Update app.py

app.py

@@ -1,41 +1,39 @@
 import gradio as gr
 import numpy as np
 import random
-from diffusers import DiffusionPipeline
-import torch
+from diffusers import AutoPipelineForImage2Image
+from diffusers.utils import make_image_grid, load_image
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 if torch.cuda.is_available():
     torch.cuda.max_memory_allocated(device=device)
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+    pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
     pipe.enable_xformers_memory_efficient_attention()
     pipe = pipe.to(device)
 else: 
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
+    pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", use_safetensors=True)
     pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
+pipe.load_lora_weights("artificialguybr/ps1redmond-ps1-game-graphics-lora-for-sdxl")
+
 def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
 
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
         
     generator = torch.Generator().manual_seed(seed)
+
+    url = "https://cmmodels.de/wp-content/uploads/2021/08/gabriel-new-face-white-shirt-brown-hair-pretty-boy-young-white-background-studio-brown-hair-wet-look.jpg"
+    init_image = load_image(url)
     
-    image = pipe(
-        prompt = prompt, 
-        negative_prompt = negative_prompt,
-        guidance_scale = guidance_scale, 
-        num_inference_steps = num_inference_steps, 
-        width = width, 
-        height = height,
-        generator = generator
-    ).images[0] 
+    image = pipeline(prompt, image=init_image, strength=0.5).images[0]
+    grid = make_image_grid([init_image, image], rows=1, cols=2)
     
-    return image
+    return grid
 
 examples = [
     "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",