Upload 3 files

app.py

@@ -1,28 +1,26 @@
 import os
 import gradio as gr
 import torch
-from diffusers import StableDiffusionPipeline
+from diffusers import DDPMPipeline
 import warnings
 warnings.filterwarnings('ignore')
 
 # Constants
-MODEL_ID = "google/ddpm-celebahq-256"  # Using a simpler model
+MODEL_ID = "google/ddpm-celebahq-256"
 DEVICE = "cpu"  # Force CPU for better compatibility
 DTYPE = torch.float32
 
-def generate_image(prompt, negative_prompt, guidance_scale=7.5, steps=30):
+def generate_image(steps=30):
     try:
         # Initialize pipeline with basic settings
-        pipe = StableDiffusionPipeline.from_pretrained(MODEL_ID)
+        pipe = DDPMPipeline.from_pretrained(MODEL_ID)
         pipe = pipe.to(DEVICE)
         
         # Generate image
         with torch.inference_mode():
             image = pipe(
-                prompt=prompt,
-                negative_prompt=negative_prompt,
+                batch_size=1,
                 num_inference_steps=steps,
-                guidance_scale=guidance_scale,
             ).images[0]
         
         return image
@@ -33,38 +31,17 @@ def generate_image(prompt, negative_prompt, guidance_scale=7.5, steps=30):
 # Create the Gradio interface
 with gr.Blocks(title="Simple Image Generator") as demo:
     gr.Markdown("# 🎨 Simple Image Generator")
-    gr.Markdown("Generate images with text prompts")
+    gr.Markdown("Generate celebrity-like faces using DDPM")
     
     with gr.Row():
         with gr.Column():
-            prompt = gr.Textbox(
-                label="Prompt",
-                placeholder="Enter your image description here...",
-                info="Be specific and descriptive for better results"
+            steps = gr.Slider(
+                minimum=10,
+                maximum=50,
+                value=30,
+                step=1,
+                label="Steps"
             )
-            negative_prompt = gr.Textbox(
-                label="Negative Prompt",
-                placeholder="What you don't want in the image...",
-                info="Specify unwanted elements",
-                value="ugly, blurry, low quality"
-            )
-            
-            with gr.Row():
-                steps = gr.Slider(
-                    minimum=10,
-                    maximum=50,
-                    value=30,
-                    step=1,
-                    label="Steps"
-                )
-                
-                guidance_scale = gr.Slider(
-                    minimum=1.0,
-                    maximum=20.0,
-                    value=7.5,
-                    step=0.1,
-                    label="Guidance Scale"
-                )
             
             generate_btn = gr.Button("🎨 Generate", variant="primary")
         
@@ -74,9 +51,6 @@ with gr.Blocks(title="Simple Image Generator") as demo:
     generate_btn.click(
         fn=generate_image,
         inputs=[
-            prompt,
-            negative_prompt,
-            guidance_scale,
             steps,
         ],
         outputs=output_image

requirements.txt

@@ -4,5 +4,3 @@ diffusers==0.2.4
 transformers==4.18.0
 accelerate==0.12.0
 gradio==3.16.2
-opencv-python==4.8.0.74
-einops==0.6.1