Update README.md

README.md

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-license: openrail
+license: bigscience-openrail-m
+base_model:
+- MiniMaxAI/MiniMax-H3-Image
 ---
+
+**NOTE Encoder was Frozen Using this VAE for Training should not effect outcome**
+
+## Overview
+
+This repository contains evaluation results for a **MiniMax Image HDR VAE (High Dynamic Range Variational Autoencoder)** designed for MiniMax-H3 image reconstruction and enhancement workflows.
+
+The HDR VAE is evaluated against the **BASE MiniMax Image VAE** using a multi-domain reconstruction analysis covering:
+
+* perceptual similarity
+* structural energy enhancement
+* color distribution changes
+* saturation enhancement
+* sharpness and high-frequency detail
+* channel-level color differences
+
+The objective is not only to measure pixel reconstruction accuracy, but to evaluate how the VAE enhances image characteristics through the encode/decode pipeline.
+
+### Image Enhancement
+
+Measured through reconstruction comparisons:
+
+* RGB pixel deviation
+* saturation changes
+* gradient energy
+* sharpness retention
+* contrast gain
+* high-frequency energy
+* perceptual color difference (DeltaE)
+
+These evaluate how reconstruction changes image detail, color intensity, sharpness, and structural information.
+
+---
+
+# Results Summary
+
+## BASE MiniMax Image VAE vs HDR VAE
+
+| Metric                        | BASE MiniMax VAE | HDR VAE |
+| ----------------------------- | ---------------: | ------: |
+| PSNR ↑                        | **32.4389** | 28.4966 |
+| SSIM ↑                        | 0.87133 | **0.87810** |
+| RGB MAE ↓                     | **0.015623** | 0.028214 |
+| Saturation MAE ↓              | **0.034885** | 0.091786 |
+| Gradient Energy Retention     | 0.98014 | **1.05029** |
+| Sharpness Retention           | **0.96952** | 0.91151 |
+| Contrast Retention            | 1.01329 | 1.00179 |
+| High-Frequency Retention      | 0.96159 | **1.04110** |
+| DeltaE ↓                      | **2.7502** | 7.0100 |
+
+---
+
+# Interpretation
+
+The **BASE MiniMax Image VAE** achieves lower pixel reconstruction error and DeltaE, indicating closer numerical agreement with the original input.
+
+The **HDR VAE** demonstrates a different reconstruction profile:
+
+* increased gradient energy
+* increased high-frequency energy
+* higher structural similarity
+* stronger saturation changes
+* enhancement-oriented reconstruction behavior
+
+The HDR VAE behaves as an enhancement-oriented reconstruction operator rather than a pixel-preservation model, producing measurable changes to image characteristics during reconstruction.
+
+---
+
+# Design Goal
+
+The HDR VAE is designed to improve image characteristics that standard VAEs commonly soften or reduce:
+
+* fine texture
+* high-frequency detail
+* local contrast
+* color variation
+* edge definition
+* perceived sharpness
+
+Rather than optimizing only for pixel-level similarity, the HDR VAE emphasizes image enhancement through decoder fine-tuning.
+
+---
+
+# Conclusion
+
+The evaluation demonstrates two different reconstruction profiles:
+
+**BASE MiniMax Image VAE**
+
+* lower PSNR error
+* lower RGB reconstruction error
+* lower DeltaE
+* stronger numerical color preservation
+* more faithful pixel reconstruction
+
+**HDR MiniMax Image VAE**
+
+* higher SSIM
+* increased gradient energy
+* increased high-frequency energy
+* enhancement-oriented reconstruction
+* greater image characteristic variation
+
+The HDR VAE provides an enhancement-oriented reconstruction profile for users seeking increased structural information, richer image characteristics, and enhanced visual detail rather than strict pixel-perfect reconstruction.