Explore 16 data transformation with PIL

[barisozmen]

They are listed here:

''' def ShearX(img, v): # [-0.3, 0.3] return img.transform(img.size, PIL.Image.AFFINE, (1, v, 0, 0, 1, 0))

def ShearY(img, v): # [-0.3, 0.3] return img.transform(img.size, PIL.Image.AFFINE, (1, 0, 0, v, 1, 0))

def TranslateX(img, v): # [-150, 150] => percentage: [-0.45, 0.45] v = v*img.size[0] return img.transform(img.size, PIL.Image.AFFINE, (1, 0, v, 0, 1, 0))

def TranslateY(img, v): # [-150, 150] => percentage: [-0.45, 0.45] v = v*img.size[1] return img.transform(img.size, PIL.Image.AFFINE, (1, 0, 0, 0, 1, v))

def Rotate(img, v): # [-30, 30] return img.rotate(v)

def AutoContrast(img, _): return PIL.ImageOps.autocontrast(img)

def Invert(img, _): return PIL.ImageOps.invert(img)

def Equalize(img, _): return PIL.ImageOps.equalize(img)

def Flip(img, _): # not from the paper return PIL.ImageOps.mirror(img)

def Solarize(img, v): # [0, 256] return PIL.ImageOps.solarize(img, v)

def Posterize(img, v): # [4, 8] v = int(v) return PIL.ImageOps.posterize(img, v)

def Contrast(img, v): # [0.1,1.9] return PIL.ImageEnhance.Contrast(img).enhance(v)

def Color(img, v): # [0.1,1.9] return PIL.ImageEnhance.Color(img).enhance(v)

def Brightness(img, v): # [0.1,1.9] return PIL.ImageEnhance.Brightness(img).enhance(v)

def Sharpness(img, v): # [0.1,1.9] return PIL.ImageEnhance.Sharpness(img).enhance(v)

def Cutout(img, v): # [0, 60] => percentage: [0, 0.2] w, h = img.size v = v*img.size[0] x0 = np.random.uniform(w-v) y0 = np.random.uniform(h-v) xy = (x0, y0, x0+v, y0+v) color = (127, 127, 127) img = img.copy() PIL.ImageDraw.Draw(img).rectangle(xy, color) return img

def SamplePairing(imgs): # [0, 0.4] def f(img1, v): i = np.random.choice(len(imgs)) img2 = PIL.Image.fromarray(imgs[i]) return PIL.Image.blend(img1, img2, v) return f '''