Files
comfyui_o1key/nodes/save_psd.py
T
o1keyandClaude Opus 4.7 3f0f4099fb feat: 新增去背景/PSD分层导出节点,优化聊天面板与重启逻辑
- 新增 O1keyRemoveBackground 节点(基于 rembg CPU 推理)
- 新增 O1keyColorRemoveBG 节点(颜色距离去背景,支持多模式)
- 新增 O1keySavePSD 节点(手写 PSD 二进制,零外部依赖)
- GPT Image 批量输出不同尺寸时自动 resize 对齐
- 聊天面板大幅增强(多模态/交互优化)
- 重启按钮绕过 beforeunload 弹窗强制刷新
- 默认路由切换为 CF加速
- http_error 新增 system error 友好文案

Co-Authored-By: Claude Opus 4.7 <[email protected]>
2026-05-26 18:05:07 +08:00

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"""
o1key SavePSD 节点
将多个 IMAGE 图层合成为分层 PSD 文件
手写 PSD 二进制格式,零外部依赖(仅 numpy + Pillow)
"""
import os
import struct
import time
import numpy as np
import torch
from PIL import Image
import folder_paths
def _pad_even(data: bytes) -> bytes:
if len(data) % 2:
return data + b"\x00"
return data
def _pad4(data: bytes) -> bytes:
return data + (b"\x00" * ((4 - (len(data) % 4)) % 4))
def _pascal_name(name: str) -> bytes:
raw = name.encode("macroman", errors="replace")[:255]
data = bytes([len(raw)]) + raw
return _pad4(data)
def _unicode_name_block(name: str) -> bytes:
payload = struct.pack(">I", len(name)) + name.encode("utf-16be")
block = b"8BIM" + b"luni" + struct.pack(">I", len(payload)) + _pad_even(payload)
return block
def _layer_extra_data(name: str) -> bytes:
data = b""
data += struct.pack(">I", 0) # layer mask data length
data += struct.pack(">I", 0) # layer blending ranges length
data += _pascal_name(name)
data += _unicode_name_block(name)
return data
def _alpha_bbox(rgba_arr: np.ndarray):
"""找到 RGBA 数组中非透明区域的 bounding box。"""
alpha = rgba_arr[:, :, 3]
rows = np.any(alpha > 0, axis=1)
cols = np.any(alpha > 0, axis=0)
if not rows.any():
return None
top = int(np.argmax(rows))
bottom = int(len(rows) - np.argmax(rows[::-1]))
left = int(np.argmax(cols))
right = int(len(cols) - np.argmax(cols[::-1]))
return top, left, bottom, right
def write_psd(filepath: str, layers: list, canvas_w: int, canvas_h: int):
"""
写入 PSD 文件。
layers: [(name, rgba_array), ...] 从底到顶排列
rgba_array: numpy uint8 [H, W, 4]
"""
records = []
channel_data_blocks = []
layers_top_to_bottom = list(reversed(layers))
for name, rgba in layers_top_to_bottom:
bbox = _alpha_bbox(rgba)
if not bbox:
continue
top, left, bottom, right = bbox
cropped = rgba[top:bottom, left:right]
# PLACEHOLDER_CHANNELS
channels = [
(0, cropped[:, :, 0].tobytes(order="C")),
(1, cropped[:, :, 1].tobytes(order="C")),
(2, cropped[:, :, 2].tobytes(order="C")),
(-1, cropped[:, :, 3].tobytes(order="C")),
]
channel_info = b""
data_block = b""
for channel_id, data in channels:
channel_info += struct.pack(">hI", channel_id, 2 + len(data))
data_block += struct.pack(">H", 0) + data # raw compression
extra = _layer_extra_data(name)
record = b""
record += struct.pack(">iiii", top, left, bottom, right)
record += struct.pack(">H", len(channels))
record += channel_info
record += b"8BIM" + b"norm"
record += bytes([255, 0, 0, 0]) # opacity=255, clipping, flags, filler
record += struct.pack(">I", len(extra)) + extra
records.append(record)
channel_data_blocks.append(data_block)
if not records:
raise ValueError("所有图层均为空(完全透明),无法生成 PSD")
# Layer and Mask Information
layer_info = struct.pack(">h", len(records))
layer_info += b"".join(records) + b"".join(channel_data_blocks)
layer_info = _pad_even(layer_info)
layer_info_block = struct.pack(">I", len(layer_info)) + layer_info
global_mask = struct.pack(">I", 0)
layer_mask_payload = layer_info_block + global_mask
layer_and_mask = struct.pack(">I", len(layer_mask_payload)) + layer_mask_payload
# PLACEHOLDER_COMPOSITE
# Composite preview (flattened image for compatibility)
comp = Image.new("RGBA", (canvas_w, canvas_h), (255, 255, 255, 255))
for name, rgba in layers:
layer_img = Image.fromarray(rgba, "RGBA")
comp.alpha_composite(layer_img)
comp_rgb = np.asarray(comp.convert("RGB"), dtype=np.uint8)
composite_data = (
struct.pack(">H", 0)
+ comp_rgb[:, :, 0].tobytes(order="C")
+ comp_rgb[:, :, 1].tobytes(order="C")
+ comp_rgb[:, :, 2].tobytes(order="C")
)
# Write PSD file
with open(filepath, "wb") as f:
# Header
f.write(b"8BPS")
f.write(struct.pack(">H", 1)) # version
f.write(b"\x00" * 6) # reserved
f.write(struct.pack(">HIIHH", 3, canvas_h, canvas_w, 8, 3))
# Color Mode Data
f.write(struct.pack(">I", 0))
# Image Resources
f.write(struct.pack(">I", 0))
# Layer and Mask
f.write(layer_and_mask)
# Composite Image Data
f.write(composite_data)
# PLACEHOLDER_NODE
class O1keySavePSD:
"""
将多个 IMAGE 输入合成为分层 PSD 文件
每个输入作为独立图层,支持 RGBA 透明通道。
图层从下到上排列(图层1在最底部)。
使用 bbox 裁剪优化文件大小,包含合成预览层。
"""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"批次图像": ("IMAGE", {
"tooltip": "批次图像输入,每张图自动作为独立图层(支持RGBA透明)",
}),
},
"optional": {
"图层名称": ("STRING", {
"default": "",
"multiline": True,
"tooltip": "每行一个图层名称,与图层顺序对应。留空则自动命名。",
}),
"文件名前缀": ("STRING", {
"default": "o1key_layers",
"tooltip": "输出 PSD 文件名前缀",
}),
},
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("文件路径",)
FUNCTION = "save_psd"
CATEGORY = "o1key/image"
OUTPUT_NODE = True
def save_psd(self, 批次图像, 图层名称: str = "", 文件名前缀: str = "o1key_layers", **kwargs):
# 将批次 tensor [B, H, W, C] 拆为单张列表
if 批次图像.dim() == 3:
layer_tensors = [批次图像]
else:
layer_tensors = [批次图像[i] for i in range(批次图像.shape[0])]
names = [n.strip() for n in 图层名称.split("\n") if n.strip()]
# 确定画布尺寸
max_h, max_w = 0, 0
for t in layer_tensors:
h, w = t.shape[0], t.shape[1]
max_h = max(max_h, h)
max_w = max(max_w, w)
# 转换为 [(name, rgba_array), ...] 格式
layers = []
for idx, tensor in enumerate(layer_tensors):
arr = (tensor.cpu().numpy() * 255).clip(0, 255).astype(np.uint8)
h, w = arr.shape[0], arr.shape[1]
channels = arr.shape[2] if arr.ndim == 3 else 1
if channels == 3:
rgba = np.zeros((max_h, max_w, 4), dtype=np.uint8)
rgba[:h, :w, :3] = arr
rgba[:h, :w, 3] = 255
elif channels == 4:
rgba = np.zeros((max_h, max_w, 4), dtype=np.uint8)
rgba[:h, :w] = arr
else:
rgba = np.zeros((max_h, max_w, 4), dtype=np.uint8)
rgba[:h, :w, 0] = rgba[:h, :w, 1] = rgba[:h, :w, 2] = arr[:, :, 0] if arr.ndim == 3 else arr
rgba[:h, :w, 3] = 255
name = names[idx] if idx < len(names) else f"图层 {idx + 1}"
layers.append((name, rgba))
print(f"[o1key SavePSD] 图层 '{name}': {w}×{h}")
# 写入 PSD
output_dir = folder_paths.get_output_directory()
timestamp = time.strftime("%Y%m%d_%H%M%S")
filename = f"{文件名前缀}_{timestamp}.psd"
filepath = os.path.join(output_dir, filename)
write_psd(filepath, layers, max_w, max_h)
size_kb = os.path.getsize(filepath) / 1024
print(f"[o1key SavePSD] 完成: {filepath} ({size_kb:.0f}KB, "
f"{len(layers)} 层, {max_w}×{max_h})")
return (filepath,)