Update app.py

app.py

@@ -4,20 +4,14 @@ import torch
 from PIL import Image
 from transformers import AutoProcessor, AutoModelForCausalLM
 
-# import os
-# import random
-# from gradio_client import Client
-
-
-subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
+# subprocess to install flash-attn if necessary (commented for now)
+# subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
 
 # Initialize Florence model
 device = "cuda" if torch.cuda.is_available() else "cpu"
 florence_model = AutoModelForCausalLM.from_pretrained('microsoft/Florence-2-base', trust_remote_code=True).to(device).eval()
 florence_processor = AutoProcessor.from_pretrained('microsoft/Florence-2-base', trust_remote_code=True)
 
-# api_key = os.getenv("HF_READ_TOKEN")
-
 def generate_caption(image):
     if not isinstance(image, Image.Image):
         image = Image.fromarray(image)
@@ -37,32 +31,22 @@ def generate_caption(image):
         task="<MORE_DETAILED_CAPTION>",
         image_size=(image.width, image.height)
     )
-    prompt =  parsed_answer["<MORE_DETAILED_CAPTION>"]
-    print("\n\nGeneration completed!:"+ prompt)
+    prompt = parsed_answer["<MORE_DETAILED_CAPTION>"]
     return prompt
-    # yield prompt, None
-    # image_path = generate_image(prompt,random.randint(0, 4294967296))
-    # yield prompt, image_path 
 
-# def generate_image(prompt, seed=42, width=1024, height=1024):
-#     try:
-#         result = Client("KingNish/Realtime-FLUX", hf_token=api_key).predict(
-#             prompt=prompt,
-#             seed=seed,
-#             width=width,
-#             height=height,
-#             api_name="/generate_image"
-#         )
-#         # Extract the image path from the result tuple
-#         image_path = result[0]
-#         return image_path 
-#     except Exception as e:
-#         raise Exception(f"Error generating image: {str(e)}")
- 
-io = gr.Interface(generate_caption,
-                  inputs=[gr.Image(label="Input Image")],
-                  outputs = [gr.Textbox(label="Output Prompt", lines=2, show_copy_button = True),
-                             # gr.Image(label="Output Image")
-                            ]
-                 )
+# Custom CSS for pink background and title styling
+css = """
+body {background-color: #FFC0CB;}
+h1 {color: #800080; text-align: center; font-size: 32px; font-family: 'Comic Sans MS', cursive, sans-serif;}
+"""
+
+# Interface with pink background and a welcome message
+io = gr.Interface(
+    fn=generate_caption,
+    inputs=[gr.Image(label="Input Image")],
+    outputs=[gr.Textbox(label="Output Prompt", lines=2, show_copy_button=True)],
+    title="歡迎來到我的魔法世界✨",
+    css=css
+)
+
 io.launch(debug=True)