Mapping and Deeplab

Dataset/Half_Circle_O/annotations_summary.csv

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+Object_Name,Image_Path,X,Y,Width,Height,Img_Width,Img_Height
+Half_Circle_O,Half_Circle_O_img_0.jpg,266,208,18,28,448,448
+Half_Circle_O,Half_Circle_O_img_1.jpg,363,279,26,22,448,448
+Half_Circle_O,Half_Circle_O_img_2.jpg,231,293,37,26,448,448
+Half_Circle_O,Half_Circle_O_img_3.jpg,163,213,22,30,448,448
+Half_Circle_O,Half_Circle_O_img_4.jpg,61,260,61,43,448,448

Dataset/Heart_O/annotations_summary.csv

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+Object_Name,Image_Path,X,Y,Width,Height,Img_Width,Img_Height
+Heart_O,Heart_O_img_0.jpg,258,204,29,28,448,448
+Heart_O,Heart_O_img_1.jpg,356,271,28,28,448,448
+Heart_O,Heart_O_img_2.jpg,225,282,38,39,448,448
+Heart_O,Heart_O_img_3.jpg,162,207,32,31,448,448
+Heart_O,Heart_O_img_4.jpg,50,241,63,66,448,448

Dataset/Heart_W/annotations_summary.csv

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+Object_Name,Image_Path,X,Y,Width,Height,Img_Width,Img_Height
+Heart_W,Heart_W_img_0.jpg,258,204,29,28,448,448
+Heart_W,Heart_W_img_1.jpg,196,93,29,30,448,448
+Heart_W,Heart_W_img_2.jpg,251,21,41,40,448,448
+Heart_W,Heart_W_img_3.jpg,262,159,40,41,448,448
+Heart_W,Heart_W_img_4.jpg,143,276,41,42,448,448

Dataset_Tools/augment_images.py

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+import numpy as np
+import imgaug as ia
+import imgaug.augmenters as iaa
+
+
+def create_augmenter():
+    sometimes = lambda aug: iaa.Sometimes(0.5, aug)
+    seq = iaa.Sequential(
+        [
+            # execute 0 to 5 of the following (less important) augmenters per image
+            # don't execute all of them, as that would often be way too strong
+            iaa.SomeOf((0, 3),
+                [
+                    sometimes(iaa.Superpixels(p_replace=(0, 1.0), n_segments=(20, 200))), # convert images into their superpixel representation
+                    iaa.OneOf([
+                        iaa.GaussianBlur((0, 3.0)), # blur images with a sigma between 0 and 3.0
+                        iaa.AverageBlur(k=(2, 7)), # blur image using local means with kernel sizes between 2 and 7
+                        iaa.MedianBlur(k=(3, 11)), # blur image using local medians with kernel sizes between 2 and 7
+                    ]),
+                    iaa.Sharpen(alpha=(0, 1.0), lightness=(0.75, 1.5)), # sharpen images
+                    iaa.Emboss(alpha=(0, 1.0), strength=(0, 2.0)), # emboss images
+                    # search either for all edges or for directed edges,
+                    # blend the result with the original image using a blobby mask
+                    iaa.SimplexNoiseAlpha(iaa.OneOf([
+                        iaa.EdgeDetect(alpha=(0.5, 1.0)),
+                        iaa.DirectedEdgeDetect(alpha=(0.5, 1.0), direction=(0.0, 1.0)),
+                    ])),
+                    iaa.AdditiveGaussianNoise(loc=0, scale=(0.0, 0.05*255), per_channel=0.5), # add gaussian noise to images
+                    iaa.OneOf([
+                        iaa.Dropout((0.01, 0.1), per_channel=0.5), # randomly remove up to 10% of the pixels
+                        iaa.CoarseDropout((0.03, 0.15), size_percent=(0.02, 0.05), per_channel=0.2),
+                    ]),
+                    iaa.Invert(0.05, per_channel=True), # invert color channels
+                    iaa.Add((-10, 10), per_channel=0.5), # change brightness of images (by -10 to 10 of original value)
+                    iaa.AddToHueAndSaturation((-20, 20)), # change hue and saturation
+                    # either change the brightness of the whole image (sometimes
+                    # per channel) or change the brightness of subareas
+                    iaa.OneOf([
+                        iaa.Multiply((0.5, 1.5), per_channel=0.5),
+                        iaa.FrequencyNoiseAlpha(
+                            exponent=(-4, 0),
+                            first=iaa.Multiply((0.5, 1.5), per_channel=True),
+                            second=iaa.LinearContrast((0.5, 2.0))
+                        )
+                    ]),
+                    iaa.LinearContrast((0.5, 2.0), per_channel=0.5), # improve or worsen the contrast
+                    iaa.Grayscale(alpha=(0.0, 1.0)),
+                    sometimes(iaa.ElasticTransformation(alpha=(0.5, 3.5), sigma=0.25)), # move pixels locally around (with random strengths)
+                    sometimes(iaa.PiecewiseAffine(scale=(0.01, 0.05))), # sometimes move parts of the image around
+                    sometimes(iaa.PerspectiveTransform(scale=(0.01, 0.1)))
+                ],
+                random_order=True
+            )
+        ],
+        random_order=True
+    )
+    return seq
+
+def augment_images(images:list):
+    '''augment images in training set only'''
+    augmenter = create_augmenter()
+    return  augmenter(images=images)