Update app.py

app.py

@@ -7,49 +7,21 @@ import torch
 os.environ["OMP_NUM_THREADS"] = str(os.cpu_count())
 torch.set_num_threads(os.cpu_count())
 
-# Load the Turbo Realism model
+# Load only the Turbo Realism model
 model = gr.load("models/prithivMLmods/SD3.5-Turbo-Realism-2.0-LoRA")
 stop_event = threading.Event()
 
-def generate_images(text, width, height, quality_level, num_inference_steps, guidance_scale):
+def generate_images(text):
     stop_event.clear()
     results = []
     
-    # Create model parameters based on advanced settings
-    model_params = {
-        "width": width,
-        "height": height,
-        "num_inference_steps": num_inference_steps,
-        "guidance_scale": guidance_scale
-    }
-    
-    # Add quality enhancements based on selected level
-    if quality_level == "HD (1080p)":
-        model_params["upscaler"] = "esrgan_x2plus"
-    elif quality_level == "4K":
-        model_params["upscaler"] = "esrgan_x4plus"
-        model_params["upscale_strength"] = 0.8
-    
     for i in range(3):
         if stop_event.is_set():
             return ["Image generation stopped by user."] * 3
         
-        # Add quality descriptors to prompt for better results
-        quality_descriptors = ""
-        if quality_level == "HD (1080p)":
-            quality_descriptors = "high definition, detailed, sharp"
-        elif quality_level == "4K":
-            quality_descriptors = "ultra high definition, extremely detailed, crystal clear, 4k quality"
-        
-        # Create the enhanced prompt
-        modified_text = f"{text}, {quality_descriptors}, variation {i+1}"
-        
-        # Generate image with advanced parameters
-        try:
-            result = model(modified_text, **model_params)
-            results.append(result)
-        except Exception as e:
-            results.append(f"Error: {str(e)}")
+        modified_text = f"{text} variation {i+1}"
+        result = model(modified_text)
+        results.append(result)
     
     return results
 
@@ -58,110 +30,40 @@ def stop_generation():
     stop_event.set()
     return ["Generation stopped."] * 3
 
-# Preset resolution options
-def get_resolution_presets(choice):
-    presets = {
-        "SD (480p)": (640, 480),
-        "HD (1080p)": (1920, 1080),
-        "4K": (3840, 2160),
-        "Square": (1024, 1024),
-        "Portrait": (1080, 1920),
-        "Landscape": (1920, 1080),
-        "Custom": None  # Will keep current values
-    }
-    
-    if choice in presets and presets[choice] is not None:
-        return presets[choice][0], presets[choice][1]
-    return gr.update(), gr.update()  # No change for custom
-
 with gr.Blocks() as interface:
     # Warning message
     gr.Markdown(
         "### ⚠ Sorry for the inconvenience. The Space is currently running on the CPU, which might affect performance. We appreciate your understanding."
     )
     
-    # Title and description
-    gr.Markdown("# Advanced Image Generator")
-    gr.Markdown("Generate high-quality images with customizable settings")
-    
     # Input area
-    with gr.Group():
-        text_input = gr.Textbox(
-            label="Type here your imagination:", 
-            placeholder="Type your prompt...",
-            lines=3
-        )
-    
-    # Advanced settings in collapsible section
-    with gr.Accordion("Advanced Settings", open=True):
-        with gr.Row():
-            resolution_preset = gr.Dropdown(
-                choices=["SD (480p)", "HD (1080p)", "4K", "Square", "Portrait", "Landscape", "Custom"],
-                value="HD (1080p)",
-                label="Resolution Preset"
-            )
-        
-        with gr.Row():
-            width = gr.Slider(minimum=256, maximum=3840, value=1920, step=64, label="Width")
-            height = gr.Slider(minimum=256, maximum=2160, value=1080, step=64, label="Height")
-        
-        with gr.Row():
-            quality_level = gr.Radio(
-                choices=["Standard", "HD (1080p)", "4K"],
-                value="HD (1080p)",
-                label="Quality Level"
-            )
-        
-        with gr.Row():
-            num_inference_steps = gr.Slider(
-                minimum=20, maximum=150, value=50, step=5,
-                label="Inference Steps (Higher = Better Quality, Slower)"
-            )
-            guidance_scale = gr.Slider(
-                minimum=1.0, maximum=20.0, value=7.5, step=0.5,
-                label="Guidance Scale (Higher = More Prompt Adherence)"
-            )
-    
-    # Connect the resolution preset to the width and height sliders
-    resolution_preset.change(get_resolution_presets, inputs=[resolution_preset], outputs=[width, height])
+    text_input = gr.Textbox(
+        label="Type here your imagination:", 
+        placeholder="Type your prompt..."
+    )
     
     # Buttons
     with gr.Row():
-        generate_button = gr.Button("Generate 3 Images 🎨", variant="primary")
-        stop_button = gr.Button("Stop Image Generation", variant="secondary")
+        generate_button = gr.Button("Generate 3 Images 🎨")
+        stop_button = gr.Button("Stop Image Generation")
     
     # Output images
     with gr.Row():
-        output1 = gr.Image(label="Generated Image 1", type="pil")
-        output2 = gr.Image(label="Generated Image 2", type="pil")
-        output3 = gr.Image(label="Generated Image 3", type="pil")
-    
-    # Generation status
-    status = gr.Textbox(label="Status", value="Ready", interactive=False)
+        output1 = gr.Image(label="Generated Image 1")
+        output2 = gr.Image(label="Generated Image 2")
+        output3 = gr.Image(label="Generated Image 3")
     
     # Set up the event handlers
     generate_button.click(
-        fn=lambda: "Generating images... Please wait.", 
-        inputs=None, 
-        outputs=status
-    ).then(
         generate_images, 
-        inputs=[text_input, width, height, quality_level, num_inference_steps, guidance_scale], 
+        inputs=[text_input], 
         outputs=[output1, output2, output3]
-    ).then(
-        fn=lambda: "Generation complete!", 
-        inputs=None, 
-        outputs=status
     )
     
     stop_button.click(
         stop_generation, 
         inputs=[], 
         outputs=[output1, output2, output3]
-    ).then(
-        fn=lambda: "Generation stopped by user.", 
-        inputs=None, 
-        outputs=status
     )
 
 interface.launch()