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Submit Your RenderDAZ3D Studio AI-Based Shader/Texture Enhancer
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NOTE: DIGITAL DOWNLOAD, NOT A PHYSICAL ITEM
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I'm a passionate coder whom uses Ai for & within his projects.
My current Projects feature PyTorch, Groq's Ai Nebius Ai chatbot generating API,
and Image enhancing ai technologies including:
but not limited to EDSR_x4, ESPCN_x4,, FSRCNN_x4, LapSRN_x8.
And customized daz3d studio posing models such as 'trained_pose_model.pth.
'
My current Projects feature PyTorch, Groq's Ai Nebius Ai chatbot generating API,
and Image enhancing ai technologies including:
but not limited to EDSR_x4, ESPCN_x4,, FSRCNN_x4, LapSRN_x8.
And customized daz3d studio posing models such as 'trained_pose_model.pth.
'
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License
Extended Use License
This item comes with our Extended Use Licensing. This means that you may use the model for both non-commercial and commercial purposes, in a variety of mediums and applications.
For full license terms, see our 3D Content Licensing Agreement
3D Material or Shader Details
| Vendor: | DrMorphGTS |
| Published: | Feb 06, 2025 |
| Download Size: | 294.6 MB |
| Software: | PC |
Statistics
| Favorites: | 2 |
| Likes: | 4 |
| Views: | 1,473 |
Item Ratings
Not Rated Yet
DAZ3D Studio AI-Based Shader/Texture Enhancer
Introducing Texture Enhancer Pro—a revolutionary AI-powered tool designed to breathe new life into your textures and shaders. Built with state-of-the-art deep neural networks, our software employs advanced super-resolution algorithms (including ESPCN, EDSR, FSRCNN, and LAPSRN models) to upscale your digital assets with exceptional clarity and detail.
Whether you're a game developer, digital artist, or 3D designer, Texture Enhancer Pro offers a streamlined and intuitive user interface powered by Kivy, making it incredibly easy to select, enhance, and export your images. Our innovative approach ensures that every pixel is refined, preserving essential details and reducing artifacts, so your textures and shaders appear crisp, vibrant, and true to your creative vision.
Experience a seamless workflow where complex AI technology meets user-friendly design. With Texture Enhancer Pro, transform your existing assets into high-definition masterpieces—elevating the quality of your projects and setting a new standard for digital artistry.
Update:
I've updated this product to executable format like the light enhancer for anyone who is having issues launching the python script with the library installer. I've also updated the model directory with the local ai models in the executable's location. The project should work flawlessly now. Thanks for your patience people. :) We've included new functionality where you can double, triple and quadrable the resolution of your final image too.
You just have to set the "Final scale" value to the image size you want. Be it times 2x, 3x, 4x.
Everything is now combined into a single package. Just redownload and try it out. Thanks friend. :)
This product uses the same archive directory system as the light generator too. After opening the archive go into the folder labeled "dist" to access the application, you don't have to bother with the 'build' directory as that directory is for the python libraries used in the application, but the directory "dist" contains the software's main executable. Feel free to open it and run the software after that. :) Thanks my ai loving friends for following my software development on renderhub. And for anyone interested and curious. I'm also making progress on the daz3d studio pose prompting application too that I've also started with my Groq model a couple of weeks ago.
More details on the enhancement models found in this project too:
"OpenCV’s **super-resolution module** offers a few different pretrained models, each with its own **speed-performance trade-offs** and typical use cases. Here’s a quick rundown:
The newest update include ai model enhancement with many other options for image enhancement proceeding your ai model image enhancement too.
As seen in the newest promotional image
Feel free to watch the demonstration video which includes all of the new enhancement options for the application. Note: The video only showcases the generic ESPCN image enhancement, the purpose of the video is to show the extra enhancements included in the product. I plan to update the video with the other ai enhancements too. The EDSR image enhancement takes quite a while to process on my PC.
Side Note: This application has intensive properties. And it may require a good GPU to process your image with higher quality. I'm using an RTX-3080. And it still stumbles on some enhancement settings.
---
## **1. ESPCN (Efficient Sub-Pixel Convolutional Network)**
**Model file:** `ESPCN_x2.pb`, `ESPCN_x3.pb`, `ESPCN_x4.pb`, etc.
- **Key Idea**: Uses sub-pixel convolutions to efficiently learn how to upscale images by rearranging “feature spaceinto “image space(sometimes called “pixel shuffle.
- **Why It’s Good**:
- **Lightweight** compared to some of the newer models.
- Typically **fast** to run on CPU or GPU.
- Good results up to 4with minimal artifacts.
- **Trade-off**:
- Not quite as sharp as some heavier models like EDSR when upscaled a lot.
---
## **2. EDSR (Enhanced Deep Super Resolution)**
**Model file:** `EDSR_x2.pb`, `EDSR_x4.pb`, etc.
- **Key Idea**: Builds on SRResNet and other deep CNN architectures with “residual blocks.
- **Why It’s Good**:
- Often considered **state-of-the-art** or near it for many super-resolution tasks in 24upscaling.
- Produces **sharper details** than ESPCN in many cases.
- **Trade-off**:
- Typically **larger** and **slower** than ESPCN because it’s a deeper network.
- More VRAM usage if using a GPU.
---
## **3. FSRCNN (Fast Super Resolution Convolutional Neural Network)**
**Model file:** `FSRCNN_x2.pb`, `FSRCNN_x4.pb`, etc.
- **Key Idea**: A re-architected version of SRCNN with **faster** upsampling stages and smaller filter sizes to keep it lightweight.
- **Why It’s Good**:
- Very **fast** and **compact**—ideal for real-time or mobile scenarios.
- Lower memory footprint than EDSR.
- **Trade-off**:
- May produce slightly **softer** results than EDSR or other heavier models at high scales (like 4.
- Great if your main concern is speed rather than absolute best detail.
---
## **4. LAPSRN (Laplacian Pyramid Super-Resolution Network)**
**Model file:** `LAPSRN_x4.pb`, `LAPSRN_x8.pb`, etc.
- **Key Idea**: Uses a **Laplacian pyramid** framework, progressively predicting residuals at multiple scales.
- **Why It’s Good**:
- Can handle **larger scaling** factors (e.g., 8 in a single pass.
- Often quite **robust** at upscaling texture details.
- **Trade-off**:
- Similar to EDSR, can be heavier and slower for older CPUs/GPUs.
- May introduce a bit of “smoothnessif you push it very high.
---
### **Which Model Should You Choose?**
- **ESPCN**
- Great for **4or less** with relatively **fast** performance and decent quality.
- **EDSR**
- If you want **best possible detail** at **24* and don’t mind a bit more computation.
- **FSRCNN**
- If you need a **real-time** or a **very fast** approach.
- **LAPSRN**
- If you require **bigger scales** (like 8 or want a pyramid-based upscaling approach."
Whether you're a game developer, digital artist, or 3D designer, Texture Enhancer Pro offers a streamlined and intuitive user interface powered by Kivy, making it incredibly easy to select, enhance, and export your images. Our innovative approach ensures that every pixel is refined, preserving essential details and reducing artifacts, so your textures and shaders appear crisp, vibrant, and true to your creative vision.
Experience a seamless workflow where complex AI technology meets user-friendly design. With Texture Enhancer Pro, transform your existing assets into high-definition masterpieces—elevating the quality of your projects and setting a new standard for digital artistry.
Update:
I've updated this product to executable format like the light enhancer for anyone who is having issues launching the python script with the library installer. I've also updated the model directory with the local ai models in the executable's location. The project should work flawlessly now. Thanks for your patience people. :) We've included new functionality where you can double, triple and quadrable the resolution of your final image too.
You just have to set the "Final scale" value to the image size you want. Be it times 2x, 3x, 4x.
Everything is now combined into a single package. Just redownload and try it out. Thanks friend. :)
This product uses the same archive directory system as the light generator too. After opening the archive go into the folder labeled "dist" to access the application, you don't have to bother with the 'build' directory as that directory is for the python libraries used in the application, but the directory "dist" contains the software's main executable. Feel free to open it and run the software after that. :) Thanks my ai loving friends for following my software development on renderhub. And for anyone interested and curious. I'm also making progress on the daz3d studio pose prompting application too that I've also started with my Groq model a couple of weeks ago.
More details on the enhancement models found in this project too:
"OpenCV’s **super-resolution module** offers a few different pretrained models, each with its own **speed-performance trade-offs** and typical use cases. Here’s a quick rundown:
The newest update include ai model enhancement with many other options for image enhancement proceeding your ai model image enhancement too.
As seen in the newest promotional image
Feel free to watch the demonstration video which includes all of the new enhancement options for the application. Note: The video only showcases the generic ESPCN image enhancement, the purpose of the video is to show the extra enhancements included in the product. I plan to update the video with the other ai enhancements too. The EDSR image enhancement takes quite a while to process on my PC.
Side Note: This application has intensive properties. And it may require a good GPU to process your image with higher quality. I'm using an RTX-3080. And it still stumbles on some enhancement settings.
---
## **1. ESPCN (Efficient Sub-Pixel Convolutional Network)**
**Model file:** `ESPCN_x2.pb`, `ESPCN_x3.pb`, `ESPCN_x4.pb`, etc.
- **Key Idea**: Uses sub-pixel convolutions to efficiently learn how to upscale images by rearranging “feature spaceinto “image space(sometimes called “pixel shuffle.
- **Why It’s Good**:
- **Lightweight** compared to some of the newer models.
- Typically **fast** to run on CPU or GPU.
- Good results up to 4with minimal artifacts.
- **Trade-off**:
- Not quite as sharp as some heavier models like EDSR when upscaled a lot.
---
## **2. EDSR (Enhanced Deep Super Resolution)**
**Model file:** `EDSR_x2.pb`, `EDSR_x4.pb`, etc.
- **Key Idea**: Builds on SRResNet and other deep CNN architectures with “residual blocks.
- **Why It’s Good**:
- Often considered **state-of-the-art** or near it for many super-resolution tasks in 24upscaling.
- Produces **sharper details** than ESPCN in many cases.
- **Trade-off**:
- Typically **larger** and **slower** than ESPCN because it’s a deeper network.
- More VRAM usage if using a GPU.
---
## **3. FSRCNN (Fast Super Resolution Convolutional Neural Network)**
**Model file:** `FSRCNN_x2.pb`, `FSRCNN_x4.pb`, etc.
- **Key Idea**: A re-architected version of SRCNN with **faster** upsampling stages and smaller filter sizes to keep it lightweight.
- **Why It’s Good**:
- Very **fast** and **compact**—ideal for real-time or mobile scenarios.
- Lower memory footprint than EDSR.
- **Trade-off**:
- May produce slightly **softer** results than EDSR or other heavier models at high scales (like 4.
- Great if your main concern is speed rather than absolute best detail.
---
## **4. LAPSRN (Laplacian Pyramid Super-Resolution Network)**
**Model file:** `LAPSRN_x4.pb`, `LAPSRN_x8.pb`, etc.
- **Key Idea**: Uses a **Laplacian pyramid** framework, progressively predicting residuals at multiple scales.
- **Why It’s Good**:
- Can handle **larger scaling** factors (e.g., 8 in a single pass.
- Often quite **robust** at upscaling texture details.
- **Trade-off**:
- Similar to EDSR, can be heavier and slower for older CPUs/GPUs.
- May introduce a bit of “smoothnessif you push it very high.
---
### **Which Model Should You Choose?**
- **ESPCN**
- Great for **4or less** with relatively **fast** performance and decent quality.
- **EDSR**
- If you want **best possible detail** at **24* and don’t mind a bit more computation.
- **FSRCNN**
- If you need a **real-time** or a **very fast** approach.
- **LAPSRN**
- If you require **bigger scales** (like 8 or want a pyramid-based upscaling approach."
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