update app

app.py

@@ -1,6 +1,7 @@
 import os
 import gradio as gr
 import numpy as np
+import spaces
 import torch
 import random
 from PIL import Image
@@ -8,18 +9,6 @@ from typing import Iterable
 from gradio.themes import Soft
 from gradio.themes.utils import colors, fonts, sizes
 
-# --- Handle optional 'spaces' import for local compatibility ---
-try:
-    import spaces
-except ImportError:
-    class spaces:
-        @staticmethod
-        def GPU(duration=60):
-            def decorator(func):
-                return func
-            return decorator
-
-# --- Custom Theme Setup ---
 colors.steel_blue = colors.Color(
     name="steel_blue",
     c50="#EBF3F8",
@@ -88,17 +77,14 @@ class SteelBlueTheme(Soft):
 
 steel_blue_theme = SteelBlueTheme()
 
-# --- Hardware Setup ---
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 dtype = torch.bfloat16
 
-# --- Imports for Custom Pipeline ---
 from diffusers import FlowMatchEulerDiscreteScheduler
 from qwenimage.pipeline_qwenimage_edit_plus import QwenImageEditPlusPipeline
 from qwenimage.transformer_qwenimage import QwenImageTransformer2DModel
 from qwenimage.qwen_fa3_processor import QwenDoubleStreamAttnProcessorFA3
 
-# --- Model Initialization ---
 print("Loading Qwen Image Edit Pipeline...")
 pipe = QwenImageEditPlusPipeline.from_pretrained(
     "Qwen/Qwen-Image-Edit-2509",
@@ -111,32 +97,26 @@ pipe = QwenImageEditPlusPipeline.from_pretrained(
     torch_dtype=dtype
 ).to(device)
 
-# 1. Load and Fuse Lightning (for speed)
 print("Loading and Fusing Lightning LoRA...")
 pipe.load_lora_weights("lightx2v/Qwen-Image-Lightning",
                        weight_name="Qwen-Image-Lightning-4steps-V2.0-bf16.safetensors",
                        adapter_name="lightning")
 pipe.fuse_lora(adapter_names=["lightning"], lora_scale=1.0)
 
-# 2. Load Task Specific LoRAs
 print("Loading Task Adapters...")
 
-# Texture
 pipe.load_lora_weights("tarn59/apply_texture_qwen_image_edit_2509", 
                        weight_name="apply_texture_v2_qwen_image_edit_2509.safetensors", 
                        adapter_name="texture")
 
-# Fusion (Fuse-Objects)
 pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Fusion", 
                        weight_name="溶图.safetensors", 
                        adapter_name="fusion")
 
-# Face Swap
 pipe.load_lora_weights("Alissonerdx/BFS-Best-Face-Swap", 
                        weight_name="bfs_head_v3_qwen_image_edit_2509.safetensors", 
                        adapter_name="faceswap")
 
-# Attempt Flash Attention 3
 try:
     pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
     print("Flash Attention 3 Processor set successfully.")
@@ -166,7 +146,7 @@ def update_dimensions_on_upload(image):
     
     return new_width, new_height
 
-@spaces.GPU(duration=60)
+@spaces.GPU(duration=30)
 def infer(
     image_1,
     image_2,
@@ -182,7 +162,6 @@ def infer(
         raise gr.Error("Please upload both images for Fusion/Texture/FaceSwap tasks.")
     
     if not prompt:
-        # Add default prompts based on mode if user leaves empty (optional helper)
         if lora_adapter == "Face-Swap":
             prompt = "Swap the face."
         elif lora_adapter == "Texture Edit":
@@ -190,8 +169,6 @@ def infer(
         elif lora_adapter == "Fuse-Objects":
             prompt = "Fuse object into background."
 
-    # Switch Adapters
-    # Note: Lightning is already fused, so we just enable the style adapter
     adapters_map = {
         "Texture Edit": "texture",
         "Fuse-Objects": "fusion",
@@ -211,15 +188,13 @@ def infer(
     generator = torch.Generator(device=device).manual_seed(seed)
     negative_prompt = "worst quality, low quality, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, jpeg artifacts, signature, watermark, username, blurry"
 
-    # Prepare Images
     img1_pil = image_1.convert("RGB")
     img2_pil = image_2.convert("RGB")
     
-    # Calculate dimensions based on the primary image (Image 1)
     width, height = update_dimensions_on_upload(img1_pil)
 
     result = pipe(
-        image=[img1_pil, img2_pil], # Pass both images
+        image=[img1_pil, img2_pil],
         prompt=prompt,
         negative_prompt=negative_prompt,
         height=height,
@@ -231,9 +206,8 @@ def infer(
 
     return result, seed
 
-@spaces.GPU(duration=60)
+@spaces.GPU(duration=30)
 def infer_example(image_1, image_2, prompt, lora_adapter):
-    # Wrapper for examples that sets defaults
     if image_1 is None or image_2 is None:
         return None, 0
     result, seed = infer(
@@ -241,10 +215,10 @@ def infer_example(image_1, image_2, prompt, lora_adapter):
         image_2.convert("RGB"), 
         prompt, 
         lora_adapter, 
-        0, # seed
-        True, # randomize
-        1.0, # guidance
-        4 # steps (Lightning optimized)
+        0,
+        True,
+        1.0,
+        4
     )
     return result, seed
 
@@ -261,7 +235,7 @@ with gr.Blocks(css=css, theme=steel_blue_theme) as demo:
         gr.Markdown("# **Qwen-Image-Edit-2509-LoRAs-Fast-Fusion**", elem_id="main-title")
         gr.Markdown("Perform diverse image edits using specialized [LoRA](https://huggingface.co/models?other=base_model:adapter:Qwen/Qwen-Image-Edit-2509) adapters for the [Qwen-Image-Edit](https://huggingface.co/Qwen/Qwen-Image-Edit-2509) model.")
         with gr.Row(equal_height=True):
-            # Left Column: Inputs
+            
             with gr.Column(scale=1):
                 with gr.Row():
                     image_1 = gr.Image(label="Base / Background / Body", type="pil", height=290)
@@ -301,7 +275,7 @@ with gr.Blocks(css=css, theme=steel_blue_theme) as demo:
             outputs=[output_image, seed],
             fn=infer_example,
             cache_examples=False,
-            label="Examples (Ensure files exist in 'examples/' folder)"
+            label="Examples"
         )
 
     run_button.click(