updated readme and added sample images

.gitattributes

@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 *.psd filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text

README.md

@@ -8,5 +8,14 @@ sdk_version: 4.27.0
 app_file: app.py
 pinned: false
 ---
+# Neural Style Transfer Deployment
+### DALI 2024S - Machine Learning Track
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Deployment of the neural style transfer algorithm.  Users can input their own style and content images and train the algorithm with their own hyperparameters.  If you need a pair of images to expiriment with, I reccomend President.jpg as the content image and SelfPortrait.jpg as the style image.  I get good results with 5 epochs, a learning rate of 0.01, a content loss of 1, and a style loss of 0.01.\
+Importantly, this algorithm is running on a CPU so keep training time in mind when setting the number of epochs.
+
+## Files
+- app.py: A copy of the interface I defined in the Python notebook
+- vgg19-dcbb9e9d.pth: The vgg19 pre-trained weights (so I don't have to query them each time I load the model)
+- President.jpg: Sample content image
+- SelfPortrait.jpg: Sample style image