Upload 2 files

app.py

@@ -1,35 +1,33 @@
 import os
 import gradio as gr
 import torch
-from diffusers import StableDiffusionXLPipeline, EulerDiscreteScheduler
-from safetensors.torch import load_file
+from diffusers import StableDiffusionPipeline, DDIMScheduler
+import warnings
+warnings.filterwarnings('ignore')
 
 # Constants
-MODEL_ID = "stabilityai/stable-diffusion-xl-base-1.0"
-REFINER_MODEL_ID = "stabilityai/stable-diffusion-xl-refiner-1.0"
+MODEL_ID = "runwayml/stable-diffusion-v1-5"  # Using SD 1.5 for better compatibility
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
-DTYPE = torch.float16 if torch.cuda.is_available() else torch.float32
+DTYPE = torch.float32  # Using float32 for better compatibility
 
 class FooocusGenerator:
     def __init__(self):
         self.pipe = None
-        self.refiner = None
         self.load_models()
 
     def load_models(self):
         # Load base model
-        scheduler = EulerDiscreteScheduler.from_pretrained(MODEL_ID, subfolder="scheduler")
-        self.pipe = StableDiffusionXLPipeline.from_pretrained(
+        scheduler = DDIMScheduler.from_pretrained(MODEL_ID, subfolder="scheduler")
+        self.pipe = StableDiffusionPipeline.from_pretrained(
             MODEL_ID,
             scheduler=scheduler,
             torch_dtype=DTYPE,
-            use_safetensors=True,
-            variant="fp16" if DEVICE == "cuda" else None
+            safety_checker=None
         )
         
         if DEVICE == "cuda":
-            self.pipe.enable_xformers_memory_efficient_attention()
-        self.pipe.to(DEVICE)
+            self.pipe.enable_attention_slicing()
+        self.pipe = self.pipe.to(DEVICE)
 
     def generate_image(
         self,
@@ -42,23 +40,40 @@ class FooocusGenerator:
         image_seed,
         sharpness,
         guidance_scale,
-        base_model_name,
-        refiner_model_name,
         progress=gr.Progress()
     ):
         try:
             # Process style selections
             processed_prompt = self.process_style(prompt, style_selections)
             
-            # Generate the image
-            generator = torch.Generator(device=DEVICE).manual_seed(image_seed)
+            # Set seed for reproducibility
+            if image_seed == -1:
+                image_seed = torch.randint(0, 2147483647, (1,)).item()
+            
+            generator = torch.manual_seed(image_seed)
+            
+            # Set steps based on performance selection
+            steps = {
+                "Speed": 20,
+                "Quality": 30,
+                "Extreme Speed": 15
+            }.get(performance_selection, 30)
+            
+            # Set image dimensions based on aspect ratio
+            dimensions = {
+                "Square": (512, 512),
+                "Portrait": (512, 768),
+                "Landscape": (768, 512)
+            }.get(aspect_ratios_selection, (512, 512))
             
             image = self.pipe(
                 prompt=processed_prompt,
                 negative_prompt=negative_prompt,
-                num_inference_steps=30,
+                num_inference_steps=steps,
                 guidance_scale=guidance_scale,
                 generator=generator,
+                width=dimensions[0],
+                height=dimensions[1]
             ).images[0]
             
             return image
@@ -158,19 +173,6 @@ with gr.Blocks(title="Fooocus Web", theme=gr.themes.Soft()) as demo:
                     label="Guidance Scale"
                 )
             
-            with gr.Row():
-                base_model_name = gr.Dropdown(
-                    choices=["SDXL 1.0"],
-                    label="Base Model",
-                    value="SDXL 1.0"
-                )
-                
-                refiner_model_name = gr.Dropdown(
-                    choices=["SDXL Refiner"],
-                    label="Refiner",
-                    value="SDXL Refiner"
-                )
-            
             generate_btn = gr.Button("🎨 Generate", variant="primary")
         
         with gr.Column():
@@ -190,8 +192,6 @@ with gr.Blocks(title="Fooocus Web", theme=gr.themes.Soft()) as demo:
             image_seed,
             sharpness,
             guidance_scale,
-            base_model_name,
-            refiner_model_name
         ],
         outputs=output_image
     )

requirements.txt

@@ -1,14 +1,15 @@
-torch==2.2.1
-transformers>=4.36.2
-accelerate==0.25.0
-safetensors==0.4.1
+torch==2.0.1
+torchvision==0.15.2
+transformers==4.30.2
+accelerate==0.21.0
+safetensors==0.3.1
 gradio==4.19.2
-diffusers==0.24.0
-opencv-python>=4.8.1.78
-einops>=0.7.0
-pytorch_lightning>=2.1.3
-omegaconf>=2.3.0
-peft>=0.7.1
-xformers>=0.0.23.post1
-triton>=2.1.0
-compel>=2.0.2
+diffusers==0.19.3
+opencv-python==4.8.0.74
+einops==0.6.1
+pytorch-lightning==2.0.2
+omegaconf==2.3.0
+huggingface-hub==0.16.4
+xformers==0.0.20
+triton==2.0.0
+compel==2.0.1