nodes/MeeeyoAI-ComfyUI_StringOps
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MeeeyoAI
2025-04-21 16:27:17 +08:00
parent d55d70252d
commit 3a6601aedd
7 changed files with 291 additions and 127 deletions
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meyo_node_File.py
+153 -59
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@@ -21,8 +21,10 @@ class LoadAndAdjustImage:
return {
"required": {
"image": (sorted(files), {"image_upload": True}),
"max_dimension": ("INT", {"default": 1024, "min": 0, "max": 4096, "step": 8}),
"size_option": (["Custom", "Small", "Medium", "Large"], {"default": "Custom"})
"max_dimension": ("INT", {"default": 0, "min": 0, "max": 4096, "step": 8}),
"size_option": (["No Change", "Custom", "Million Pixels", "Small", "Medium", "Large",
"480P-H(vid 4:3)", "480P-V(vid 3:4)", "720P-H(vid 16:9)", "720P-V(vid 9:16)", "832×480", "480×832"],
{"default": "No Change"})
}
}
@@ -30,6 +32,7 @@ class LoadAndAdjustImage:
RETURN_NAMES = ("image", "mask", "info")
FUNCTION = "load_image"
CATEGORY = "Meeeyo/File"
DESCRIPTION = "如需更多帮助或商务需求(For tech and business support)+VX/WeChat: meeeyo"
def IS_CHANGED():
return float("NaN")
@@ -41,7 +44,12 @@ class LoadAndAdjustImage:
aspect_ratio = W / H
def get_target_size():
if size_option == "Custom":
if size_option == "No Change":
# No resizing or cropping, just return the original size
return W, H
elif size_option == "Million Pixels":
return self._resize_to_million_pixels(W, H)
elif size_option == "Custom":
ratio = min(max_dimension / W, max_dimension / H)
return round(W * ratio), round(H * ratio)
@@ -60,9 +68,17 @@ class LoadAndAdjustImage:
(1600, 1120) if aspect_ratio >= 1.23 else
(1120, 1600) if aspect_ratio <= 0.82 else
(1600, 1600)
)
),
"Million Pixels": self._resize_to_million_pixels(W, H), # Million Pixels option
"480P-H(vid 4:3)": (640, 480), # 480P-H, 640x480
"480P-V(vid 3:4)": (480, 640), # 480P-V, 480x640
"720P-H(vid 16:9)": (1280, 720), # 720P-H, 1280x720
"720P-V(vid 9:16)": (720, 1280), # 720P-V, 720x1280
"832×480": (832, 480), # 832x480
"480×832": (480, 832), # 480x832
}
return size_options[size_option]
target_width, target_height = get_target_size()
output_images = []
output_masks = []
@@ -73,50 +89,83 @@ class LoadAndAdjustImage:
frame = frame.convert("RGBA")
elif 'A' in frame.getbands():
frame = frame.convert("RGBA")
if size_option == "Custom":
ratio = min(target_width / W, target_height / H)
adjusted_width = round(W * ratio)
adjusted_height = round(H * ratio)
image_frame = frame.convert("RGB").resize((adjusted_width, adjusted_height), Image.Resampling.BILINEAR)
else:
if size_option == "No Change":
# No resizing, just use the original frame
image_frame = frame.convert("RGB")
image_frame = ImageOps.fit(image_frame, (target_width, target_height), method=Image.Resampling.BILINEAR, centering=(0.5, 0.5))
else:
if size_option == "Custom" or size_option == "Million Pixels":
ratio = min(target_width / W, target_height / H)
adjusted_width = round(W * ratio)
adjusted_height = round(H * ratio)
image_frame = frame.convert("RGB").resize((adjusted_width, adjusted_height), Image.Resampling.BILINEAR)
else:
image_frame = frame.convert("RGB")
image_frame = ImageOps.fit(image_frame, (target_width, target_height), method=Image.Resampling.BILINEAR, centering=(0.5, 0.5))
image_array = np.array(image_frame).astype(np.float32) / 255.0
output_images.append(torch.from_numpy(image_array)[None,])
# Process the mask if available
if 'A' in frame.getbands():
mask_frame = frame.getchannel('A')
if size_option == "Custom":
if size_option == "Custom" or size_option == "Million Pixels":
mask_frame = mask_frame.resize((adjusted_width, adjusted_height), Image.Resampling.BILINEAR)
else:
mask_frame = ImageOps.fit(mask_frame, (target_width, target_height), method=Image.Resampling.BILINEAR, centering=(0.5, 0.5))
mask = np.array(mask_frame).astype(np.float32) / 255.0
mask = 1. - mask
else:
if size_option == "Custom":
if size_option == "Custom" or size_option == "Million Pixels":
mask = np.zeros((adjusted_height, adjusted_width), dtype=np.float32)
else:
mask = np.zeros((target_height, target_width), dtype=np.float32)
output_masks.append(torch.from_numpy(mask).unsqueeze(0))
output_image = torch.cat(output_images, dim=0) if len(output_images) > 1 else output_images[0]
output_mask = torch.cat(output_masks, dim=0) if len(output_masks) > 1 else output_masks[0]
info = f"Image Path: {image_path}\nOriginal Size: {W}x{H}\nAdjusted Size: {target_width}x{target_height}"
return (output_image, output_mask, info)
@classmethod
def VALIDATE_INPUTS(s, image):
if not folder_paths.exists_annotated_filepath(image):
return f"Invalid image file: {image}"
return True
def _resize_to_million_pixels(self, W, H):
# Calculate the aspect ratio of the original image
aspect_ratio = W / H
target_area = 1000000 # 1 million pixels
# Calculate the new width and height while maintaining the aspect ratio
if aspect_ratio > 1: # Landscape
width = int(np.sqrt(target_area * aspect_ratio))
height = int(target_area / width)
else: # Portrait
height = int(np.sqrt(target_area / aspect_ratio))
width = int(target_area / height)
#======重置图像尺寸
# Round width and height to the nearest multiple of 8
width = (width + 7) // 8 * 8
height = (height + 7) // 8 * 8
return width, height
#======重置图像
class ImageAdjuster:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"image": ("IMAGE",),
"max_dimension": ("INT", {"default": 1024, "min": 0, "max": 4096, "step": 8}),
"size_option": (["Custom", "Small", "Medium", "Large"], {"default": "Custom"}),
"max_dimension": ("INT", {"default": 0, "min": 0, "max": 4096, "step": 8}),
"size_option": ([
"Custom", "Million Pixels", "Small", "Medium", "Large",
"480P-H(vid 4:3)", "480P-V(vid 3:4)", "720P-H(vid 16:9)", "720P-V(vid 9:16)", "832×480", "480×832"],
{"default": "Million Pixels"})
}
}
@@ -124,6 +173,7 @@ class ImageAdjuster:
RETURN_NAMES = ("image", "width", "height")
FUNCTION = "process_image"
CATEGORY = "Meeeyo/File"
DESCRIPTION = "如需更多帮助或商务需求(For tech and business support)+VX/WeChat: meeeyo"
def IS_CHANGED():
return float("NaN")
@@ -160,7 +210,14 @@ class ImageAdjuster:
(1600, 1120) if aspect_ratio >= 1.23 else
(1120, 1600) if aspect_ratio <= 0.82 else
(1600, 1600)
)
),
"Million Pixels": self._resize_to_million_pixels(W, H), # Million Pixels option
"480P-H(vid 4:3)": (640, 480), # 480P-H, 640x480
"480P-V(vid 3:4)": (480, 640), # 480P-V, 480x640
"720P-H(vid 16:9)": (1280, 720), # 720P-H, 1280x720
"720P-V(vid 9:16)": (720, 1280), # 720P-V, 720x1280
"832×480": (832, 480), # 832x480
"480×832": (480, 832), # 480x832
}
target_width, target_height = size_options[size_option]
@@ -184,6 +241,73 @@ class ImageAdjuster:
else:
return (output_image, adjusted_width, adjusted_height)
def _resize_to_million_pixels(self, W, H):
# Calculate the aspect ratio of the original image
aspect_ratio = W / H
target_area = 1000000 # 1 million pixels
# Calculate the new width and height while maintaining the aspect ratio
if aspect_ratio > 1: # Landscape
width = int(np.sqrt(target_area * aspect_ratio))
height = int(target_area / width)
else: # Portrait
height = int(np.sqrt(target_area / aspect_ratio))
width = int(target_area / height)
# Round width and height to the nearest multiple of 8
width = (width + 7) // 8 * 8
height = (height + 7) // 8 * 8
return width, height
#======裁剪图像
class CustomCrop:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"image": ("IMAGE",),
"width": ("INT", {"default": 768, "min": 0, "max": 4096, "step": 8}),
"height": ("INT", {"default": 768, "min": 0, "max": 4096, "step": 8}),
}
}
RETURN_TYPES = ("IMAGE", "INT", "INT")
RETURN_NAMES = ("image", "width", "height")
FUNCTION = "process_image"
CATEGORY = "Meeeyo/File"
DESCRIPTION = "如需更多帮助或商务需求(For tech and business support)+VX/WeChat: meeeyo"
def IS_CHANGED(self):
return float("NaN")
def process_image(self, image, width=768, height=768):
input_image = Image.fromarray((image.squeeze(0).numpy() * 255).astype(np.uint8))
W, H = input_image.size
processed_images = []
for frame in [input_image]:
frame = ImageOps.exif_transpose(frame)
if frame.mode == 'P':
frame = frame.convert("RGBA")
elif 'A' in frame.getbands():
frame = frame.convert("RGBA")
processed_image = frame.convert("RGB")
processed_image = ImageOps.fit(processed_image, (width, height), method=Image.Resampling.BILINEAR, centering=(0.5, 0.5))
processed_image = np.array(processed_image).astype(np.float32) / 255.0
processed_image = torch.from_numpy(processed_image)[None,]
processed_images.append(processed_image)
output_image = torch.cat(processed_images, dim=0) if len(processed_images) > 1 else processed_images[0]
return (output_image, width, height)
#======保存图像
class SaveImagEX:
@@ -206,6 +330,7 @@ class SaveImagEX:
FUNCTION = "save_image"
OUTPUT_NODE = True
CATEGORY = "Meeeyo/File"
DESCRIPTION = "如需更多帮助或商务需求(For tech and business support)+VX/WeChat: meeeyo"
def IS_CHANGED():
return float("NaN")
@@ -274,6 +399,7 @@ class FileCopyCutNode:
RETURN_NAMES = ("result",)
FUNCTION = "copy_cut_file"
CATEGORY = "Meeeyo/File"
DESCRIPTION = "如需更多帮助或商务需求(For tech and business support)+VX/WeChat: meeeyo"
def IS_CHANGED():
return float("NaN")
@@ -301,43 +427,6 @@ class FileCopyCutNode:
return (result,)
#======读取页面
class ReadWebNode:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"url": ("STRING", {"default": "https://", "multiline": False}),
},
"optional": {
"any": ("*",), # 可选触发输入
},
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("output",)
FUNCTION = "read_web"
CATEGORY = "Meeeyo/File"
def IS_CHANGED():
return float("NaN")
def read_web(self, url, any=None):
try:
response = requests.get(url)
encoding = chardet.detect(response.content)['encoding']
response.encoding = encoding or 'ISO-8859-1'
if response.status_code == 200:
return (response.text,)
else:
return (f"Failed to retrieve webpage. Status code: {response.status_code}",)
except Exception as e:
return (f"Error: {str(e)}",)
#======文件路径和后缀统计
class FileListAndSuffix:
def __init__(self):
@@ -356,7 +445,8 @@ class FileListAndSuffix:
RETURN_TYPES = ("STRING", "INT", "LIST")
FUNCTION = "file_list_and_suffix"
CATEGORY = "Meeeyo/File"
DESCRIPTION = "如需更多帮助或商务需求(For tech and business support)+VX/WeChat: meeeyo"
def IS_CHANGED():
return float("NaN")
@@ -396,7 +486,8 @@ class ReadExcelData:
RETURN_TYPES = ("STRING",)
FUNCTION = "read_excel_data"
CATEGORY = "Meeeyo/File"
DESCRIPTION = "如需更多帮助或商务需求(For tech and business support)+VX/WeChat: meeeyo"
def IS_CHANGED():
return float("NaN")
@@ -455,7 +546,8 @@ class WriteExcelData:
RETURN_TYPES = ("STRING",)
FUNCTION = "write_excel_data"
CATEGORY = "Meeeyo/File"
DESCRIPTION = "如需更多帮助或商务需求(For tech and business support)+VX/WeChat: meeeyo"
def IS_CHANGED():
return float("NaN")
@@ -530,7 +622,8 @@ class FindExcelData:
RETURN_TYPES = ("STRING", "INT", "INT")
FUNCTION = "find_excel_data"
CATEGORY = "Meeeyo/File"
DESCRIPTION = "如需更多帮助或商务需求(For tech and business support)+VX/WeChat: meeeyo"
def IS_CHANGED():
return float("NaN")
@@ -591,7 +684,8 @@ class ReadExcelRowOrColumnDiff:
RETURN_TYPES = ("INT",)
FUNCTION = "read_excel_row_or_column_diff"
CATEGORY = "Meeeyo/File"
DESCRIPTION = "如需更多帮助或商务需求(For tech and business support)+VX/WeChat: meeeyo"
def IS_CHANGED():
return float("NaN")