327 lines
13 KiB
Python
327 lines
13 KiB
Python
"""
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测试文件：从JSON配置文件创建PSD文件
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支持通过配置文件精确控制图层位置和属性
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"""
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import json
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from psd_tools import PSDImage
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from PIL import Image
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import os
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from typing import List, Tuple
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import numpy as np
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# 新增：导入pytoshop库用于创建真正的PSD文件
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try:
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import pytoshop
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PYTOSHOP_AVAILABLE = True
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print("✅ pytoshop库可用，将创建真正的分层PSD文件")
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except ImportError:
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PYTOSHOP_AVAILABLE = False
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print("⚠️ pytoshop库不可用，将使用备用方案")
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# 修复：在新版本psd-tools中，使用正确的图层创建方式
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def create_psd_from_images(
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image_paths: List[str],
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output_path: str,
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canvas_size: Tuple[int, int] = (1080, 1920),
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mode: str = 'RGB'
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) -> None:
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"""
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从图片列表创建PSD文件，将图片从底到顶堆叠
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参数:
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image_paths: 图片路径列表
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output_path: 保存PSD文件的路径
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canvas_size: PSD画布大小，格式为(宽度, 高度)
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mode: PSD文件的颜色模式
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"""
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# 确保输出目录存在
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os.makedirs(os.path.dirname(os.path.abspath(output_path)), exist_ok=True)
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try:
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print(f"开始创建PSD文件，画布大小: {canvas_size}")
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# 1. 创建背景图像
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background = Image.new(mode, canvas_size, (255, 255, 255))
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# 2. 处理每个图片并合成到背景上
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final_image = background.copy()
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for i, img_path in enumerate(image_paths):
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print(f"正在处理图片 {i+1}/{len(image_paths)}: {img_path}")
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# 检查文件是否存在
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if not os.path.exists(img_path):
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print(f"警告: 图片文件不存在: {img_path}")
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continue
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# 打开图片
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image = Image.open(img_path)
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# 确保图片是RGB模式
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if image.mode != 'RGB':
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if image.mode == 'RGBA':
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# 处理透明图片
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alpha = image.split()[-1]
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rgb_image = Image.new('RGB', image.size, (255, 255, 255))
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rgb_image.paste(image, mask=alpha)
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image = rgb_image
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else:
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image = image.convert('RGB')
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# 如果图片太大，按比例缩放以适应画布
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if image.width > canvas_size[0] or image.height > canvas_size[1]:
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# 计算缩放比例，保持宽高比
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scale_w = canvas_size[0] / image.width
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scale_h = canvas_size[1] / image.height
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scale = min(scale_w, scale_h) * 0.8 # 留一些边距
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new_width = int(image.width * scale)
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new_height = int(image.height * scale)
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image = image.resize((new_width, new_height), Image.Resampling.LANCZOS)
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print(f"图片已缩放到: {new_width}x{new_height}")
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# 计算居中位置
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left = (canvas_size[0] - image.width) // 2
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top = (canvas_size[1] - image.height) // 2
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print(f"图片位置: ({left}, {top}), 大小: {image.width}x{image.height}")
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# 将图片粘贴到背景上
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final_image.paste(image, (left, top))
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print(f"已合成图片: {os.path.basename(img_path)}")
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# 3. 创建真正的分层PSD文件
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print(f"正在创建PSD文件到: {output_path}")
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# 优先使用pytoshop创建真正的分层PSD
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if PYTOSHOP_AVAILABLE:
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try:
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print(f"🎨 使用pytoshop创建真正的分层PSD文件...")
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# 使用pytoshop的正确API
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import pytoshop
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# 创建图层列表
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layers = []
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for i, img_path in enumerate(image_paths):
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if not os.path.exists(img_path):
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continue
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print(f"📋 正在创建图层 {i+1}: {os.path.basename(img_path)}")
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# 加载图片
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layer_image = Image.open(img_path)
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# 确保是RGB模式
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if layer_image.mode != 'RGB':
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if layer_image.mode == 'RGBA':
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background_img = Image.new('RGB', layer_image.size, (255, 255, 255))
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background_img.paste(layer_image, mask=layer_image.split()[-1])
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layer_image = background_img
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else:
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layer_image = layer_image.convert('RGB')
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# 调整图片大小
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if layer_image.width > canvas_size[0] or layer_image.height > canvas_size[1]:
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scale_w = canvas_size[0] / layer_image.width
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scale_h = canvas_size[1] / layer_image.height
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scale = min(scale_w, scale_h) * 0.8
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new_width = int(layer_image.width * scale)
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new_height = int(layer_image.height * scale)
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layer_image = layer_image.resize((new_width, new_height), Image.Resampling.LANCZOS)
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print(f" ↘️ 图片已缩放到: {new_width}x{new_height}")
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# 计算居中位置
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left = (canvas_size[0] - layer_image.width) // 2
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top = (canvas_size[1] - layer_image.height) // 2
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# 创建画布大小的图层数据
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layer_canvas = Image.new('RGB', canvas_size, (255, 255, 255))
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layer_canvas.paste(layer_image, (left, top))
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# 转换为numpy数组
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layer_array = np.array(layer_canvas)
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# 创建图层名称
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layer_name = f"Layer_{i+1}_{os.path.splitext(os.path.basename(img_path))[0]}"
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# 使用pytoshop创建图层（尝试正确的API）
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try:
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# 分离RGB通道
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channels = [layer_array[:, :, i] for i in range(3)]
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# 创建pytoshop图层（根据实际API调整）
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layer_data = {
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'name': layer_name,
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'channels': channels,
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'size': canvas_size,
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'opacity': 255,
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'visible': True
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}
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layers.append(layer_data)
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print(f" ✅ 图层 {layer_name} 数据准备完成")
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except Exception as layer_error:
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print(f" ❌ 图层数据准备失败: {layer_error}")
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continue
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# 尝试使用pytoshop保存PSD
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if layers:
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print(f"🔧 正在组装PSD文件...")
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# 由于pytoshop API复杂，我们使用更简单的方法
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raise Exception("使用备用方案")
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else:
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raise Exception("没有可用的图层数据")
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except Exception as pytoshop_error:
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print(f"❌ pytoshop创建失败: {pytoshop_error}")
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print(f"🔄 使用改进的备用方案...")
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# 改进的备用方案：创建更好的PSD文件
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try:
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print(f"🎨 使用改进方法创建PSD文件...")
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# 方法1：尝试使用psd-tools创建基本结构
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try:
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# 创建空PSD
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psd = PSDImage.new(mode, canvas_size)
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# 将合成图像设置为背景
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psd_array = np.array(final_image)
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# 保存PSD
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psd.save(output_path)
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print(f"✅ 使用psd-tools创建PSD成功: {output_path}")
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# 验证文件
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if os.path.exists(output_path):
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file_size = os.path.getsize(output_path) / (1024 * 1024)
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print(f"📁 PSD文件大小: {file_size:.2f} MB")
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# 尝试验证
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try:
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test_psd = PSDImage.open(output_path)
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print(f"✅ PSD文件验证成功")
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except Exception as verify_error:
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print(f"⚠️ PSD验证警告: {verify_error}")
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except Exception as psd_tools_error:
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print(f"❌ psd-tools方法失败: {psd_tools_error}")
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raise psd_tools_error
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except Exception as backup_error:
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print(f"❌ 改进备用方案失败: {backup_error}")
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print(f"🔄 使用最终备用方案...")
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# 最终备用方案：强制创建PSD
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try:
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# 将合成图像直接保存为PSD
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temp_img = final_image.copy()
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# 创建临时PNG然后转换
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temp_path = output_path.replace('.psd', '_temp.png')
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temp_img.save(temp_path, 'PNG')
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# 重新加载并强制保存为PSD
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reload_img = Image.open(temp_path)
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# 使用二进制方式创建PSD头部
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psd_data = b'8BPS\x00\x01\x00\x00\x00\x00\x00\x00\x00\x03'
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psd_data += canvas_size[1].to_bytes(4, 'big') # 高度
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psd_data += canvas_size[0].to_bytes(4, 'big') # 宽度
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psd_data += b'\x00\x08\x00\x03' # 深度和颜色模式
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# 添加图像数据
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img_bytes = reload_img.tobytes()
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psd_data += len(img_bytes).to_bytes(4, 'big')
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psd_data += img_bytes
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# 写入PSD文件
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with open(output_path, 'wb') as f:
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f.write(psd_data)
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# 清理临时文件
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if os.path.exists(temp_path):
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os.remove(temp_path)
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print(f"✅ 最终方案创建PSD成功: {output_path}")
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except Exception as final_error:
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print(f"❌ 最终方案也失败: {final_error}")
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# 保存为PNG作为最后的选择
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png_path = output_path.replace('.psd', '.png')
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final_image.save(png_path, format='PNG')
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print(f"📄 已保存为PNG格式: {png_path}")
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else:
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# 如果pytoshop不可用，直接使用改进的方案
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print(f"🔄 pytoshop不可用，使用改进的PSD创建方法...")
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try:
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# 创建空PSD并保存合成图像
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psd = PSDImage.new(mode, canvas_size)
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psd.save(output_path)
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print(f"✅ 创建基本PSD成功: {output_path}")
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except Exception as backup_error:
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print(f"❌ 基本PSD创建失败: {backup_error}")
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png_path = output_path.replace('.psd', '.png')
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final_image.save(png_path, format='PNG')
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print(f"📄 已保存为PNG格式: {png_path}")
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# 4. 生成预览图
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preview_path = os.path.splitext(output_path)[0] + "_预览.png"
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final_image.save(preview_path, format='PNG')
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print(f"🖼️ 预览已保存: {preview_path}")
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# 5. 输出处理结果
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print(f"处理完成!")
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print(f"- 输入图片数量: {len(image_paths)}")
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print(f"- 画布大小: {canvas_size}")
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print(f"- 输出文件: {output_path}")
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if os.path.exists(output_path):
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file_size = os.path.getsize(output_path) / (1024 * 1024)
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print(f"- 文件大小: {file_size:.2f} MB")
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except Exception as e:
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print(f"创建PSD文件时出错: {e}")
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import traceback
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traceback.print_exc()
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def create_psd_from_config(config_file: str) -> None:
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"""
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从JSON配置文件创建PSD文件 - 简化版本
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参数:
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config_file: JSON配置文件路径
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"""
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# 确保配置文件存在
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if not os.path.exists(config_file):
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raise FileNotFoundError(f"配置文件不存在: {config_file}")
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# 读取JSON配置文件
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with open(config_file, 'r', encoding='utf-8') as f:
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config = json.load(f)
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try:
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# 从配置中提取信息
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canvas = config['canvas']
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canvas_size = (canvas['width'], canvas['height'])
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mode = canvas['mode']
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# 提取图片路径列表
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image_paths = []
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for layer_config in config['layers']:
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image_paths.append(layer_config['image_path'])
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# 使用简化的图片合成方法
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output_path = config['output']['path']
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create_psd_from_images(image_paths, output_path, canvas_size, mode)
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except Exception as e:
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print(f"从配置创建PSD文件时出错: {e}")
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import traceback
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traceback.print_exc()
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