Update app.py

app.py

@@ -525,8 +525,8 @@ torch.cuda.empty_cache()
 
 def upscaler(
     input_image: Image.Image,
-    prompt: str = "Hyper realistic photography, Natural visual content.",
-    negative_prompt: str = "Distorted, Discontinuous, Blurry, Doll-Like, Overly-Plastic, Low-Quality, Painted, Smoothed, Artificial, Phony, Gaudy, Digital Effects.",
+    prompt: str = "Masterpiece, Best Quality, Hyper-Realistic, Super-Realistic.",
+    negative_prompt: str = "Blurry, Shiny, Smooth, Polished, Low Quality, Worst Quality, Normal Quality, Anime Quality, Movies Quality.",
     seed: int = random.randint(0, MAX_SEED),
     upscale_factor: int = 2,
     controlnet_scale: float = 0.6,
@@ -535,7 +535,7 @@ def upscaler(
     tile_width: int = 112,
     tile_height: int = 144,
     denoise_strength: float = 0.35,
-    num_inference_steps: int = 40,
+    num_inference_steps: int = 30,
     solver: str = "DDIM",
 ) -> Image.Image:
 
@@ -634,15 +634,12 @@ def generate_random_string(length):
 def add_song_cover_text(img,top_title=None,bottom_title=None):
 
     global working
-    global _HEIGHT_
-    global _WIDTH_
     
     if not working:
 
         working = True
 
-        h = _HEIGHT_
-        w = _WIDTH_
+        w, h = img.size
         
         draw = ImageDraw.Draw(img,mode="RGBA")
     
@@ -1319,9 +1316,9 @@ def handle_generation(h,w,d):
                 d = d if d == "" else translate(d)
             d = re.sub(r"([ \t]){1,}", " ", d).lower().strip()
     
-        neg = f"Textual, Text, Distorted, Fake, Discontinuous, Blurry, Doll-Like, Overly Plastic, Low Quality, Paint, Smoothed, Artificial, Phony, Gaudy, Digital Effects."
+        neg = f"Textual, Text, Blurry, Shiny, Smooth, Polished, Low Quality, Worst Quality, Normal Quality, Anime Quality, Movies Quality."
         q = "\""
-        pos = f'HQ Hyper-realistic professional photograph{ d if d == "" else ": " + d }.'
+        pos = f'Masterpiece, Best Quality, Hyper-Realistic, Super-Realistic{ d if d == "" else ", " + d }'
     
         print(f"""
             Positive: {pos}
@@ -1337,7 +1334,7 @@ def handle_generation(h,w,d):
             output_type="pil",
             guidance_scale=img_accu,
             num_images_per_prompt=1,
-            num_inference_steps=50,
+            num_inference_steps=30,
             max_sequence_length=seq,
             generator=torch.Generator(device).manual_seed(random.randint(0, MAX_SEED))
         ).images[0]