feat: adjust the backgroung; change parameters for inference

app.py

@@ -21,14 +21,14 @@ examples = [
 ]
 
 css = """
-body {
+body::before {
     content: "";
     position: fixed;
     top: 0;
     left: 0;
     width: 100%;
     height: 100%;
-    background: url(''https://fastly.picsum.photos/id/65/1920/1080.jpg?hmac=906OwjpX9_xvs1WWE2FOcXxg_a9e3DufNz8XIomLAS4'') no-repeat center center fixed;
+    background: url("https://fastly.picsum.photos/id/65/1920/1080.jpg?hmac=906OwjpX9_xvs1WWE2FOcXxg_a9e3DufNz8XIomLAS4") no-repeat center center fixed;
     filter: blur(8px);
     z-index: -1;
     min-height: 100vh;

stable_diffusion_inference.py

@@ -12,9 +12,10 @@ from diffusers import StableDiffusionPipeline
 from accelerate import Accelerator
 import gradio as gr
 import spaces
-
 from loguru import logger
 
+from utils import timer
+
 model_path = 'Ngene787/Faice_text2face'
 
 accelerator = Accelerator(mixed_precision="fp16", gradient_accumulation_steps=1)
@@ -59,12 +60,13 @@ def inference(prompt,
     generator = torch.Generator().manual_seed(seed)
 
     logger.info('Generating image ...')
-    image = pipe(
-        prompt=prompt,
-        negative_prompt=negative_prompt,
-        guidance_scale=guidance_scale,
-        eta=0.0,
-        num_inference_steps=num_inference_steps,
-        generator=generator,
-    ).images[0]
+    with timer("inference"):
+        image = pipe(
+            prompt=prompt,
+            negative_prompt=negative_prompt,
+            guidance_scale=guidance_scale,
+            eta=0.0,
+            num_inference_steps=num_inference_steps,
+            generator=generator,
+        ).images[0]
     return image, seed