general distr

README.md

@@ -14,6 +14,8 @@ Currently implemented methods:
   Example: `custom_pipeline.load_initial_noise_modifier(method="fixed-seed", seed=…)`
 -  Golden Noise for Diffusion Models: A Learning Framework (Zhou et al., https://arxiv.org/abs/2411.09502). 
   Example: `custom_pipeline.load_initial_noise_modifier(method="golden-noise", npnet_path=…)`
+- General Normal Distribution: Sample from a user defined General Normal Distribution
+  Example: `custom_pipeline.load_initial_noise_modifier(method="general-normal-distribution", init_noise_mean=(0, -0.1, 0.2, 0), init_noise_std=(1, 1, 1, 1)])`
 
 
 
@@ -89,4 +91,22 @@ Code adapted from [Github Repo](https://github.com/xie-lab-ml/Golden-Noise-for-D
       primaryClass={cs.LG},
       url={https://arxiv.org/abs/2411.09502}, 
 }
-``` 
+``` 
+
+## Example 3: General Normal Distribution
+
+The latent space of SDXL is a 4-channel tensor with interpretable semantics. Channel 1 primarily encodes luminance or overall brightness, while Channel 2 captures the cyan–red color axis, and Channel 3 represents the green–blue axis. Channel 4 encodes structure and patterns.
+
+By manipulating the mean values of these channels—particularly those associated with color—you can bias the generation process toward specific visual tones or styles. This allows for a degree of control over the image's color palette directly in the latent space, without modifying the text prompt or conditioning vectors.
+<div style="display: flex; justify-content: space-between; align-items: center;">
+  <div style="text-align: center; flex: 1; margin-right: 10px;">
+    <img src="examples/mountain_blue.png" alt="Blue, purple tone" style="width:100%;">
+    <p><em>(a) Biased toward blue and purple tones</em></p>
+  </div>
+  <div style="text-align: center; flex: 1; margin-left: 10px;">
+    <img src="examples/mountain_red.png" alt="Red, orange tone" style="width:100%;">
+    <p><em>(b) Biased toward red and orange tones</em></p>
+  </div>
+</div>
+
+<p style="text-align: center;"><strong>Figure:</strong> Controlling the latent space color distribution biases the generation toward different global color schemes.</p>