qwenimageedit

app_local.py

@@ -15,8 +15,8 @@ import math
 import json  # Added json import
 from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
 import logging
-import copy
 from copy import deepcopy
+
 #############################
 os.environ.setdefault('GRADIO_ANALYTICS_ENABLED', 'False')
 os.environ.setdefault('HF_HUB_DISABLE_TELEMETRY', '1')
@@ -47,21 +47,17 @@ rewriter_model = AutoModelForCausalLM.from_pretrained(
     quantization_config=bnb_config,
 )
 
-# Store original presets for reference
-ORIGINAL_PRESETS = deepcopy(PRESETS)
-
 def get_fresh_presets():
-    return ORIGINAL_PRESETS
+    """Return a fresh copy of presets to avoid persistence across users"""
+    return deepcopy(PRESETS)
 
-preset_state = gr.State(value=get_fresh_presets())
+# Store original presets for reference
+ORIGINAL_PRESETS = deepcopy(PRESETS)
 
-def reset_presets():
-    return get_fresh_presets()
-    
 # Preload enhancement model at startup
-logger.info("🔄 Loading prompt enhancement model...")
+print("🔄 Loading prompt enhancement model...")
 rewriter_tokenizer = AutoTokenizer.from_pretrained(REWRITER_MODEL)
-logger.info("✅ Enhancement model loaded and ready!")
+print("✅ Enhancement model loaded and ready!")
 
 SYSTEM_PROMPT_EDIT = '''
 # Edit Instruction Rewriter
@@ -117,7 +113,7 @@ def extract_json_response(model_output: str) -> str:
         end_idx = model_output.rfind('}')
         # Fix the condition - check if brackets were found
         if start_idx == -1 or end_idx == -1 or start_idx >= end_idx:
-            logger.warning(f"No valid JSON structure found in output. Start: {start_idx}, End: {end_idx}")
+            print(f"No valid JSON structure found in output. Start: {start_idx}, End: {end_idx}")
             return None
         # Expand to the full object including outer braces
         end_idx += 1  # Include the closing brace
@@ -157,8 +153,8 @@ def extract_json_response(model_output: str) -> str:
         if str_values:
             return str_values[0].strip()
     except Exception as e:
-        logger.warning(f"JSON parse error: {str(e)}")
-        logger.warning(f"Model output was: {model_output}")
+        print(f"JSON parse error: {str(e)}")
+        print(f"Model output was: {model_output}")
     return None
 
 def polish_prompt(original_prompt: str) -> str:
@@ -177,10 +173,10 @@ def polish_prompt(original_prompt: str) -> str:
     with torch.no_grad():
         generated_ids = rewriter_model.generate(
             **model_inputs,
-            max_new_tokens=512,
+            max_new_tokens=256,
             do_sample=True,
-            temperature=0.75,
-            top_p=0.85,
+            temperature=0.7,
+            top_p=0.8,
             repetition_penalty=1.1,
             no_repeat_ngram_size=3,
             pad_token_id=rewriter_tokenizer.eos_token_id
@@ -190,8 +186,8 @@ def polish_prompt(original_prompt: str) -> str:
         generated_ids[0][model_inputs.input_ids.shape[1]:],
         skip_special_tokens=True
     ).strip()
-    logger.info(f"Original Prompt: {original_prompt}")
-    logger.info(f"Model raw output: {enhanced}")  # Debug logging
+    print(f"Original Prompt: {original_prompt}")
+    print(f"Model raw output: {enhanced}")  # Debug logging
     # Try to extract JSON content
     rewritten_prompt = extract_json_response(enhanced)
     if rewritten_prompt:
@@ -249,7 +245,7 @@ pipe = QwenImageEditPipeline.from_pretrained(
 pipe.load_lora_weights(
     "lightx2v/Qwen-Image-Lightning",
     # weight_name="Qwen-Image-Lightning-8steps-V1.1.safetensors"
-    weight_name="Qwen-Image-Edit-Lightning-4steps-V1.0.safetensors"
+    weight_name="Qwen-Image-Lightning-4steps-V1.0.safetensors"
 )
 pipe.fuse_lora()
 
@@ -260,7 +256,7 @@ pipe.fuse_lora()
 try:
     pipe.enable_vae_slicing()
 except Exception as e:
-    logger.info(f"VAE Slicing Failed: {e}")
+    print(f"VAE Slicing Failed: {e}")
     
 
 def toggle_output_count(preset_type):
@@ -301,30 +297,39 @@ def update_prompt_preview(preset_type, base_prompt):
         return preview_text
     else:
         return "Select a preset above to see how your base prompt will be modified for batch generation."
-        
-def update_preset_prompt_textbox(preset_type, p1, p2, p3, p4):
-    if preset_type and preset_type in preset_state.value:
-        # Build new preset instead of mutating in place
-        new_preset = {
-            **preset_state.value[preset_type],
-            "prompts": [p1, p2, p3, p4]
-        }
-        preset_state.value[preset_type] = new_preset
-        return update_prompt_preview_with_presets(preset_type, prompt.value, preset_state.value)
-    return "Select a preset first."
-    
+
+def update_preset_prompt_textbox(preset_type, prompt_1, prompt_2, prompt_3, prompt_4):
+    """Update preset prompts based on user input - now works with session copy"""
+    if preset_type and preset_type in ORIGINAL_PRESETS:
+        # Update each prompt in the preset copy (this won't persist globally)
+        new_prompts = [prompt_1, prompt_2, prompt_3, prompt_4]
+        # Create a working copy for preview purposes
+        working_presets = get_fresh_presets()
+        for i, new_prompt in enumerate(new_prompts):
+            if i < len(working_presets[preset_type]["prompts"]):
+                working_presets[preset_type]["prompts"][i] = new_prompt.strip()
+            else:
+                working_presets[preset_type]["prompts"].append(new_prompt.strip())
+        # Return updated preset info for preview
+        return update_prompt_preview_with_presets(preset_type, "your subject", working_presets)
+    return "Select a preset first to edit its prompts."
+
 def update_prompt_preview_with_presets(preset_type, base_prompt, custom_presets):
+    """Update the prompt preview display with custom presets"""
     if preset_type and preset_type in custom_presets:
         preset = custom_presets[preset_type]
         non_empty_prompts = [p for p in preset["prompts"] if p.strip()]
         if not non_empty_prompts:
             return "No prompts defined. Please enter at least one prompt in the editor."
-        preview = f"**Preset: {preset_type}**\n\n{preset['description']}\n\n"
-        preview += f"**Generating {len(non_empty_prompts)} image{'s' if len(non_empty_prompts)>1 else ''}:**\n"
-        for i, pp in enumerate(non_empty_prompts, 1):
-            preview += f"{i}. {base_prompt}, {pp}\n"
-        return preview
-    return "Select a preset to see the preview."
+        preview_text = f"**Preset: {preset_type}**\n\n"
+        preview_text += f"*{preset['description']}*\n\n"
+        preview_text += f"**Generating {len(non_empty_prompts)} image{'s' if len(non_empty_prompts) > 1 else ''}:**\n"
+        for i, preset_prompt in enumerate(non_empty_prompts, 1):
+            full_prompt = f"{base_prompt}, {preset_prompt}"
+            preview_text += f"{i}. {full_prompt}\n"
+        return preview_text
+    else:
+        return "Select a preset above to see how your base prompt will be modified for batch generation."
 
 @spaces.GPU()
 def infer(
@@ -333,7 +338,7 @@ def infer(
     seed=42,
     randomize_seed=False,
     true_guidance_scale=4.0,
-    num_inference_steps=3,
+    num_inference_steps=4,
     rewrite_prompt=True,
     num_images_per_prompt=1,
     preset_type=None,
@@ -341,8 +346,6 @@ def infer(
 ):
     """Image editing endpoint with optimized prompt handling - now uses fresh presets"""
     # Resize image to max 1024px on longest side
-    session_presets = preset_state.value
-
     def resize_image(pil_image, max_size=1024):
         """Resize image to maximum dimension of 1024px while maintaining aspect ratio"""
         try:
@@ -358,10 +361,10 @@ def infer(
             new_height = int(height * scale)
             # Resize image
             resized_image = pil_image.resize((new_width, new_height), Image.LANCZOS)
-            logger.info(f"📝 Image resized from {width}x{height} to {new_width}x{new_height}")
+            print(f"📝 Image resized from {width}x{height} to {new_width}x{new_height}")
             return resized_image
         except Exception as e:
-            logger.warning(f"⚠️ Image resize failed: {e}")
+            print(f"⚠️ Image resize failed: {e}")
             return pil_image  # Return original if resize fails
 
     # Add noise function for batch variation
@@ -379,11 +382,11 @@ def infer(
             noisy_array = (noisy_array * 255).astype(np.uint8)
             return Image.fromarray(noisy_array)
         except Exception as e:
-            logger.warning(f"Warning: Could not add noise to image: {e}")
+            print(f"Warning: Could not add noise to image: {e}")
             return pil_image  # Return original if noise addition fails
 
     # Get fresh presets for this session
-    
+    session_presets = get_fresh_presets()
     
     # Resize input image first
     image = resize_image(image, max_size=1024)
@@ -399,19 +402,19 @@ def infer(
             batch_prompts = [f"{original_prompt}, {preset_prompt}" for preset_prompt in non_empty_preset_prompts]
             num_images_per_prompt = len(non_empty_preset_prompts)  # Use actual count of non-empty prompts
             prompt_info = (
-                f"<div style='margin:10px; padding:15px; border-radius:8px; border-left:4px solid #2196F3;>"
+                f"<div style='margin:10px; padding:15px; border-radius:8px; border-left:4px solid #2196F3; background: #f0f8ff'>"
                 f"<h4 style='margin-top: 0;'>🎨 Preset: {preset_type}</h4>"
                 f"<p>{preset['description']}</p>"
                 f"<p><strong>Base Prompt:</strong> {original_prompt}</p>"
                 f"<p>Generating {len(non_empty_preset_prompts)} image{'s' if len(non_empty_preset_prompts) > 1 else ''}</p>"
                 f"</div>"
             )
-            logger.info(f"Using preset: {preset_type} with {len(batch_prompts)} variations")
+            print(f"Using preset: {preset_type} with {len(batch_prompts)} variations")
         else:
             # Fallback to manual if no valid prompts
             batch_prompts = [prompt]
             prompt_info = (
-                f"<div style='margin:10px; padding:15px; border-radius:8px; border-left:4px solid #FF9800;>"
+                f"<div style='margin:10px; padding:15px; border-radius:8px; border-left:4px solid #FF9800; background: #fff8f0'>"
                 f"<h4 style='margin-top: 0;'>⚠️ Invalid Preset</h4>"
                 f"<p>No valid prompts found. Using manual prompt.</p>"
                 f"<p><strong>Prompt:</strong> {original_prompt}</p>"
@@ -420,13 +423,12 @@ def infer(
     else:
         batch_prompts = [prompt]  # Single prompt in list
         # Handle regular prompt rewriting
-        
         if rewrite_prompt:
             try:
                 enhanced_instruction = polish_prompt(original_prompt)
                 if enhanced_instruction and enhanced_instruction != original_prompt:
                     prompt_info = (
-                        f"<div style='margin:10px; padding:15px; border-radius:8px; border-left:4px solid #4CAF50;>"
+                        f"<div style='margin:10px; padding:15px; border-radius:8px; border-left:4px solid #4CAF50; background: #f5f9fe'>"
                         f"<h4 style='margin-top: 0;'>🚀 Prompt Enhancement</h4>"
                         f"<p><strong>Original:</strong> {original_prompt}</p>"
                         f"<p><strong style='color:#2E7D32;'>Enhanced:</strong> {enhanced_instruction}</p>"
@@ -435,23 +437,23 @@ def infer(
                     batch_prompts = [enhanced_instruction]
                 else:
                     prompt_info = (
-                        f"<div style='margin:10px; padding:15px; border-radius:8px; border-left:4px solid #FF9800;>"
+                        f"<div style='margin:10px; padding:15px; border-radius:8px; border-left:4px solid #FF9800; background: #fff8f0'>"
                         f"<h4 style='margin-top: 0;'>📝 Prompt Enhancement</h4>"
                         f"<p>No enhancement applied or enhancement failed</p>"
                         f"</div>"
                     )
             except Exception as e:
-                logger.warning(f"Prompt enhancement error: {str(e)}")  # Debug logging
+                print(f"Prompt enhancement error: {str(e)}")  # Debug logging
                 gr.Warning(f"Prompt enhancement failed: {str(e)}")
                 prompt_info = (
-                    f"<div style='margin:10px; padding:15px; border-radius:8px; border-left:4px solid #FF5252;>"
+                    f"<div style='margin:10px; padding:15px; border-radius:8px; border-left:4px solid #FF5252; background: #fef5f5'>"
                     f"<h4 style='margin-top: 0;'>⚠️ Enhancement Not Applied</h4>"
                     f"<p>Using original prompt. Error: {str(e)[:100]}</p>"
                     f"</div>"
                 )
         else:
             prompt_info = (
-                f"<div style='margin:10px; padding:10px; border-radius:8px;>"
+                f"<div style='margin:10px; padding:10px; border-radius:8px; background: #f8f9fa'>"
                 f"<h4 style='margin-top: 0;'>📝 Original Prompt</h4>"
                 f"<p>{original_prompt}</p>"
                 f"</div>"
@@ -481,10 +483,10 @@ def infer(
                 num_inference_steps=num_inference_steps,
                 generator=generator,
                 true_cfg_scale=varied_guidance,
-                num_images_per_prompt=2
+                num_images_per_prompt=1
             ).images
             edited_images.extend(result)
-            logger.info(f"Generated image {i+1}/{len(batch_prompts)} with prompt: {current_prompt}...")
+            print(f"Generated image {i+1}/{len(batch_prompts)} with prompt: {current_prompt[:75]}...")
         # Clear cache after generation
         # if device == "cuda":
         #     torch.cuda.empty_cache()
@@ -497,17 +499,23 @@ def infer(
             gc.collect()
         gr.Error(f"Image generation failed: {str(e)}")
         return [], base_seed, (
-            f"<div style='margin:10px; padding:15px; border-radius:8px; border-left:4px solid #dd2c00;>"
+            f"<div style='margin:10px; padding:15px; border-radius:8px; border-left:4px solid #dd2c00; background: #fef5f5'>"
             f"<h4 style='margin-top: 0;'>⚠️ Processing Error</h4>"
             f"<p>{str(e)[:200]}</p>"
             f"</div>"
         )
 
-with gr.Blocks(title="'Qwen Image Edit' Model Playground & Showcase [4-Step Lightning Mode]") as demo:
+with gr.Blocks(title="Qwen Image Edit - Fast Lightning Mode w/ Batch") as demo:
     preset_prompts_state = gr.State(value=[])
     # preset_prompts_state = gr.State(value=["", "", "", ""])
-    preset_state = gr.State(value=ORIGINAL_PRESETS)
-    gr.Markdown("## ⚡️ Qwen-Image-Edit Lightning Presets")
+
+    gr.Markdown("""
+    <div style="text-align: center; background: linear-gradient(to right, #3a7bd5, #00d2ff); color: white; padding: 20px; border-radius: 8px;">
+        <h1 style="margin-bottom: 5px;">⚡️ Qwen-Image-Edit Lightning</h1>
+        <p>✨ 4-step inferencing with lightx2v's LoRA.</p>
+        <p>📝 Local Prompt Enhancement, Batched Multi-image Generation, 🎨 Preset Batches</p>
+    </div>
+    """)
     
     with gr.Row(equal_height=True):
         # Input Column
@@ -516,15 +524,8 @@ with gr.Blocks(title="'Qwen Image Edit' Model Playground & Showcase [4-Step Ligh
                 label="Source Image",
                 type="pil",
                 height=300
-            )
-        with gr.Column(scale=2):
-            result = gr.Gallery(
-                label="Edited Images",
-                columns=2,
-                container=True
-            )
-    with gr.Row():
-        with gr.Column(scale=1):
+            )            
+
             prompt = gr.Textbox(
                 label="Edit Instructions / Base Prompt",
                 placeholder="e.g. Replace the background with a beach sunset... When a preset is selected, use as the base prompt, e.g. the lamborghini",
@@ -547,11 +548,13 @@ with gr.Blocks(title="'Qwen Image Edit' Model Playground & Showcase [4-Step Ligh
                 preset_prompt_2 = gr.Textbox(label="Prompt 2", lines=1, value="")
                 preset_prompt_3 = gr.Textbox(label="Prompt 3", lines=1, value="")
                 preset_prompt_4 = gr.Textbox(label="Prompt 4", lines=1, value="")
-                
-                update_preset_button = gr.Button("Update Preset", variant="secondary", visible=False)
-                reset_button = gr.Button("Reset Presets", variant="stop", visible=False)
-
-
+                update_preset_button = gr.Button("Update Preset", variant="secondary")
+            
+            rewrite_toggle = gr.Checkbox(
+                label="Enable Prompt Enhancement",
+                value=True,
+                interactive=True
+            )
             
             # Add prompt preview component
             prompt_preview = gr.Textbox(
@@ -562,14 +565,6 @@ with gr.Blocks(title="'Qwen Image Edit' Model Playground & Showcase [4-Step Ligh
                 value="Enter a base prompt and select a preset above to see how your prompt will be modified for batch generation.",
                 placeholder="Prompt preview will appear here..."
             )
-            
-            rewrite_toggle = gr.Checkbox(
-                label="Additional Prompt Enhancement",
-                info="Setting this to true will pass the basic prompt(s) generated via the static preset template to a secondary LLM tasked with improving the overall cohesiveness and details of the final generation prompt.",
-                value=True,
-                interactive=True
-            )
-            
             run_button = gr.Button(
                 "Generate Edit(s)",
                 variant="primary"
@@ -593,14 +588,14 @@ with gr.Blocks(title="'Qwen Image Edit' Model Playground & Showcase [4-Step Ligh
                         minimum=1.0,
                         maximum=10.0,
                         step=0.1,
-                        value=1.1
+                        value=1.0
                     )
                     num_inference_steps = gr.Slider(
                         label="Inference Steps",
-                        minimum=1,
+                        minimum=2,
                         maximum=16,
                         step=1,
-                        value=3
+                        value=4
                     )
                     
                 num_images_per_prompt = gr.Slider(
@@ -612,33 +607,45 @@ with gr.Blocks(title="'Qwen Image Edit' Model Playground & Showcase [4-Step Ligh
                     interactive=True
                 )
                 
+        # Output Column
         with gr.Column(scale=2):
-            prompt_info = gr.Markdown(
+            result = gr.Gallery(
+                label="Edited Images",
+                columns=lambda x: min(x, 2),
+                height=500,
+                object_fit="cover",
+                preview=True
+            )
+            prompt_info = gr.HTML(
                 value="<div style='padding:15px; margin-top:15px'>"
-                "Hint: depending on the original image, prompt quality, and complexity, you can often get away with 3 steps, even 2 steps without much loss in quality. </div>"
+                "Prompt details will appear after generation. Ability to edit Preset Prompts on the fly will be implemented shortly.</div>"
             )
-        
-    
+
+    # Fix the show_preset_editor function to use ORIGINAL_PRESETS:
     def show_preset_editor(preset_type):
-        if preset_type and preset_type in preset_state.value:
-            preset = preset_state.value[preset_type]
-            prompts = preset["prompts"] + [""] * (4 - len(preset["prompts"]))
-            return gr.Group(visible=True), *prompts[:4]
+        if preset_type and preset_type in ORIGINAL_PRESETS:  # Changed from PRESETS to ORIGINAL_PRESETS
+            preset = ORIGINAL_PRESETS[preset_type]
+            prompts = preset["prompts"]
+            # Pad prompts to 4 items if needed
+            while len(prompts) < 4:
+                prompts.append("")
+            return gr.Group(visible=True), prompts[0], prompts[1], prompts[2], prompts[3]
         return gr.Group(visible=False), "", "", "", ""
-        
-    def update_preset_count(preset_type, p1, p2, p3, p4):
-        if preset_type and preset_type in preset_state.value:
-            count = len([p for p in (p1,p2,p3,p4) if p.strip()])
-            return gr.Slider(value=max(1, min(4, count)), interactive=False)
+    
+    # Fix the update_preset_count function to use ORIGINAL_PRESETS:
+    def update_preset_count(preset_type, prompt_1, prompt_2, prompt_3, prompt_4):
+        """Update the output count slider based on non-empty preset prompts"""
+        if preset_type and preset_type in ORIGINAL_PRESETS:  # Changed from PRESETS to ORIGINAL_PRESETS
+            non_empty_count = len([p for p in [prompt_1, prompt_2, prompt_3, prompt_4] if p.strip()])
+            return gr.Slider(value=max(1, min(4, non_empty_count)), interactive=False)
         return gr.Slider(interactive=True)
 
     # Update the preset_dropdown.change handlers to use ORIGINAL_PRESETS
     preset_dropdown.change(
-        fn=show_preset_editor,
-        inputs=[preset_dropdown],
-        outputs=[preset_editor, preset_prompt_1, preset_prompt_2, preset_prompt_3, preset_prompt_4]
+        fn=toggle_output_count,
+        inputs=preset_dropdown,
+        outputs=[preset_editor, num_images_per_prompt, preset_prompt_1, preset_prompt_2, preset_prompt_3, preset_prompt_4]
     )
-
     
     preset_dropdown.change(
         fn=update_prompt_preview,
@@ -646,28 +653,6 @@ with gr.Blocks(title="'Qwen Image Edit' Model Playground & Showcase [4-Step Ligh
         outputs=prompt_preview
     )
 
-    preset_prompt_1.change(
-        fn=update_preset_prompt_textbox,
-        inputs=[preset_dropdown, preset_prompt_1, preset_prompt_2, preset_prompt_3, preset_prompt_4],
-        outputs=prompt_preview
-    )
-
-    preset_prompt_2.change(
-        fn=update_preset_prompt_textbox,
-        inputs=[preset_dropdown, preset_prompt_1, preset_prompt_2, preset_prompt_3, preset_prompt_4],
-        outputs=prompt_preview
-    )
-    preset_prompt_3.change(
-        fn=update_preset_prompt_textbox,
-        inputs=[preset_dropdown, preset_prompt_1, preset_prompt_2, preset_prompt_3, preset_prompt_4],
-        outputs=prompt_preview
-    )
-    preset_prompt_4.change(
-        fn=update_preset_prompt_textbox,
-        inputs=[preset_dropdown, preset_prompt_1, preset_prompt_2, preset_prompt_3, preset_prompt_4],
-        outputs=prompt_preview
-    )
-
     preset_prompt_1.change(
         fn=update_preset_count,
         inputs=[preset_dropdown, preset_prompt_1, preset_prompt_2, preset_prompt_3, preset_prompt_4],
@@ -720,14 +705,10 @@ with gr.Blocks(title="'Qwen Image Edit' Model Playground & Showcase [4-Step Ligh
         inputs=inputs,
         outputs=outputs
     )
-    # .then(
-    #     fn=reset_presets, outputs=preset_state
-    # )
     prompt.submit(
         fn=infer,
         inputs=inputs,
         outputs=outputs
     )
-    reset_button.click(fn=reset_presets, outputs=preset_state)
 
 demo.queue(max_size=5).launch()

presets.py

@@ -30,9 +30,9 @@ PRESETS = {
         "prompts": [
             "frontal view of the subject, facing camera directly",
             "side view of subject, profile view from the side", 
-            "dutch angle shot of subject, candid photography"
+            "back side view of subject, showing the rear/back view"
         ],
-        "description": "Generate three different views of the subject"
+        "description": "Generate 4 different views of the subject"
     },
     "Style Variations": {
         "count": 3, 
@@ -61,143 +61,16 @@ PRESETS = {
         ],
         "description": "Show the subject in different hairstyles"
     },
-    "Seasonal Themes": {
-        "count": 4,
+    "Color Comparison": {
+        "count": 2,
         "prompts": [
-            "in a snowy winter landscape, snowflakes falling gently",
-            "in a sunny summer meadow, bright sunshine",
-            "in a crisp autumn forest, leaves turning orange",
-            "in a misty spring garden, blooming flowers"
+            "painted in matte black paint and red accents",
+            "covered in gold glitter over white fabric"
         ],
-        "description": "Render the subject in each of the four seasons"
-    },
-    
-    "Emotional Mood": {
-        "count": 4,
-        "prompts": [
-            "with a joyful grin, eyes sparkling",
-            "with a thoughtful expression, slightly furrowed brow",
-            "with a dramatic, intense stare",
-            "with a gentle, serene smile"
-        ],
-        "description": "Show the subject’s emotions in four different moods"
-    },
-    
-    "Historical Eras": {
-        "count": 4,
-        "prompts": [
-            "in Victorian England, ornate lace and corset",
-            "in the 1980s, neon lights and big hair",
-            "in a medieval castle, knight armor",
-            "in a futuristic cyber‑punk city, holographic backdrop"
-        ],
-        "description": "Place the subject in four iconic time periods"
-    },
-    
-    "Camera Lens Effects": {
-        "count": 4,
-        "prompts": [
-            "captured with a wide‑angle lens, exaggerated perspective",
-            "shot with a telephoto lens, shallow depth of field",
-            "taken with a fisheye lens, circular distortion",
-            "rendered with a macro lens, extreme close‑up detail"
-        ],
-        "description": "Play with different lens styles for the same subject"
-    },
-    
-    "Fantasy Elements": {
-        "count": 3,
-        "prompts": [
-            "surrounded by a swirling vortex of light",
-            "hovering above a floating island in the clouds",
-            "paired with a companion dragon, breathing fire",
-        ],
-        "description": "Add a fantastical twist to each rendition"
-    },
-    
-    "Texture Variations": {
-        "count": 3,
-        "prompts": [
-            "covered in soft velvet, plush texture",
-            "painted with glossy enamel, shiny finish",
-            "wrapped in intricate lace patterns",
-        ],
-        "description": "Show the subject in three distinct surface textures"
-    },
-    
-    "Color Palette Swaps": {
-        "count": 3,
-        "prompts": [
-            "in pastel colors, soft hues",
-            "with neon saturation, high‑contrast glow",
-            "in monochrome black & white, dramatic contrast"
-        ],
-        "description": "Recolor the subject with three distinct palettes"
-    },
-    "Runway Catwalk": {
-        "count": 4,
-        "prompts": [
-            "strutting down a glossy runway, spotlight on the model",
-            "walking confidently with a high‑fashion backdrop",
-            "posing with a dramatic, angular pose on the catwalk",
-            "showcasing an avant‑garde ensemble, dramatic lighting"
-        ],
-        "description": "Capture the model on a high‑end runway"
-    },
-
-    "Vogue Editorial": {
-        "count": 3,
-        "prompts": [
-            "editorial shot with a moody, artistic background",
-            "intimate close‑up, dramatic lighting and subtle shadows",
-            "wide‑angle full‑body shot, striking composition"
-        ],
-        "description": "Create a magazine‑quality editorial spread"
-    },
-    "Evening Gown Glam": {
-        "count": 3,
-        "prompts": [
-            "floor‑length ballroom gown, shimmering crystal embellishments",
-            "gold‑en, reflective lighting, chandelier backdrop",
-            "soft, ethereal glow, elegant pose"
-        ],
-        "description": "Render an elegant evening dress in glamorous lighting"
-    },
-    
-    "Chic Streetwear": {
-        "count": 4,
-        "prompts": [
-            "urban street backdrop, high‑contrast graffiti walls",
-            "modern athleisure look, bold colors and textures",
-            "casual, relaxed pose with a casual jacket and sneakers",
-            "dynamic movement shot, capturing fluidity"
-        ],
-        "description": "Showcase the model in trendy street‑style attire"
-    },
-    "Swimwear Showcase": {
-        "count": 4,
-        "prompts": [
-            "wearing a vibrant neon bikini, sunny beach background",
-            "in a sleek one‑piece with high‑waisted cut, poolside setting",
-            "sporty swim trunks and matching tank top, surfing wave backdrop",
-            "coastal vibe with a chic cover‑up over a solid‑color swimsuit"
-        ],
-        "description": "Highlight the model in four distinct swimwear styles, from bold bikinis to elegant one‑pieces and sporty swimwear"
-    },
-    "Polaroid and Film": {
-        "count": 4,
-        "prompts": [
-            "captured in a vintage Polaroid frame, sepia‑tone filter, soft vignette",
-            "black‑and‑white film shot with a slight grain, high‑contrast lighting",
-            "soft focus, pastel color palette with a subtle yellow tint, nostalgic feel",
-            "classic instant camera style, square format, warm lighting, subtle bokeh"
-        ],
-        "description": "Generate a nostalgic Polaroid/film aesthetic across four different looks"
+        "description": "Simple two-tone color comparison"
     }
 }
 
-
-
 def get_preset_choices():
     """
     Return list of preset choices for Gradio dropdown.