☸ feat(preprocessing): add ELA image generation presets

- added ability to generate ELA images with different presets for comparison
- updated UI to display multiple ELA images in a gallery

🎉Performance: change_ELA_image_generator_script

- modified ELA preprocessing step
- replace single ELA image generation by presets

app.py

@@ -222,15 +222,23 @@ def generate_results_html(results):
     """
     return html_content
 
+
 def predict_image_with_html(img, confidence_threshold, augment_methods, rotate_degrees, noise_level, sharpen_strength):
     if augment_methods:
         img_pil, _ = augment_image(img, augment_methods, rotate_degrees, noise_level, sharpen_strength)
     else:
         img_pil = img
     img_pil, results = predict_image(img_pil, confidence_threshold)
-    ela_img = ELA(img_pil)  # Apply ELA to the image
+    
+    # Generate ELA images with different presets
+    ela_img_1 = ELA(img_pil, scale=77, alpha=0.66)
+    ela_img_2 = ELA(img_pil, scale=100, alpha=0.8)
+    ela_img_3 = ELA(img_pil, scale=50, alpha=0.5)
+    
+    ela_images = [ela_img_1, ela_img_2, ela_img_3]
+    
     html_content = generate_results_html(results)
-    return img_pil, ela_img, html_content
+    return img_pil, ela_images, html_content
 
 with gr.Blocks() as iface:
     with gr.Tab("AI Image Detection"):
@@ -248,7 +256,7 @@ with gr.Blocks() as iface:
                 inputs = [image_input, confidence_slider, augment_checkboxgroup, rotate_slider, noise_slider, sharpen_slider]
                 predict_button = gr.Button("Predict")
                 image_output = gr.Image(label="Processed Image", visible=True)
-                ela_image_output = gr.Image(label="ELA Processed Image", visible=True)
+                ela_gallery = gr.Gallery(label="ELA Processed Images", visible=True)
 
 
             with gr.Column(scale=2):
@@ -256,7 +264,7 @@ with gr.Blocks() as iface:
                     gr.Markdown("## OpenSight is a SOTA gen. image detection model, in pre-release prep.\n\nThis HF Space is a temporary home for us and the public to evaluate the shortcomings of current open source models.\n\n<-- Feel free to play around by starting with an image as we prepare our formal announcement.")
                 # Custom HTML component to display results in 5 columns
                 results_html = gr.HTML(label="Model Predictions")
-                outputs = [image_output, ela_image_output, results_html]
+                outputs = [image_output, ela_gallery, results_html]
         
         # Show/hide rotate slider based on selected augmentation method
         augment_checkboxgroup.change(lambda methods: gr.update(visible="rotate" in methods), inputs=[augment_checkboxgroup], outputs=[rotate_slider])