hair/face_analysis/annotation.py

"""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_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]


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（避免重叠）：
    - 四庭水平分界线（渐变消失），四庭 cm 数值在**左侧**各段中点。
    - **全脸总高**：右侧竖向标尺（虚线双箭头，头顶→下巴），标签在标尺左侧竖排。
    - 七眼：单眼宽度 / 两眼间距 / 脸宽 三个量**上下错开三个高度**，
      各自虚线带箭头 + 紧贴各自线条的标签，互不重叠。
    """
    h, w = image_bgr.shape[:2]
    v = measure_result.vertical

    # --- 1. 四庭水平分界线（numpy 渐变） ---
    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]
    cx_line = v["brow_center"][0]
    for cy in ys:
        draw_gradient_horizontal_line(buf, cx_line, cy)

    canvas = Image.fromarray(buf, mode="RGBA")
    draw = ImageDraw.Draw(canvas)
    font = _load_font()

    # --- 2. 四庭 cm 数值（左侧，各段中点） ---
    court_labels = [
        ("顶庭", measure_result.top_cm),
        ("上庭", measure_result.upper_cm),
        ("中庭", measure_result.middle_cm),
        ("下庭", measure_result.lower_cm),
    ]
    left_margin = 12
    for i, (label, cm_val) in enumerate(court_labels):
        y_mid = (ys[i] + ys[i + 1]) / 2 - FONT_SIZE / 2
        draw.text((left_margin, y_mid), f"{label} {cm_val:.2f}cm",
                  fill=LINE_COLOR, font=font)

    # --- 3. 全脸总高：右侧竖向标尺（头顶→下巴，虚线双箭头） ---
    top_y, chin_y = ys[0], ys[-1]
    ruler_x = w - 30                              # 内移，使竖线与箭头完整可见
    draw_dashed_line_with_arrows(draw, ruler_x, top_y, ruler_x, chin_y)
    th_lines = ["全脸总高", f"{measure_result.face_total_cm:.2f}cm"]
    th_w = max(_text_size(draw, t, font)[0] for t in th_lines)
    th_x = ruler_x - 6 - th_w                     # 标签放标尺左侧，避免出界
    th_y = (top_y + chin_y) / 2 - FONT_SIZE       # 竖向居中（两行）
    for j, t in enumerate(th_lines):
        draw.text((th_x, th_y + j * (FONT_SIZE + 3)), t, fill=LINE_COLOR, font=font)

    # --- 4. 七眼：上下错开三个高度，各自虚线箭头 + 标签 ---
    pts = measure_result.eyes["points"]
    eye_y = (pts["left_inner"][1] + pts["right_inner"][1]) / 2
    vgap = FONT_SIZE + 12  # 行间距，保证标签放得下

    def span(p_left, p_right, y, label, cm_val, label_above):
        draw_dashed_line_with_arrows(draw, p_left[0], y, p_right[0], y)
        text = f"{label} {cm_val:.2f}cm"
        tw, _ = _text_size(draw, text, font)
        tx = (p_left[0] + p_right[0]) / 2 - tw / 2
        ty = y - FONT_SIZE - 3 if label_above else y + 3
        draw.text((tx, ty), text, fill=LINE_COLOR, font=font)

    # 单眼宽度（眼睛线，标签在上）
    span(pts["left_outer"], pts["left_inner"], eye_y,
         "单眼宽度", measure_result.eye_width_cm, label_above=True)
    # 两眼间距（稍下一层，标签在线上方的空档）
    span(pts["left_inner"], pts["right_inner"], eye_y + vgap,
         "两眼间距", measure_result.inter_eye_cm, label_above=True)
    # 脸宽（再下一层，标签在下）
    span(pts["left_cheek"], pts["right_cheek"], eye_y + 2 * vgap,
         "脸宽", measure_result.face_width_cm, label_above=False)

    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")