maxval=8.))),#Perte du gradient
'=Solarize': (lambda x, mag: solarize(x, thresholds=invScale_rand_floats(size=x.shape[0], mag=mag, minval=1/256., maxval=256/256.))), #Perte du gradient #=>Image entre [0,1]
@ -86,7 +87,7 @@ TF_dict={ #Dataugv5+
#'Auto_Contrast': (lambda mag: None), #Pas opti pour des batch (Super lent)
#'Equalize': (lambda mag: None),
}
'''
## Image type cast ##
def int_image(float_image):
"""Convert a float Tensor/Image to an int Tensor/Image.
@ -304,7 +305,7 @@ def brightness(x, brightness_factor):
return blend(torch.zeros(x.size(), device=device), x, brightness_factor).clamp(min=0.0,max=1.0) #Expect image in the range of [0, 1]
def sharpeness(x, sharpness_factor):
def sharpness(x, sharpness_factor):
"""Adjust sharpness of images.
Args: