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- server.js: face_maps 改为白名单 5 图层完整 dataURL 透传(REPORT_MAPS,按魔数判 mime),marks 坐标随 result 原样透传;实测 return_marks 不支持毛孔/黑头等扩展标记 - skin-score.js: 按需求文档 V2.2 逐字审计修正 9 处(黑眼圈 dark_circle_severity、oil_desc/spot_flag §7.2 拼接、skintone 中文映射、轮廓预警档前缀、痘痘 heavy_note、50+精华全文、综合文案数值格式),契约引用 V2.0→V2.2 - app.js/index.html/css: 报告页 6 分类检测可视化(轮廓=正脸实拍、皱纹=正脸压暗+皱纹增强线、光滑=正脸+色斑/痣/痤疮标记、肤色=色沉图、敏感=红区图、痘痘=正脸+闭口/痤疮标记),数据驱动 VIZ_CAT 配置,优雅降级 - h5/test/: Excel 两组三视图真值回归 84/84(含案例2 AY 列扁平化数据重建 fixture) - h5/assets/mock/: 真实案例1 报告页 fixture(坐标与照片同比例缩放),?mock=1&screen=report 直渲 - e2e: Chrome 无头闭环 55/55(mock 全流程/直渲/真实 API 降级链路),截图存档 preview/e2e-20260926 - 自测: skin-score 83/83,fixture 冒烟 35/35
105 lines
4.5 KiB
Python
105 lines
4.5 KiB
Python
#!/usr/bin/env python3
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# ─── 报告页可视化调试 fixture 生成器(仅本目录工具,需 Pillow) ───
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# 数据来源:reference/facepp-skinanalyze/examples/ref_3view_raw.json(案例1 完整原始返回)
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# + reference/facepp-skinanalyze/examples/images/C3_180.jpg(案例1 正脸 4000×3000)
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# 产物:report-fixture.js → window.MOCK_FIXTURE = { result, face_rectangle, side, photos:[正脸dataURL,null,null] }
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# 生产不变量:照片与 face_maps 统一缩到宽 1280,marks 坐标同比例缩放(坐标空间 = 照片空间)
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# 用法:python3 build-fixture.py
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import base64
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import io
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import json
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import os
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from PIL import Image
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ROOT = os.path.dirname(os.path.abspath(__file__))
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REF = os.path.join(ROOT, '..', '..', '..', 'reference', 'facepp-skinanalyze', 'examples')
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TARGET_W = 1280
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# 与服务端 REPORT_MAPS 白名单一致(h5/server.js)
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MAP_KEYS = ['red_area', 'brown_area', 'texture_enhanced_lines', 'texture_enhanced_pores', 'texture_enhanced_blackheads']
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def to_data_url(img, fmt):
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buf = io.BytesIO()
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if fmt == 'JPEG':
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img.convert('RGB').save(buf, 'JPEG', quality=85)
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mime = 'image/jpeg'
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else:
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img.save(buf, 'PNG', optimize=True)
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mime = 'image/png'
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return 'data:%s;base64,%s' % (mime, base64.b64encode(buf.getvalue()).decode('ascii'))
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def scale_coords(node, s):
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"""递归缩放 result 内全部坐标:{left,top,width,height} 矩形与 {x,y} 点,与原数据同为整数。"""
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if isinstance(node, dict):
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ks = node.keys()
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if {'left', 'top', 'width', 'height'} <= ks and all(isinstance(node[k], (int, float)) for k in ('left', 'top', 'width', 'height')):
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node['left'] = round(node['left'] * s)
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node['top'] = round(node['top'] * s)
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node['width'] = max(1, round(node['width'] * s))
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node['height'] = max(1, round(node['height'] * s))
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return
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if {'x', 'y'} <= ks and isinstance(node['x'], (int, float)) and isinstance(node['y'], (int, float)):
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node['x'] = round(node['x'] * s)
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node['y'] = round(node['y'] * s)
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return
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for v in node.values():
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scale_coords(v, s)
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elif isinstance(node, list):
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for v in node:
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scale_coords(v, s)
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def main():
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raw = json.load(open(os.path.join(REF, 'ref_3view_raw.json'), encoding='utf-8'))
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result = raw['result']
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src_w, src_h = Image.open(os.path.join(REF, 'images', 'C3_180.jpg')).size
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s = TARGET_W / src_w # 4000 → 1280:0.32
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target_h = round(src_h * s)
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# 正脸照片
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photo = Image.open(os.path.join(REF, 'images', 'C3_180.jpg')).convert('RGB')
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photo = photo.resize((TARGET_W, target_h), Image.LANCZOS)
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photo_url = to_data_url(photo, 'JPEG')
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# face_maps:白名单图层,同比例缩放;格式保持原样(jpeg 图层出 jpeg,透明叠加层出 png,与服务端魔数判定一致)
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maps = {}
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for k in MAP_KEYS:
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b64 = result.get('face_maps', {}).get(k)
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if not b64:
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continue
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im = Image.open(io.BytesIO(base64.b64decode(b64)))
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fmt = im.format # resize 后 format 丢失,先取
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im = im.resize((TARGET_W, target_h), Image.LANCZOS)
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maps[k] = to_data_url(im, 'JPEG' if fmt == 'JPEG' else 'PNG')
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# marks 坐标随照片同比例缩放(face_maps 已替换为缩放后 dataURL,不参与坐标缩放)
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result['face_maps'] = maps
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scale_coords(result, s)
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face_rect = raw.get('face_rectangle')
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if face_rect:
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scale_coords(face_rect, s)
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fixture = {
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'result': result,
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'face_rectangle': face_rect,
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'side': {'left': raw.get('left_side_result'), 'right': raw.get('right_side_result')},
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'photos': [photo_url, None, None] # 与 CAM_STEPS 同序:[0]正脸;侧脸图未纳入 fixture
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}
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out = os.path.join(ROOT, 'report-fixture.js')
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with open(out, 'w', encoding='utf-8') as f:
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f.write('/* 报告页可视化 mock fixture — 由 build-fixture.py 生成,勿手改\n')
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f.write(' 来源:ref_3view_raw.json(案例1)+ C3_180.jpg;照片与 face_maps 统一宽 %d,marks 坐标同比例缩放(×%.2f)\n' % (TARGET_W, s))
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f.write(' 仅在 ?mock=1 时由 index.html 按需注入,生产零额外请求 */\n')
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f.write('window.MOCK_FIXTURE = ')
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json.dump(fixture, f, ensure_ascii=False, separators=(',', ':'))
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f.write(';\n')
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print('[build-fixture] %s %.1f KB(照片 %d×%d,图层 %d 张)' % (
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out, os.path.getsize(out) / 1024, TARGET_W, target_h, len(maps)))
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if __name__ == '__main__':
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main()
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