restrucured in the readmes

README.md

@@ -4,27 +4,23 @@
 
 Make sure you have `virtualenv` and `python 3.5+` installed
 
-
 ```bash
 bash install.sh
 ```
 This will activate the virtualenv and install the proper packages.
 
-You will probably also need [Git LFS](https://git-lfs.github.com/) to track various datasets
-
 To then launch the jupyter instance use
 ```bash
 jupyter notebook
 ```
-And you should be directed to `localhost:8888`. In the future we should set up the gcloud instance with the same thing. But it seems some bureaucracy got in the way for now.
+And you should be directed to `localhost:8888`. 
 
 ### Project structure
 * [Models](models) - The resulting generated models
 * [Utilities](utils) - Various tools such as visualization etc.
 * [Scripts](scripts) - The scripts used for the project
 * [Datasets](datasets) - The datasets used for the project
 
-
 ## Resources
 
 ### Voice to text
@@ -46,23 +42,9 @@ And you should be directed to `localhost:8888`. In the future we should set up t
 
 * Adversarial loss [short](https://www.quora.com/What-is-adversarial-loss-in-machine-learning) [paper](https://arxiv.org/pdf/1901.08753.pdf)
 
-### Datasets
-
-* Conceptual Captions [link](https://ai.google.com/research/ConceptualCaptions/download)
-
-* Flickr 30k [link](https://www.kaggle.com/hsankesara/flickr-image-dataset/version/1)
-
-* TIMIT Speech corpus [link](https://catalog.ldc.upenn.edu/LDC93S1)
-
-I think that we should use the flickr dataset as the 30k images should really be enough in the limited time we have.
+* Training GANs, [Tips and Tricks](https://github.com/soumith/ganhacks)
 
-Once you have downloaded the flickr dataset extract it and run the resize script
-that's located in the flickr30k_images folder, from the folder in question
-```bash
-bash resize_images.sh
-```
-
-## Further notes
+## Further information
 
 ### Report
 The report Overleaf is available [here](https://www.overleaf.com/4488118745cjmprgwyfxcw)
@@ -72,17 +54,8 @@ The report Overleaf is available [here](https://www.overleaf.com/4488118745cjmpr
 Might have to use a bag of words model or some other form of context presentation to simplify what the sentence says, look into this further.
 
 ### Training GANS
-* [Tips and Tricks](https://github.com/soumith/ganhacks)
 
-## GCP
-### Running StackGAN
-Run StackGAN on GCP from the code folder with
-```bash
-python2 main.py --cfg cfg/coco_eval.yml --gpu 0
-```
-Contrary to popular belief setting `--gpu 0` here actually refers to the id of the gpu. In most other cases `gpu 0` refers to cpu mode. Weird.
-
-The generated images will be stored in the `models/coco/netG_epoch_90` directory.
+## Google Cloud Platform
 
 ### Jupyter notebooks
 To use jupyter notebooks, run this on the remote
@@ -95,6 +68,7 @@ Then tunnel your connection through
 david@fridge:~$ ssh -N -L localhost:8888:localhost:8888 david@<EXTERNAL_IP_OF_VM>
 ```
 Then simply open a browser on `localhost:8888` and provide it with the token that should be visible in the commandline window on the vm to connect.
+
 ### Show results
 The images are viewable in python notebooks and can also, be downloaded from there. 
 

datasets/README.md

@@ -0,0 +1,15 @@
+# Datasets
+
+* Conceptual Captions [link](https://ai.google.com/research/ConceptualCaptions/download)
+
+* Flickr 30k [link](https://www.kaggle.com/hsankesara/flickr-image-dataset/version/1)
+
+* TIMIT Speech corpus [link](https://catalog.ldc.upenn.edu/LDC93S1)
+
+I think that we should use the flickr dataset as the 30k images should really be enough in the limited time we have.
+
+Once you have downloaded the flickr dataset extract it and run the resize script
+that's located in the flickr30k_images folder, from the folder in question
+```bash
+bash resize_images.sh
+```

inspiration/README.md

@@ -0,0 +1,8 @@
+## Running StackGAN
+Run StackGAN on GCP from the code folder with
+```bash
+python2 main.py --cfg cfg/coco_eval.yml --gpu 0
+```
+Contrary to popular belief setting `--gpu 0` here actually refers to the id of the gpu. In most other cases `gpu 0` refers to cpu mode. Weird.
+
+The generated images will be stored in the `models/coco/netG_epoch_90` directory.