Rename rotona.py to app.py

app.py

@@ -0,0 +1,35 @@
+import torch
+import gradio as gr
+from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
+
+# Load Model
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model_id = "runwayml/stable-diffusion-v1-5"
+pipeline = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16 if device == "cuda" else torch.float32)
+pipeline.safety_checker = None
+pipeline.scheduler = DPMSolverMultistepScheduler.from_config(pipeline.scheduler.config)
+pipeline = pipeline.to(device)
+
+# Image generation function
+def generate_image(prompt):
+    negative_prompt = "blurry, distorted, bad anatomy, missing fingers, extra limbs, bad proportions, deformed hands, low quality, cropped, out of frame, partial body, cut off, head cut off"
+    refined_prompt = f"{prompt}, centered, full body, well-framed, symmetrical"
+
+    with torch.no_grad():
+        image = pipeline(refined_prompt, negative_prompt=negative_prompt, guidance_scale=7.5, num_inference_steps=50).images[0]
+
+    torch.cuda.empty_cache()  # Free GPU memory
+    return image
+
+# Gradio UI
+interface = gr.Interface(
+    fn=generate_image,
+    inputs=gr.Textbox(label="Enter Your Prompt"),
+    outputs=gr.Image(label="Generated Image"),
+    title="Rotona: Unrestricted Image Generator",
+    description="Enter a prompt to generate an AI image. This model is unrestricted—use responsibly."
+)
+
+# Launch
+if __name__ == "__main__":
+    interface.launch()

rotona.py

@@ -1,88 +0,0 @@
-import torch
-import tkinter as tk
-from tkinter import filedialog, messagebox
-from PIL import Image, ImageTk
-from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
-
-# Initialize Stable Diffusion
-model_id = "runwayml/stable-diffusion-v1-5"
-device = "cuda" if torch.cuda.is_available() else "cpu"
-dtype = torch.float16 if device == "cuda" else torch.float32
-
-print(f"Using device: {device.upper()}")
-
-pipeline = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=dtype)
-pipeline.safety_checker = None  # WARNING: No safety filters—USE RESPONSIBLY
-pipeline.scheduler = DPMSolverMultistepScheduler.from_config(pipeline.scheduler.config)
-pipeline = pipeline.to(device)
-pipeline.enable_attention_slicing()
-
-# GUI Setup
-class RotonaGUI:
-    def __init__(self, root):
-        self.root = root
-        self.root.title("Rotona - Unrestricted AI Image Generator")
-        self.root.geometry("600x700")
-        self.root.configure(bg="black")
-
-        # Title Label
-        self.title_label = tk.Label(root, text="Rotona AI Generator", fg="red", bg="black", font=("Helvetica", 18, "bold"))
-        self.title_label.pack(pady=10)
-
-        # Prompt Entry
-        self.prompt_label = tk.Label(root, text="Enter your prompt:", fg="white", bg="black", font=("Helvetica", 12))
-        self.prompt_label.pack()
-        self.prompt_entry = tk.Entry(root, width=60)
-        self.prompt_entry.pack(pady=5)
-
-        # Generate Button
-        self.generate_button = tk.Button(root, text="Generate Image", command=self.generate_image, bg="red", fg="white", font=("Helvetica", 12, "bold"))
-        self.generate_button.pack(pady=10)
-
-        # Canvas for Displaying Image
-        self.canvas = tk.Canvas(root, width=512, height=512, bg="gray")
-        self.canvas.pack(pady=10)
-
-        # Save Button
-        self.save_button = tk.Button(root, text="Save Image", command=self.save_image, bg="blue", fg="white", font=("Helvetica", 12, "bold"))
-        self.save_button.pack(pady=10)
-        self.save_button["state"] = "disabled"
-
-        self.generated_image = None
-
-    def generate_image(self):
-        user_prompt = self.prompt_entry.get()
-        if not user_prompt:
-            messagebox.showerror("Error", "Please enter a prompt!")
-            return
-
-        try:
-            negative_prompt = "blurry, distorted, bad anatomy, missing fingers, extra limbs, bad proportions, deformed hands, low quality"
-            image = pipeline(user_prompt, negative_prompt=negative_prompt, guidance_scale=7.5, num_inference_steps=50).images[0]
-
-            self.generated_image = image
-            self.display_image(image)
-            self.save_button["state"] = "normal"
-
-        except torch.cuda.OutOfMemoryError:
-            messagebox.showerror("Error", "Out of GPU memory! Try reducing image size.")
-        except Exception as e:
-            messagebox.showerror("Error", f"Image generation failed: {e}")
-
-    def display_image(self, image):
-        image.thumbnail((512, 512))
-        img_tk = ImageTk.PhotoImage(image)
-        self.canvas.create_image(256, 256, image=img_tk)
-        self.canvas.image = img_tk
-
-    def save_image(self):
-        if self.generated_image:
-            file_path = filedialog.asksaveasfilename(defaultextension=".png", filetypes=[("PNG files", "*.png")])
-            if file_path:
-                self.generated_image.save(file_path)
-                messagebox.showinfo("Saved", f"Image saved successfully as {file_path}")
-
-# Run GUI
-root = tk.Tk()
-app = RotonaGUI(root)
-root.mainloop()