"""标注图层生成（透明底 RGBA PNG，仅标注、不含人物）。 规格（技术方案 §6）：线/字色 #FFFFFF、字体 10pt、线宽 1pt、透明底。 - 四庭水平分界线：numpy 向量化渐变消失（中间亮、两侧渐隐）。 - 四庭 cm 数值：图片左侧。 - 七眼标注：眼宽/两眼间距/脸宽，虚线带箭头，标签上下穿插。 中文字体用打包的思源黑体绝对路径加载，缺字体直接抛错（不静默降级成方块）。 """ import os import numpy as np from PIL import Image, ImageDraw, ImageFont FONT_PATH = os.path.join(os.path.dirname(__file__), "fonts", "NotoSansCJKsc-Regular.otf") FONT_SIZE = 10 LINE_COLOR = (255, 255, 255, 255) # #FFFFFF 100% LINE_WIDTH = 1 def _load_font(): if not os.path.isfile(FONT_PATH): raise FileNotFoundError(f"中文字体缺失：{FONT_PATH}（请按 OFFLINE_ASSETS.md 放置）") return ImageFont.truetype(FONT_PATH, FONT_SIZE) def draw_gradient_horizontal_line(buf, cx, cy, color=LINE_COLOR, half_length=None): """在 RGBA numpy 缓冲 buf 上，以 (cx,cy) 为中心画向两侧渐变消失的水平线。 numpy 向量化：一次性算整行 alpha，避免逐像素 draw.point。 """ h, w = buf.shape[:2] cy = int(round(cy)); cx = int(round(cx)) if not (0 <= cy < h): return half = half_length or (w // 3) xs = np.arange(w) dist = np.abs(xs - cx) alpha = np.clip(1.0 - dist / half, 0.0, 1.0) * color[3] mask = alpha > 0 row = buf[cy] row[mask, 0] = color[0] row[mask, 1] = color[1] row[mask, 2] = color[2] row[mask, 3] = np.maximum(row[mask, 3], alpha[mask].astype(np.uint8)) def draw_gradient_vertical_line(buf, cx, y0, y1, color=LINE_COLOR, fade=None): """在 RGBA numpy 缓冲 buf 上画一条竖线，两端渐变消失（中间实、上下淡）。""" h, w = buf.shape[:2] cx = int(round(cx)) if not (0 <= cx < w): return y0, y1 = int(round(y0)), int(round(y1)) y0, y1 = max(0, min(y0, y1)), min(h - 1, max(y0, y1)) if y1 <= y0: return ys = np.arange(y0, y1 + 1) span = y1 - y0 fade = fade or max(1, span // 5) # 仅两端 ~1/5 段渐隐 d = np.minimum(ys - y0, y1 - ys) # 到最近端点的距离 alpha = np.clip(d / fade, 0.0, 1.0) * color[3] col = buf[y0:y1 + 1, cx] m = alpha > 0 col[m, 0] = color[0] col[m, 1] = color[1] col[m, 2] = color[2] col[m, 3] = np.maximum(col[m, 3], alpha[m].astype(np.uint8)) def draw_dashed_line_with_arrows(draw, x1, y1, x2, y2, color=LINE_COLOR, dash_len=6, gap_len=4, arrow_size=5): """两点间画虚线，两端带箭头（等腰三角）。""" total = ((x2 - x1) ** 2 + (y2 - y1) ** 2) ** 0.5 if total == 0: return dx = (x2 - x1) / total dy = (y2 - y1) / total pos = 0.0 while pos < total: seg_end = min(pos + dash_len, total) draw.line([(x1 + dx * pos, y1 + dy * pos), (x1 + dx * seg_end, y1 + dy * seg_end)], fill=color, width=LINE_WIDTH) pos += dash_len + gap_len # 法向量（用于箭头两翼张开） nx, ny = -dy, dx for (ex, ey, sdx, sdy) in [(x1, y1, dx, dy), (x2, y2, -dx, -dy)]: p1 = (ex + sdx * arrow_size + nx * arrow_size * 0.6, ey + sdy * arrow_size + ny * arrow_size * 0.6) p2 = (ex + sdx * arrow_size - nx * arrow_size * 0.6, ey + sdy * arrow_size - ny * arrow_size * 0.6) draw.line([p1, (ex, ey)], fill=color, width=LINE_WIDTH) draw.line([p2, (ex, ey)], fill=color, width=LINE_WIDTH) def _text_size(draw, text, font): bbox = draw.textbbox((0, 0), text, font=font) return bbox[2] - bbox[0], bbox[3] - bbox[1] _LINE_NAMES = { "hair_top": "头顶", "hairline": "发际线", "brow_center": "眉心", "nose_bottom": "鼻翼下缘", "chin_tip": "下巴尖", } def create_annotated_image(image_bgr, measure_result): """生成标注图层 PNG（透明底 RGBA，尺寸同原图）。返回 PIL.Image。 布局： - 线条只覆盖人脸范围（横线=脸宽，竖线=脸高），渐变消失。 - 横向 5 条分界线：头顶/发际线/眉心/鼻翼下缘/下巴尖，**线名在右侧**； 四庭 cm 数值（顶庭/上庭/中庭/下庭）在左侧各段中点。 - 纵向 6 条线：左脸颊/左眼外角/左眼内角/右眼内角/右眼外角/右脸颊，把脸宽切 5 段； 每段宽度在脸的**上端和下端**各标一次（只标 `X.XXcm`，不写名）。 """ h, w = image_bgr.shape[:2] v = measure_result.vertical pc = measure_result.px_per_cm buf = np.zeros((h, w, 4), dtype=np.uint8) order = ["hair_top", "hairline", "brow_center", "nose_bottom", "chin_tip"] ys = [v[name][1] for name in order] pts = measure_result.eyes["points"] seven_keys = ["left_cheek", "left_outer", "left_inner", "right_inner", "right_outer", "right_cheek"] xs = sorted(pts[k][0] for k in seven_keys) # 自左向右 # 人脸包围盒：x 为脸宽(左右脸颊)，y 为脸高(头顶→下巴) fx0, fx1 = xs[0], xs[-1] fy0, fy1 = ys[0], ys[-1] face_cx = (fx0 + fx1) / 2 face_half = (fx1 - fx0) / 2 * 1.08 # 略放大确保横线覆盖到脸颊 # --- 1. 横向 5 条分界线（渐变，覆盖脸宽） --- for cy in ys: draw_gradient_horizontal_line(buf, face_cx, cy, half_length=face_half) # --- 2. 纵向 6 条线（渐变，覆盖脸高 头顶→下巴） --- for vx in xs: draw_gradient_vertical_line(buf, vx, fy0, fy1) canvas = Image.fromarray(buf, mode="RGBA") draw = ImageDraw.Draw(canvas) font = _load_font() # --- 3a. 横线右侧：线名（头顶/发际线/眉心/鼻翼下缘/下巴尖） --- name_x = fx1 + 8 for i, name in enumerate(order): text = _LINE_NAMES[name] tw, _ = _text_size(draw, text, font) x = min(name_x, w - 2 - tw) # 右侧越界时回收 draw.text((x, ys[i] - FONT_SIZE / 2), text, fill=LINE_COLOR, font=font) # --- 3b. 横线左侧：四庭 cm 数值（各段中点，右对齐到脸盒左缘） --- court_cm = [measure_result.top_cm, measure_result.upper_cm, measure_result.middle_cm, measure_result.lower_cm] court_name = ["顶庭", "上庭", "中庭", "下庭"] for i in range(4): text = f"{court_name[i]} {court_cm[i]:.2f}cm" tw, _ = _text_size(draw, text, font) x = max(2, fx0 - 8 - tw) # 贴脸盒左缘，右对齐 y_mid = (ys[i] + ys[i + 1]) / 2 - FONT_SIZE / 2 draw.text((x, y_mid), text, fill=LINE_COLOR, font=font) # --- 4. 七眼每段宽度：脸的上端 + 下端各标一次（相邻段上下错行防重叠） --- row_h = FONT_SIZE + 2 y_top_a = max(1, fy0 - row_h - 2) # 上端：头顶线上方两行 y_top_b = max(1, fy0 - 2 * row_h - 2) y_bot_a = min(h - FONT_SIZE - 1, fy1 + 2) # 下端：下巴线下方两行 y_bot_b = min(h - FONT_SIZE - 1, fy1 + row_h + 2) for i in range(len(xs) - 1): seg_cm = (xs[i + 1] - xs[i]) / pc cx_seg = (xs[i] + xs[i + 1]) / 2 text = f"{seg_cm:.2f}cm" tw, _ = _text_size(draw, text, font) ty_top = y_top_a if i % 2 == 0 else y_top_b ty_bot = y_bot_a if i % 2 == 0 else y_bot_b draw.text((cx_seg - tw / 2, ty_top), text, fill=LINE_COLOR, font=font) draw.text((cx_seg - tw / 2, ty_bot), text, fill=LINE_COLOR, font=font) return canvas if __name__ == "__main__": import sys import time import cv2 from face_analysis.detector import detector from face_analysis.measure import measure_face path = sys.argv[1] if len(sys.argv) > 1 else "tests/fixtures/frontal.jpg" out = sys.argv[2] if len(sys.argv) > 2 else "tests/output/annotated.png" img = cv2.imread(path) if img is None: print(f"无法读取图片: {path}") sys.exit(1) h, w = img.shape[:2] lms = detector.detect(img) if lms is None: print("未检出人脸") sys.exit(1) mask = None try: from face_analysis.hair_segmenter import get_segmenter mask = get_segmenter().segment_hair(img) except Exception as e: # noqa: BLE001 print(f"[warn] 分割不可用，回退方案 A：{e}") result = measure_face(lms, mask, w, h) t0 = time.time() canvas = create_annotated_image(img, result) dt = time.time() - t0 os.makedirs(os.path.dirname(out), exist_ok=True) canvas.save(out) arr = np.asarray(canvas) print(f"saved {out} mode={canvas.mode} size={canvas.size} " f"transparent={bool((arr[:,:,3]==0).any())} opaque={bool((arr[:,:,3]>0).any())} " f"elapsed={dt*1000:.1f}ms")