In this work, we are interested in translating text in the form of single-sentence human-written descriptions directly into image pixels. For example, "this flower has petals that are yellow and has a ruffled stamen" and "this pink and yellow flower has a beautiful yellow center with many stamens". You have to develop a novel deep architecture and GAN formulation to effectively translate visual concepts from characters to pixels.

More specifically, given a set of texts, your task is to generate suitable images with size 64x64x3 to illustrate each of the texts.

You will compete on the modified release of [Oxford-102 flower dataset](https://www.robots.ox.ac.uk/~vgg/data/flowers/102/) and its [paired texts.](https://drive.google.com/file/d/0B0ywwgffWnLLcms2WWJQRFNSWXM/view?resourcekey=0-Av8zFbeDDvNcF1sSjDR32w)
![image1](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F2380849%2F4b114306156e8884bed87288c7bf1bd9%2Fexample.png?generation=1575453398734941&alt=media)