Update README.md

README.md

@@ -8,6 +8,27 @@ sdk_version: 3.28.2
 app_file: app.py
 pinned: false
 license: cc-by-4.0
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- diffusers
+- controlnet
+- jax-diffusers-event
 ---
+    
+# ControlLight: Light control through ControlNet and Depth Maps conditioning
+We propose a ControlNet using depth maps conditioning that is capable of controlling the light direction in a scene while trying to maintain the scene integrity.
+The model was trained on [VIDIT dataset](https://huggingface.co/datasets/Nahrawy/VIDIT-Depth-ControlNet) and [
+A Dataset of Flash and Ambient Illumination Pairs from the Crowd](https://huggingface.co/datasets/Nahrawy/FAID-Depth-ControlNet) as a part of the [Jax Diffusers Event](https://huggingface.co/jax-diffusers-event).
+
+Due to the limited available data the model is clearly overfit, but it serves as a proof of concept to what can be further achieved using enough data.
+
+A large part of the training data is synthetic so we encourage further training using synthetically generated scenes, using Unreal engine for example.
+
+The WandB training logs can be found [here](https://wandb.ai/hassanelnahrawy/controlnet-VIDIT-FAID), it's worth noting that the model was left to overfit for experimentation and it's advised to use the 8K steps weights or prior weights.
+
+This project is a joint work between [ParityError](https://huggingface.co/ParityError) and [Nahrawy](https://huggingface.co/Nahrawy).
+
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference