Add v2 models description

README.md

@@ -18,12 +18,12 @@ tags:
 This repository provides a collection of ControlNet checkpoints for
 [FLUX.1-dev model](https://huggingface.co/black-forest-labs/FLUX.1-dev) by Black Forest Labs
 
-![Example Picture 1](https://github.com/XLabs-AI/x-flux/blob/main/assets/readme/examples/depth_example_2.png?raw=true)
+![Example Picture 1](./assets/depth_v2_res1.png?raw=true)
 
 [See our github](https://github.com/XLabs-AI/x-flux-comfyui) for comfy ui workflows.
 ![Example Picture 1](https://github.com/XLabs-AI/x-flux-comfyui/blob/main/assets/image1.png?raw=true)
 
-[See our github](https://github.com/XLabs-AI/x-flux) for train script and train configs.
+[See our github](https://github.com/XLabs-AI/x-flux) for train script, train configs and demo script for inference.
 
 # Models
 
@@ -32,8 +32,11 @@ Our collection supports 3 models:
 - HED
 - Depth (Midas)
 
-Each ControlNet is trained on 1024x1024 resolution. 
-However, we recommend you to generate images with 1024x1024 for Depth, and use 768x768 resolution for Canny and HED for better results.
+Each ControlNet is trained on 1024x1024 resolution and works for 1024x1024 resolution.
+We release **v2 versions** - better and realistic versions, which can be used directly in ComfyUI!   
+
+Please, see our [ComfyUI custom nodes installation guide](https://github.com/XLabs-AI/x-flux-comfyui)
+
 
 # Examples
 
@@ -41,13 +44,29 @@ See examples of our models results below.
 Also, some generation results with input images are provided in "Files and versions"
 
 # Inference
-Use main.py from our [official repo](https://github.com/XLabs-AI/x-flux)   
 
-We do not guarantee that our checkpoints will work 100% correctly with other repositories and tools due to the nature of our sampling implementation and so on until we add our support.
+To try our models, you have 2 options:
+1. Use main.py from our [official repo](https://github.com/XLabs-AI/x-flux)
+2. Use our custom nodes for ComfyUI and test it with provided workflows
 
 See examples how to launch our models:
 
-## Canny ControlNet
+## Canny ControlNet (version 2)
+
+1. Clone our [x-flux-comfyui](https://github.com/XLabs-AI/x-flux-comfyui) custom nodes
+2. Launch ComfyUI
+3. Try our canny_workflow.json
+
+![Example Picture 1](./assets/canny_v2_res1.png?raw=true)
+![Example Picture 1](./assets/canny_v2_res2.png?raw=true)
+![Example Picture 1](./assets/canny_v2_res3.png?raw=true)
+
+
+## Canny ControlNet (version 1)
+
+1. Clone [our repo](https://github.com/XLabs-AI/x-flux), install requirements
+2. Launch main.py in command line with parameters
+
 ```bash
 python3 main.py \
  --prompt "a viking man with white hair looking, cinematic, MM full HD" \
@@ -60,7 +79,18 @@ python3 main.py \
 ```
 ![Example Picture 1](https://github.com/XLabs-AI/x-flux/blob/main/assets/readme/examples/canny_example_1.png?raw=true)
 
-## Depth ControlNet
+## Depth ControlNet (version 2)
+
+1. Clone our [x-flux-comfyui](https://github.com/XLabs-AI/x-flux-comfyui) custom nodes
+2. Launch ComfyUI
+3. Try our depth_workflow.json
+
+![Example Picture 1](./assets/depth_v2_res1.png?raw=true)
+![Example Picture 1](./assets/depth_v2_res2.png?raw=true)
+
+## Depth ControlNet (version 1)
+1. Clone [our repo](https://github.com/XLabs-AI/x-flux), install requirements
+2. Launch main.py in command line with parameters
 ```bash
 python3 main.py \
  --prompt "Photo of the bold man with beard and laptop, full hd, cinematic photo" \
@@ -98,7 +128,7 @@ python3 main.py \
 ![Example Picture 2](https://github.com/XLabs-AI/x-flux/blob/main/assets/readme/examples/depth_example_3.png?raw=true)
 
 
-## HED ControlNet
+## HED ControlNet (version 1)
 ```bash
 python3 main.py \
  --prompt "2d art of a sitting african rich woman, full hd, cinematic photo" \