From 342206d94317f058baa6fbc22bed0ee53ab38394 Mon Sep 17 00:00:00 2001
From: Tim Laibacher <tim.laibacher@idiap.ch>
Date: Mon, 26 Aug 2019 10:11:39 +0200
Subject: [PATCH] Remove distortions
---
bob/ip/binseg/data/transforms.py | 113 -------------------------------
1 file changed, 113 deletions(-)
diff --git a/bob/ip/binseg/data/transforms.py b/bob/ip/binseg/data/transforms.py
index b81163fa..1336ff13 100644
--- a/bob/ip/binseg/data/transforms.py
+++ b/bob/ip/binseg/data/transforms.py
@@ -330,119 +330,6 @@ class RandomResizedCrop:
return format_string
-class Distortion:
- """
- Applies random elastic distortion to a PIL Image, adapted from https://github.com/mdbloice/Augmentor/blob/master/Augmentor/Operations.py :
- As well as the probability, the granularity of the distortions
- produced by this class can be controlled using the width and
- height of the overlaying distortion grid. The larger the height
- and width of the grid, the smaller the distortions. This means
- that larger grid sizes can result in finer, less severe distortions.
- As well as this, the magnitude of the distortions vectors can
- also be adjusted.
-
- Attributes
- ----------
- grid_width : int
- the width of the gird overlay, which is used by the class to apply the transformations to the image. Defaults to ``8``
- grid_height : int
- the height of the gird overlay, which is used by the class to apply the transformations to the image. Defaults to ``8``
- magnitude : int
- controls the degree to which each distortion is applied to the overlaying distortion grid. Defaults to ``1``
-
- prob : float
- probability that the operation is performend. Defaults to ``0.5``
- """
- def __init__(self,grid_width=8, grid_height=8, magnitude=1, prob=0.5):
- self.grid_width = grid_width
- self.grid_height = grid_height
- self.magnitude = magnitude
- self.prob = prob
-
- def _generatemesh(self, image):
- w, h = image.size
- horizontal_tiles = self.grid_width
- vertical_tiles = self.grid_height
- width_of_square = int(floor(w / float(horizontal_tiles)))
- height_of_square = int(floor(h / float(vertical_tiles)))
- width_of_last_square = w - (width_of_square * (horizontal_tiles - 1))
- height_of_last_square = h - (height_of_square * (vertical_tiles - 1))
- dimensions = []
- for vertical_tile in range(vertical_tiles):
- for horizontal_tile in range(horizontal_tiles):
- if vertical_tile == (vertical_tiles - 1) and horizontal_tile == (horizontal_tiles - 1):
- dimensions.append([horizontal_tile * width_of_square,
- vertical_tile * height_of_square,
- width_of_last_square + (horizontal_tile * width_of_square),
- height_of_last_square + (height_of_square * vertical_tile)])
- elif vertical_tile == (vertical_tiles - 1):
- dimensions.append([horizontal_tile * width_of_square,
- vertical_tile * height_of_square,
- width_of_square + (horizontal_tile * width_of_square),
- height_of_last_square + (height_of_square * vertical_tile)])
- elif horizontal_tile == (horizontal_tiles - 1):
- dimensions.append([horizontal_tile * width_of_square,
- vertical_tile * height_of_square,
- width_of_last_square + (horizontal_tile * width_of_square),
- height_of_square + (height_of_square * vertical_tile)])
- else:
- dimensions.append([horizontal_tile * width_of_square,
- vertical_tile * height_of_square,
- width_of_square + (horizontal_tile * width_of_square),
- height_of_square + (height_of_square * vertical_tile)])
- last_column = []
- for i in range(vertical_tiles):
- last_column.append((horizontal_tiles-1)+horizontal_tiles*i)
- last_row = range((horizontal_tiles * vertical_tiles) - horizontal_tiles, horizontal_tiles * vertical_tiles)
- polygons = []
- for x1, y1, x2, y2 in dimensions:
- polygons.append([x1, y1, x1, y2, x2, y2, x2, y1])
- polygon_indices = []
- for i in range((vertical_tiles * horizontal_tiles) - 1):
- if i not in last_row and i not in last_column:
- polygon_indices.append([i, i + 1, i + horizontal_tiles, i + 1 + horizontal_tiles])
- for a, b, c, d in polygon_indices:
- dx = random.randint(-self.magnitude, self.magnitude)
- dy = random.randint(-self.magnitude, self.magnitude)
- x1, y1, x2, y2, x3, y3, x4, y4 = polygons[a]
- polygons[a] = [x1, y1,
- x2, y2,
- x3 + dx, y3 + dy,
- x4, y4]
- x1, y1, x2, y2, x3, y3, x4, y4 = polygons[b]
- polygons[b] = [x1, y1,
- x2 + dx, y2 + dy,
- x3, y3,
- x4, y4]
- x1, y1, x2, y2, x3, y3, x4, y4 = polygons[c]
- polygons[c] = [x1, y1,
- x2, y2,
- x3, y3,
- x4 + dx, y4 + dy]
- x1, y1, x2, y2, x3, y3, x4, y4 = polygons[d]
- polygons[d] = [x1 + dx, y1 + dy,
- x2, y2,
- x3, y3,
- x4, y4]
- generated_mesh = []
- for i in range(len(dimensions)):
- generated_mesh.append([dimensions[i], polygons[i]])
-
- return generated_mesh
-
- def __call__(self,*args):
- if random.random() < self.prob:
- # img, gt and mask have same resolution, we only generate mesh once:
- mesh = self._generatemesh(args[0])
- imgs = []
- for img in args:
- img = img.transform(img.size, Image.MESH, mesh, resample=Image.BICUBIC)
- imgs.append(img)
- return imgs
- else:
- return args
-
-
class Resize:
"""Resize to given size.
--
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