Blender: v1.0 release

README.md

@@ -19,6 +19,9 @@ Our AI plugins offer the following key features:
 ### <img src="plugins\stable-diffusion-webui\qairt_accelerate\docs\resources\main_icon.png" alt="drawing" style="width:30px;border-radius: 50%;"/> AUTOMATIC1111 stable-diffusion-webui Extension
 - [Overview and Installation](plugins/stable-diffusion-webui/qairt_accelerate/README.md)
 
+### <img src="plugins\blender\SnapdragonImageGeneration\docs\resources\main_icon.jpg" alt="drawing" style="width:30px;border-radius: 50%;"/> Blender ControlNet Plugin
+- [Overview and Installation](plugins/blender/SnapdragonImageGeneration/README.md)
+
 ##  License Information
 
 This project is licensed under the [BSD-3-Clause License](https://spdx.org/licenses/BSD-3-Clause.html). For the full license text, please refer to the [LICENSE](LICENSE) file in this repository.

plugins/blender/SnapdragonImageGeneration/README.md

@@ -0,0 +1,48 @@
+
+# <img src="docs\resources\main_icon.jpg" alt="drawing" style="width:40px;border-radius: 50%;"/> Blender ControlNet Plugin
+
+Blender ControlNet plugin runs on Qualcomm X-Elite NPU using [Qualcomm AI Runtime (QAIRT) SDK](https://www.qualcomm.com/developer/software/qualcomm-ai-engine-direct-sdk). The plugin uses QAIRT python APIs to run context binaries (.bin) generated by QAIRT SDK. We provide optimal performance by using QAIRT to run AI models on Qualcomm X-Elite NPU. These models are hosted on [Qualcomm AI hub](https://aihub.qualcomm.com/models/controlnet_quantized).
+
+![controlnet](docs/resources/blender_snapdragon_addon.gif)
+<sub><sup>This clip is at 2x speed</sup></sup>
+
+## Supported features
+
+* ControlNet model, 512x512 as input image, 512x512 or 2048x2048 as output image
+* Sampling method: DPM++ 2M
+* Upscaling method: ESRGAN-x4
+
+## Installation Instructions:
+
+### Step 1: Install Dependencies
+Download and install [Python 3.10.6](https://www.python.org/ftp/python/3.10.6/python-3.10.6-amd64.exe)
+
+> **_NOTE:_** The program is tested to work on Python `3.10.6`. Don't use other versions.
+
+### Step 2: Download Blender Arm64
+Download Blender Arm64 4.3 Alpha version from [Daily build](https://builder.blender.org/download/daily/). The Stable version of Arm64 is expected to be releasing soon.
+
+### Step 3: Download Blender ControlNet Plugin
+Download `blender-controlnet-plugin-v1.0.zip` from the [latest release](https://github.com/quic/wos-ai-plugins/releases/tag/v1.0-blender).
+Unzip and place the `SnapdragonImageGeneration` folder under `C:\Users\<user>\AppData\Roaming\Blender Foundation\Blender\4.3\scripts\addons`
+
+> **_NOTE:_** The path `C:\Users\<user>\AppData\Roaming\Blender Foundation\Blender\4.3` won't be created until the Blender application is opened at least once.
+
+> **_NOTE:_** Create the `scripts\addons` folder if not already present.
+
+
+### Step 4: Install Plugin
+
+Run below command to install the plugin. This installs QAIRT SDK and models required for the plugin. This script also creates a python virtual environment for the plugin.
+```
+.\install.bat
+```
+
+### Step 5: Enable Plugin
+Run Blender Arm64 4.3 and go to `Edit`->`Preferences`->`Add-ons` and search for `Snapdragon Image Generation` and enable it.
+<img src="docs/resources/enable-addon.png" alt="drawing" style="width:400px;"/>
+
+
+## Troubleshooting
+
+* To reinstall from scratch, delete directories: `venv`, `qnn_assets`