294 lines
12 KiB
Python
294 lines
12 KiB
Python
"""
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创建一个可视化工具，显示效果渲染中的各个图层及其叠加效果
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"""
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import os
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import sys
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import numpy as np
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from PIL import Image, ImageDraw, ImageFont
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import matplotlib.pyplot as plt
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from core.svg_parser import SVGParser
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from core.svg_style_converter import SVGStyleConverter
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from core.effects_processor import EffectsProcessor
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from core.text_renderer import TextRenderer
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def visualize_effect_layers(style_name="all-effects-test", text="Effect", output_path="test_output"):
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"""可视化效果图层"""
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# 创建输出目录
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if not os.path.exists(output_path):
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os.makedirs(output_path)
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# 加载SVG样式
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base_dir = os.path.dirname(os.path.abspath(__file__))
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svg_path = os.path.join(base_dir, "SVG", f"{style_name}.svg")
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if not os.path.exists(svg_path):
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print(f"错误: 未找到SVG文件: {svg_path}")
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return None
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# 解析SVG文件
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parser = SVGParser(svg_path)
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svg_data = parser.parse()
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# 使用转换器
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print(f"[测试] 正在解析样式: {style_name}")
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converter = SVGStyleConverter(svg_data)
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converter.style_name = style_name
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# 转换为样式字典
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style = converter.convert_to_json_style()
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# 显示检测到的效果
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effect_keys = [key for key in style.keys() if key in ['shadow', 'inner_shadow', 'glow', 'outline', 'fill']]
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print(f"[测试] 样式中发现的效果:", effect_keys)
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# 设置图像尺寸和安全区域
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width, height = 600, 400
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safe_area = (50, 50, 550, 350) # (x0, y0, x1, y1)
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# 获取字体路径
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font_name = style.get("font", "Knewave-Regular.ttf")
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fonts_dir = os.path.join(base_dir, "fonts")
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font_path = os.path.join(fonts_dir, font_name)
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# 如果字体不存在，使用默认字体
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if not os.path.exists(font_path):
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default_fonts = ["Knewave-Regular.ttf", "Lobster-Regular.ttf", "MaldiniBold.ttf"]
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for default_font in default_fonts:
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default_path = os.path.join(fonts_dir, default_font)
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if os.path.exists(default_path):
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font_path = default_path
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break
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# 创建渲染器
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renderer = TextRenderer(font_path, style.get("size", 72))
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effects_processor = EffectsProcessor()
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# 创建基础图像并确保是RGBA模式
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base_img = renderer.create_base_text_image(text, style, width, height, True, safe_area)
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if base_img.mode != 'RGBA':
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base_img = base_img.convert('RGBA')
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# 保存单独的效果图层
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layers = {}
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steps = []
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# 1. 绘制基础图层 - 完全不透明的白色填充文本
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base_style = {
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'font': style.get('font'),
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'size': style.get('size'),
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'alignment': style.get('alignment'),
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'spacing': style.get('spacing'),
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'leading': style.get('leading'),
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'fill': {'type': 'solid', 'color': '#FFFFFF'},
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'fill_opacity': 1.0
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}
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# 创建带有文本轮廓的透明图像
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base_text_img = renderer.create_base_text_image(text, base_style, width, height, True, safe_area)
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# 确保文本区域是完全不透明的白色填充
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# 从alpha通道创建一个遮罩
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_, _, _, a = base_text_img.split()
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# 创建纯白色背景图像
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solid_white = Image.new('RGB', base_text_img.size, (255, 255, 255))
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# 使用文本的alpha通道作为遮罩，创建实心白色文本
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base_white = Image.new('RGBA', base_text_img.size, (0, 0, 0, 255)) # 黑色背景
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base_white.paste(solid_white, (0, 0), a)
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layers["base"] = base_white
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steps.append(("base", base_white))
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output_path_base = os.path.join(output_path, f"{style_name}_layer_0_base.png")
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base_white.save(output_path_base)
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# 2. 应用描边效果
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if 'outline' in style and style['outline'].get('width', 0) > 0:
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outline_style = style.copy()
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# 只保留描边效果
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for key in ['shadow', 'inner_shadow', 'glow']:
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if key in outline_style:
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del outline_style[key]
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# 将填充改为透明
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if 'fill' in outline_style:
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outline_style['fill'] = {'type': 'solid', 'color': '#FFFFFF00'}
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outline_base = renderer.create_base_text_image(text, outline_style, width, height, True, safe_area)
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if 'gradient' in style.get('outline', {}):
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outline_img = effects_processor._apply_gradient_outline(outline_base, style)
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else:
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outline_img = effects_processor.apply_outline(outline_base, style)
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layers["outline"] = outline_img
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steps.append(("outline", outline_img))
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output_path_outline = os.path.join(output_path, f"{style_name}_layer_1_outline.png")
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outline_img.save(output_path_outline)
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# 3. 应用阴影效果
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if 'shadow' in style:
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shadow_style = {
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'font': style.get('font'),
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'size': style.get('size'),
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'alignment': style.get('alignment'),
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'spacing': style.get('spacing'),
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'leading': style.get('leading'),
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'fill': {'type': 'solid', 'color': '#FFFFFF'},
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'shadow': style['shadow']
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}
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shadow_base = renderer.create_base_text_image(text, shadow_style, width, height, True, safe_area)
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shadow_img = effects_processor.apply_shadow(shadow_base, shadow_style)
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layers["shadow"] = shadow_img
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steps.append(("shadow", shadow_img))
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output_path_shadow = os.path.join(output_path, f"{style_name}_layer_2_shadow.png")
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shadow_img.save(output_path_shadow)
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# 4. 应用渐变填充
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if 'fill' in style and style['fill'].get('type') == 'gradient':
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# 创建渐变填充效果
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fill_style = {
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'font': style.get('font'),
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'size': style.get('size'),
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'alignment': style.get('alignment'),
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'spacing': style.get('spacing'),
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'leading': style.get('leading'),
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'fill': style['fill'].copy(),
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'fill_opacity': style.get('fill_opacity', 1.0)
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}
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# 获取原始文本mask - 确保只有文本区域是可见的
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_, _, _, text_mask = base_text_img.split() # 使用原始文本图像的alpha通道
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# 创建渐变图像
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gradient = effects_processor._create_gradient(
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width,
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height,
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[effects_processor.hex_to_rgba(color)[:3] for color in style['fill'].get('colors', ['#FFFFFF', '#0000FF'])],
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style['fill'].get('angle', 0)
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)
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# 创建一个只包含文本形状的二值蒙版（白色=文本区域，黑色=背景）
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binary_mask = Image.new('1', (width, height), 0) # 初始化全黑二值图像
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binary_mask.paste(1, (0, 0), text_mask) # 在文本区域粘贴白色
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# 使用numpy进行精确的像素级操作
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gradient_array = np.array(gradient)
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mask_array = np.array(binary_mask)
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# 扩展mask数组以匹配渐变数组的形状
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mask_array_3d = np.stack([mask_array] * 3, axis=2)
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# 将渐变应用到文本区域（其他区域保持黑色）
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gradient_masked = gradient_array * mask_array_3d
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# 转换回PIL图像并添加透明通道
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gradient_masked_img = Image.fromarray(gradient_masked.astype(np.uint8))
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gradient_masked_rgba = gradient_masked_img.convert('RGBA')
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# 将透明度通道设置为文本的透明度
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r, g, b, _ = gradient_masked_rgba.split()
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fill_img = Image.merge('RGBA', (r, g, b, text_mask))
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layers["fill"] = fill_img
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steps.append(("fill", fill_img))
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output_path_fill = os.path.join(output_path, f"{style_name}_layer_3_fill.png")
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fill_img.save(output_path_fill)
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# 5. 应用内阴影效果
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if 'inner_shadow' in style:
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inner_shadow_style = {
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'font': style.get('font'),
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'size': style.get('size'),
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'alignment': style.get('alignment'),
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'spacing': style.get('spacing'),
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'leading': style.get('leading'),
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'fill': {'type': 'solid', 'color': '#FFFFFF'},
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'inner_shadow': style['inner_shadow']
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}
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inner_base = renderer.create_base_text_image(text, inner_shadow_style, width, height, True, safe_area)
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inner_img = effects_processor.apply_inner_shadow(inner_base, inner_shadow_style)
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layers["inner_shadow"] = inner_img
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steps.append(("inner_shadow", inner_img))
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output_path_inner = os.path.join(output_path, f"{style_name}_layer_4_inner_shadow.png")
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inner_img.save(output_path_inner)
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# 6. 应用发光效果
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if 'glow' in style:
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glow_style = {
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'font': style.get('font'),
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'size': style.get('size'),
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'alignment': style.get('alignment'),
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'spacing': style.get('spacing'),
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'leading': style.get('leading'),
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'fill': {'type': 'solid', 'color': '#FFFFFF'},
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'glow': style['glow']
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}
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glow_base = renderer.create_base_text_image(text, glow_style, width, height, True, safe_area)
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glow_img = effects_processor.apply_glow(glow_base, glow_style)
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layers["glow"] = glow_img
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steps.append(("glow", glow_img))
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output_path_glow = os.path.join(output_path, f"{style_name}_layer_5_glow.png")
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glow_img.save(output_path_glow)
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# 7. 所有效果组合 - 使用修改后的合成方法
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# 创建一个干净的基础图像作为起点
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# 我们不使用base_white，因为它已经有黑色背景和白色文本
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# 而是使用原始的透明背景文本图像
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base_for_effects = renderer.create_base_text_image(text, style, width, height, True, safe_area)
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# 添加name参数，解决style_name未正确传递的问题
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all_img = effects_processor.apply_all_effects(base_for_effects, style, style_name)
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output_path_all = os.path.join(output_path, f"{style_name}_layer_all.png")
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all_img.save(output_path_all)
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# 也保存一个带黑色背景的版本，便于查看
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bg = Image.new('RGBA', all_img.size, (0, 0, 0, 255)) # 黑色背景
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with_bg = Image.alpha_composite(bg, all_img)
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with_bg.save(os.path.join(output_path, f"{style_name}_layer_all_with_bg.png"))
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# 创建可视化图像
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from matplotlib import pyplot as plt
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# 设置黑色背景
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plt.rcParams['figure.facecolor'] = 'black'
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plt.rcParams['axes.facecolor'] = 'black'
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plt.rcParams['savefig.facecolor'] = 'black'
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plt.figure(figsize=(15, 10))
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plt.suptitle(f"Effects Layers Visualization - {style_name}", fontsize=16, color='white')
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# 创建两行三列的布局
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total_layers = len(layers) + 1 # 所有图层加上一个组合效果
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cols = 3
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rows = (total_layers + cols - 1) // cols
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# 按顺序显示图层
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for i, (name, img) in enumerate(steps):
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plt.subplot(rows, cols, i + 1)
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plt.title(f"Layer: {name}", color='white')
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plt.imshow(np.array(img))
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plt.axis('off')
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# 在最后一个位置添加组合效果
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plt.subplot(rows, cols, len(steps) + 1)
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plt.title("All Effects Combined", color='white')
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plt.imshow(np.array(all_img))
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plt.axis('off')
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# 保存可视化图像
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visualization_path = os.path.join(output_path, f"{style_name}_visualization.png")
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plt.tight_layout()
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plt.savefig(visualization_path, dpi=100)
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plt.close()
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print(f"[测试] 可视化图层已保存到: {output_path}目录")
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return all_img
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if __name__ == "__main__":
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# 从命令行获取样式名称
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if len(sys.argv) > 1:
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style_name = sys.argv[1]
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else:
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style_name = "all-effects-test"
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# 运行可视化
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visualize_effect_layers(style_name)
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