doc: Add example images

README.md

@@ -1,5 +1,11 @@
 ## Data Generator for 2D Object Detection
 ---
+
+| | |
+|---|---|
+| ![img01](examples/image01_original.png) | ![img01](examples/image01_processed01.png) |
+| ![img01](examples/image01_processed02.png) | ![img01](examples/image01_processed03.png) |
+
 ### Contents
 
 1. [Overview](#overview)
@@ -15,9 +21,9 @@ Main features:
 * Provides most common photometric and geometric image transformations out of the box.
 * Provides both random and deterministic versions of all image transformations.
 * Provides flexible options for how decide whether a random transformation of an image is "valid" (see tutorial).
-* Provides parsers for ground truth annotations in the MS COCO (JSON) and Pascal VOC (XML) formats as well as a wide range of CSV formats.
+* Provides parsers for ground truth annotations in the MS COCO (JSON) and Pascal VOC (XML) formats as well as for a wide range of CSV formats.
 
-Most data generators for training deep neural networks on computer vision tasks that ship with deep learning libraries are limited to image classification and those that I was able to find for 2D object detection are either only applicable to a specific model, provide only a small set of hard-coded and inflexible data augmentation features, or are otherwise severely limited. When you train a deep neural network on an object detection task, the data augmentation you perform is one of the most important factors that determine the success of your training, therefore I wrote this data generator specifically with the goal of flexible and easily extensible data augmentation.
+Most data generators for training deep neural networks on computer vision tasks that ship with deep learning libraries are limited to image classification and those that I was able to find for 2D object detection are either only applicable to a specific model, provide only a small set of hard-coded and inflexible data augmentation features, or are otherwise severely limited. When you train a deep neural network on an object detection task, data augmentation one of the most important factors that determine the success of your training, therefore I wrote this data generator specifically with the goal of flexible and easily extensible data augmentation.
 
 ### Dependencies