Upload README.md

README.md

@@ -1,13 +1,52 @@
----
-title: StableDiffusionModel
-emoji: 🌍
-colorFrom: purple
-colorTo: green
-sdk: gradio
-sdk_version: 4.14.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# ERA_Session20
+
+## Objective:
+The purpose of this repository is to understand the architecture of Generative Art & Stable Diffusion
+
+## Repository:
+```
+.
+├── LICENSE
+├── README.md
+├── config.py
+├── diffusion_loss.py
+├── image_generator.py
+├── inference.ipynb
+├── model.py
+├── prediction.py
+├── requirements.txt
+├── symmetry_loss_analysis.py
+└── utils.py
+```
+
+## How to execute this repository?
+
+In `inference.ipynb`, 
+    - add the prompt in the `prompt` variable
+    - configure the required loss function and execute the prediction function
+
+## Results
+
+`prompt = A King riding a horse`
+
+### 1. Without Loss Function
+
+![Alt text](image.png)
+
+### 2. Blue Channel
+
+Computing the average absolute difference between the `blue channel` values of each pixel in the batch and the target value of `0.9`. This allows us to measure how far, on average the blue channel deviates from the desired value of `0.9` across all images in the batch
+
+![Alt text](image-1.png)
+
+### 3. Elastic Deformations
+
+A data augmentation process. Applying the random elastic deformations to get an input image. The Strength and Smoothness of these deformations are controlled by the `alpha` and `sigma` parameters. The process involves generating displacement vectors for each pixel, adding these vectors to an identified grid, and then using the deformed grid to interpolate pixel values from the original image.
+
+![Alt text](image-2.png)
+
+### 4. Saturation
+
+Applied a saturation adjustment to the images, and the error is calculated as the mean absolute pixel-wise difference between the original and the transformed images
+
+![Alt text](image-3.png)