---
title: Controlnet Depth Generation
emoji: 🌖
colorFrom: red
colorTo: purple
sdk: gradio
sdk_version: 5.38.0
app_file: app.py
pinned: false
license: mit
short_description: Interior design using controlnet depth model
---

Stable Diffusion ControlNet Depth Demo
This Space demonstrates a Stable Diffusion model combined with a ControlNet model fine-tuned for depth, and includes automatic depth map estimation from your input image.

How to use:

Upload an Input Image: Provide any photo (e.g., of a room, an object, a scene). The app will automatically estimate its depth map.

Enter a Text Prompt: Describe the image you want to generate. The model will try to apply your prompt while respecting the structure derived from the depth map.

Adjust Parameters: Experiment with "Inference Steps" and "Guidance Scale" for different results.

Click "Submit" to generate the image.

Model Details:

Base Diffusion Model: runwayml/stable-diffusion-v1-5 (downloaded from Hugging Face Hub)

ControlNet Model: Fine-tuned for depth (uploaded as ./Output_ControlNet_Finetune)

Depth Estimator: Intel/dpt-hybrid-midas (downloaded from Hugging Face Hub)

Note: This model is quite large, so the first generation after a "cold start" (when the Space wakes up) might take a few minutes to load the models. Subsequent generations will be faster.

Enjoy!

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference