update workflow, compress result img size

app.py

@@ -10,6 +10,7 @@ import subprocess
 
 from huggingface_hub import hf_hub_download
 from huggingface_hub import snapshot_download
+from utils.image_utils import remove_image_metadata, resize_and_optimize_image
 
 #https://huggingface.co/SG161222/Realistic_Vision_V6.0_B1_noVAE/blob/main/Realistic_Vision_V6.0_NV_B1_fp16.safetensors
 print("Realistic_Vision_V6.0_NV_B1_fp16.safetensors")
@@ -699,9 +700,10 @@ def generate_image(model_image, hairstyle_template_image):
 
         # result
         saveimage_680 = saveimage.save_images(
-            filename_prefix="ComfyUI",
+            filename_prefix="hairstyle_filter",
             images=get_value_at_index(layerutility_imageblend_v2_686, 0),
         )
+        remove_image_metadata(f"output/{saveimage_680['ui']['images'][0]['filename']}")
 
         image_comparer_rgthree_820 = image_comparer_rgthree.compare_images(
             image_a=get_value_at_index(layerutility_imageblend_v2_399, 0),
@@ -722,15 +724,21 @@ def generate_image(model_image, hairstyle_template_image):
 
         # result with ultra sharp
         saveimage_847 = saveimage.save_images(
-            filename_prefix="ComfyUI",
+            filename_prefix="hairstyle_filter_result",
             images=get_value_at_index(imageupscalewithmodel_831, 0),
         )
+        # 将4x upscale的图片缩小到2x，并优化压缩（长边从3072降到1536）
+        resize_and_optimize_image(
+            f"output/{saveimage_847['ui']['images'][0]['filename']}", 
+            target_long_edge=1536
+        )
 
         # bald
         saveimage_848 = saveimage.save_images(
-            filename_prefix="ComfyUI",
+            filename_prefix="hairstyle_bald_result",
             images=get_value_at_index(layerutility_imageblend_v2_399, 0),
         )
+        remove_image_metadata(f"output/{saveimage_848['ui']['images'][0]['filename']}")
 
         saved_path_bald = f"output/{saveimage_848['ui']['images'][0]['filename']}"
         saved_path_result = f"output/{saveimage_680['ui']['images'][0]['filename']}"
@@ -887,9 +895,10 @@ def generate_image_bald(model_image):
 
         # bald
         saveimage_848 = saveimage.save_images(
-            filename_prefix="ComfyUI",
+            filename_prefix="hairstyle_bald_result",
             images=get_value_at_index(layerutility_imageblend_v2_399, 0),
         )
+        remove_image_metadata(f"output/{saveimage_848['ui']['images'][0]['filename']}")
 
         saved_path_bald = f"output/{saveimage_848['ui']['images'][0]['filename']}"
         return saved_path_bald

utils/image_utils.py

@@ -0,0 +1,105 @@
+"""
+Image processing utility functions
+"""
+from PIL import Image
+import os
+
+
+def remove_image_metadata(image_path: str) -> None:
+    """
+    Remove metadata information from image file
+    
+    Args:
+        image_path: Path to the image file
+    """
+    if not os.path.exists(image_path):
+        print(f"Warning: Image file does not exist: {image_path}")
+        return
+    
+    try:
+        # Load original image
+        img = Image.open(image_path)
+        
+        # Create new image without metadata
+        # Preserve image mode and size
+        img_without_metadata = Image.new(img.mode, img.size)
+        img_without_metadata.putdata(list(img.getdata()))
+        
+        # Save without any metadata
+        img_without_metadata.save(image_path, format='PNG')
+        
+        print(f"Removed image metadata: {image_path}")
+    except Exception as e:
+        print(f"Failed to remove metadata ({image_path}): {str(e)}")
+
+
+def remove_multiple_images_metadata(image_paths: list) -> None:
+    """
+    Batch remove metadata from multiple image files
+    
+    Args:
+        image_paths: List of image file paths
+    """
+    for path in image_paths:
+        remove_image_metadata(path)
+
+
+def resize_and_optimize_image(image_path: str, target_long_edge: int = 1536) -> None:
+    """
+    Resize image (long edge) and optimize PNG compression, while removing metadata
+    
+    Args:
+        image_path: Path to the image file
+        target_long_edge: Target long edge size, default 1536 (768×2)
+    """
+    if not os.path.exists(image_path):
+        print(f"Warning: Image file does not exist: {image_path}")
+        return
+    
+    try:
+        # Load original image
+        img = Image.open(image_path)
+        original_size = img.size
+        
+        # Calculate scaling ratio
+        width, height = img.size
+        long_edge = max(width, height)
+        
+        # If long edge is already smaller than target, only optimize compression
+        if long_edge <= target_long_edge:
+            print(f"Image size {original_size} is already smaller than target, only optimizing compression: {image_path}")
+            img.save(
+                image_path, 
+                format='PNG',
+                compress_level=9,  # Maximum compression level (0-9)
+                optimize=True      # Enable optimization
+            )
+            return
+        
+        # Calculate new dimensions
+        scale = target_long_edge / long_edge
+        new_width = int(width * scale)
+        new_height = int(height * scale)
+        
+        # Resize using high-quality Lanczos resampling algorithm
+        img_resized = img.resize((new_width, new_height), Image.Resampling.LANCZOS)
+        
+        # Save optimized image (without metadata)
+        img_resized.save(
+            image_path,
+            format='PNG',
+            compress_level=9,  # Maximum compression level
+            optimize=True      # Enable optimization
+        )
+        
+        print(f"Image resized and optimized: {image_path}")
+        print(f"  Original size: {original_size} -> New size: ({new_width}, {new_height})")
+        
+        # Display file size
+        if os.path.exists(image_path):
+            file_size_mb = os.path.getsize(image_path) / (1024 * 1024)
+            print(f"  File size: {file_size_mb:.2f} MB")
+            
+    except Exception as e:
+        print(f"Failed to resize and optimize image ({image_path}): {str(e)}")
+