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feat: 接口1/6 发际线贴近头顶时改为修正而非弃用置null

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顶庭(头顶→发际线)<0.7cm 时不再返回 null：
- 上庭 = 0.95×中庭 反推发际线；若越过头顶则顶庭固定 0.7cm（发际线钉在头顶下方）
- hairline_source 新增 "corrected"；to_response 始终输出完整四庭
- 标注图始终正常画发际线横线与庭段
- 接口6 三庭逻辑同步，去 discarded 分支

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
xsl
2026-08-08 11:47:16 +08:00
co-authored by Claude
parent 6ffc7f343d
commit 63ee8444c0
5 changed files with 91 additions and 135 deletions
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app.py
+21 -36
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@@ -401,36 +401,22 @@ def _run_face_measure_data(image, variant="v1"):
logger.warning("头发/耳朵分割失败，回退方案A：%s", seg_e) logger.warning("头发/耳朵分割失败，回退方案A：%s", seg_e)
result = measure_face(landmarks, hair_mask, w, h, head_pose=head_pose) result = measure_face(landmarks, hair_mask, w, h, head_pose=head_pose)
discarded = result.hairline_discarded
data = result.to_response() data = result.to_response()
vd = result.vertical vd = result.vertical
if variant == "v6": if variant == "v6":
if discarded: # 接口6 是三庭：去掉顶庭相关字段（top_court_cm / ratios.top_court），
# 发际线弃用：接口6 的上庭也依赖发际线，一并置 null；只保留中/下庭。 # 比例分母按上/中/下三庭。发际线贴近头顶时已在 measure 修正，hairline 正常返回。
base_px = vd["middle_court_px"] + vd["lower_court_px"] base_px = vd["upper_court_px"] + vd["middle_court_px"] + vd["lower_court_px"]
data["four_courts"]["upper_court_cm"] = None data["four_courts"]["ratios"] = {
data["four_courts"]["ratios"] = { "upper_court": round(vd["upper_court_px"] / base_px, 3),
"upper_court": None, "middle_court": round(vd["middle_court_px"] / base_px, 3),
"middle_court": round(vd["middle_court_px"] / base_px, 3), "lower_court": round(vd["lower_court_px"] / base_px, 3),
"lower_court": round(vd["lower_court_px"] / base_px, 3), }
} data["four_courts"].pop("top_court_cm", None)
data["four_courts"].pop("top_court_cm", None) data["face_total_height_cm"] = round(
data["face_total_height_cm"] = round( result.upper_cm + result.middle_cm + result.lower_cm, 2)
result.middle_cm + result.lower_cm, 2) # 注：landmarks.hair_top 保留返回（供前端/下游定位头顶），但顶庭数值、
data["landmarks"]["hairline"] = None # 占比、标注图仍按三庭处理，显示效果不变。
else:
base_px = vd["upper_court_px"] + vd["middle_court_px"] + vd["lower_court_px"]
# 接口6 是三庭：去掉顶庭相关字段（top_court_cm / ratios.top_court / landmarks.hair_top）
data["four_courts"]["ratios"] = {
"upper_court": round(vd["upper_court_px"] / base_px, 3),
"middle_court": round(vd["middle_court_px"] / base_px, 3),
"lower_court": round(vd["lower_court_px"] / base_px, 3),
}
data["four_courts"].pop("top_court_cm", None)
data["face_total_height_cm"] = round(
result.upper_cm + result.middle_cm + result.lower_cm, 2)
# 注：landmarks.hair_top 保留返回（供前端/下游定位头顶），但顶庭数值、
# 占比、标注图仍按三庭处理，显示效果不变。
# 七眼段宽度（cm）。eye1=左耳外段 eye2=左脸颊 eye3=左眼 eye4=两眼间距 eye5=右眼 eye6=右脸颊 eye7=右耳外段。 # 七眼段宽度（cm）。eye1=左耳外段 eye2=左脸颊 eye3=左眼 eye4=两眼间距 eye5=右眼 eye6=右脸颊 eye7=右耳外段。
# eye2~eye6（5段）只用内部分点，接口1/6 共用；eye1/eye7 需耳朵分割端线，仅接口1 有。 # eye2~eye6（5段）只用内部分点，接口1/6 共用；eye1/eye7 需耳朵分割端线，仅接口1 有。
@@ -446,10 +432,9 @@ def _run_face_measure_data(image, variant="v1"):
None if (a is None or b is None) else round((b - a) / pc, 2)) None if (a is None or b is None) else round((b - a) / pc, 2))
if variant != "v6": if variant != "v6":
# 接口1 额外算 eye1/eye7（左/右耳外段），需耳朵分割端线。 # 接口1 额外算 eye1/eye7（左/右耳外段），需耳朵分割端线。
# 竖向范围：发际线弃用时用眉心做上界（hair_top 不可靠），否则用头顶。 # 竖向范围上界用头顶（hair_top 始终可用）。
from face_analysis.annotation import _ear_edges_from_mask from face_analysis.annotation import _ear_edges_from_mask
top_y = (vd["brow_center"][1] if result.hairline_discarded top_y = vd["hair_top"][1]
else vd["hair_top"][1])
head_l, head_r = _ear_edges_from_mask( head_l, head_r = _ear_edges_from_mask(
ear_mask, hair_mask, ear_mask, hair_mask,
top_y, vd["chin_tip"][1], top_y, vd["chin_tip"][1],
@@ -709,11 +694,11 @@ def _run_face_measure_data_debug(image):
_draw_text_cv2(vis_hl, f"hairline_y={hairline_y} (source={result.hairline_source})", _draw_text_cv2(vis_hl, f"hairline_y={hairline_y} (source={result.hairline_source})",
(hairline_y, w - int(s * 0.5)), color=(0, 200, 255), (hairline_y, w - int(s * 0.5)), color=(0, 200, 255),
scale=max(0.4, s * 0.0015)) scale=max(0.4, s * 0.0015))
# 发际线弃用提示：顶庭 < 0.7cm 视为贴近头顶、不可靠 # 发际线修正提示：检测到的顶庭 < 0.7cm 视为贴近头顶、已按 0.95×中庭修正
if result.hairline_discarded: if getattr(result, "hairline_corrected", False):
gap_cm = result.top_cm gap_cm = result.detected_top_cm
_draw_text_cv2(vis_hl, _draw_text_cv2(vis_hl,
f"⚠️ 发际线离头顶仅 {gap_cm:.2f}cm (<0.7cm)，已弃用", f"⚠️ 发际线离头顶仅 {gap_cm:.2f}cm (<0.7cm)，已按 0.95×中庭修正",
(10, 10), color=(40, 40, 255), scale=max(0.5, s * 0.0022)) (10, 10), color=(40, 40, 255), scale=max(0.5, s * 0.0022))
put("hairline", vis_hl) put("hairline", vis_hl)
@@ -829,8 +814,8 @@ def _run_face_measure_data_debug(image):
None if (a is None or b is None) else round((b - a) / pc, 2)) None if (a is None or b is None) else round((b - a) / pc, 2))
from face_analysis.annotation import _ear_edges_from_mask as _eef from face_analysis.annotation import _ear_edges_from_mask as _eef
lcx, rcx = epts["left_cheek"][0], epts["right_cheek"][0] lcx, rcx = epts["left_cheek"][0], epts["right_cheek"][0]
# 弃用时用眉心做上界（与 _run_face_measure_data 一致） # 竖向范围上界用头顶（hair_top 始终可用）
top_y = v["brow_center"][1] if result.hairline_discarded else v["hair_top"][1] top_y = v["hair_top"][1]
head_l, head_r = _eef(ear_mask, hair_mask, top_y, v["chin_tip"][1], head_l, head_r = _eef(ear_mask, hair_mask, top_y, v["chin_tip"][1],
lcx, rcx, (lcx + rcx) / 2) lcx, rcx, (lcx + rcx) / 2)
data["seven_eyes"]["eye1"] = None if head_l is None else round((lcx - head_l) / pc, 2) data["seven_eyes"]["eye1"] = None if head_l is None else round((lcx - head_l) / pc, 2)
docs/接口文档.md
+1 -1
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@@ -446,7 +446,7 @@
| four_courts | object | 四庭数据（顶/上/中/下庭 cm + 占比 ratios），结构同接口1 | | four_courts | object | 四庭数据（顶/上/中/下庭 cm + 占比 ratios），结构同接口1 |
| seven_eyes | object | 七眼数据（眼宽/脸宽/两眼间距 cm + 占比 ratios + eye1~eye7 从左到右 7 段宽度），结构同接口1 | | seven_eyes | object | 七眼数据（眼宽/脸宽/两眼间距 cm + 占比 ratios + eye1~eye7 从左到右 7 段宽度），结构同接口1 |
| landmarks | object | 5 个纵向关键点像素坐标（hair_top/hairline/brow_center/nose_bottom/chin_tip），结构同接口1 | | landmarks | object | 5 个纵向关键点像素坐标（hair_top/hairline/brow_center/nose_bottom/chin_tip），结构同接口1 |
| hairline_source | string | 发际线来源：`segmentation`（真实分割）/ `estimated`（比例估算） | | hairline_source | string | 发际线来源：`segmentation`（真实分割）/ `estimated`（比例估算）/ `corrected`（发际线贴近头顶、分割不可靠，已按 0.95×中庭反推修正） |
| head_pose | object | 头部姿态角度（yaw/pitch/roll，单位：度） | | head_pose | object | 头部姿态角度（yaw/pitch/roll，单位：度） |
| left_position | object | MediaPipe 21 号关键点坐标（左脸定位点），原图像素：`{ "x": int, "y": int }` | | left_position | object | MediaPipe 21 号关键点坐标（左脸定位点），原图像素：`{ "x": int, "y": int }` |
| right_position | object | MediaPipe 251 号关键点坐标（右脸定位点，与 21 号镜像），原图像素：`{ "x": int, "y": int }` | | right_position | object | MediaPipe 251 号关键点坐标（右脸定位点，与 21 号镜像），原图像素：`{ "x": int, "y": int }` |
face_analysis/annotation.py
+6 -14
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@@ -212,11 +212,9 @@ def create_annotated_image(image_bgr, measure_result, ear_mask=None, hair_mask=N
buf = np.zeros((h, w, 4), dtype=np.uint8) buf = np.zeros((h, w, 4), dtype=np.uint8)
# 发际线弃用（hairline_discarded）：保留头顶横线，去掉发际线横线， # 横线：v1 = 头顶/发际线/眉心/鼻翼下缘/下巴尖；v6 = 发际线/眉心/鼻翼下缘/下巴尖。
# 也不标顶/上庭（缺发际线作边界，算不出）。横线 = 头顶/眉心/鼻翼下缘/下巴尖。 # （发际线贴近头顶时已在 MeasureResult 修正 vertical，此处始终正常画发际线。）
if getattr(measure_result, "hairline_discarded", False): if variant == "v6":
order = ["hair_top", "brow_center", "nose_bottom", "chin_tip"]
elif variant == "v6":
order = ["hairline", "brow_center", "nose_bottom", "chin_tip"] order = ["hairline", "brow_center", "nose_bottom", "chin_tip"]
else: else:
order = ["hair_top", "hairline", "brow_center", "nose_bottom", "chin_tip"] order = ["hair_top", "hairline", "brow_center", "nose_bottom", "chin_tip"]
@@ -243,7 +241,7 @@ def create_annotated_image(image_bgr, measure_result, ear_mask=None, hair_mask=N
face_cx = (fx0 + fx1) / 2 face_cx = (fx0 + fx1) / 2
over = max(6, round(s * 0.030)) # 线超出包围盒的长度（参考图风格） over = max(6, round(s * 0.030)) # 线超出包围盒的长度（参考图风格）
face_half = (fx1 - fx0) / 2 + over # 横线超出最外侧竖线一点 face_half = (fx1 - fx0) / 2 + over # 横线超出最外侧竖线一点
# 竖线纵向范围：v6 = 发际线→下巴尖（不超出）；v1（含发际线弃用）= 头顶→下巴尖并两端超出一点 # 竖线纵向范围：v6 = 发际线→下巴尖（不超出）；v1 = 头顶→下巴尖并两端超出一点
v_top = fy0 if variant == "v6" else fy0 - over v_top = fy0 if variant == "v6" else fy0 - over
v_bot = fy1 if variant == "v6" else fy1 + over v_bot = fy1 if variant == "v6" else fy1 + over
@@ -281,14 +279,8 @@ def create_annotated_image(image_bgr, measure_result, ear_mask=None, hair_mask=N
draw.text((x, ys[i]), text, fill=LINE_COLOR, font=font, anchor="lm") draw.text((x, ys[i]), text, fill=LINE_COLOR, font=font, anchor="lm")
# --- 3b. 左侧四庭：名 + 数值两行（无 cm）+ 竖向虚线双箭头 --- # --- 3b. 左侧四庭：名 + 数值两行（无 cm）+ 竖向虚线双箭头 ---
# court_start：庭段在 order 里的起始索引。发际线弃用时 order 首位是头顶（无下界发际线， # court_start：庭段在 order 里的起始索引。v6 为三庭（无顶庭），其余四庭。
# 顶/上庭不标），中庭从眉心开始 → 跳过 order[0]。 if variant == "v6":
if getattr(measure_result, "hairline_discarded", False):
court_cm = [measure_result.middle_cm, measure_result.lower_cm]
court_name = ["中庭", "下庭"]
n_court = 2
court_start = 1
elif variant == "v6":
court_cm = [measure_result.upper_cm, measure_result.middle_cm, measure_result.lower_cm] court_cm = [measure_result.upper_cm, measure_result.middle_cm, measure_result.lower_cm]
court_name = ["上庭", "中庭", "下庭"] court_name = ["上庭", "中庭", "下庭"]
n_court = 3 n_court = 3
face_analysis/measure.py
+61 -82
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@@ -153,10 +153,12 @@ def pt_or_none(vertical, name):
class MeasureResult: class MeasureResult:
"""测量结果，提供 to_response() 输出与接口文档同构的 data 字段。""" """测量结果，提供 to_response() 输出与接口文档同构的 data 字段。"""
# 发际线弃用阈值：发际线离头顶（顶庭）< 此值时判定分割不可靠，弃用发际线。 # 发际线修正阈值/固定值：发际线离头顶（顶庭）< 此值时判定分割不可靠，需修正发际线。
# hairline 与 hair_top 几乎重合（如稀疏头发中轴漏检只剩一小撮），说明发际线 # hairline 与 hair_top 几乎重合（如稀疏头发中轴漏检只剩一小撮）→ 上庭改取
# 定位无意义 → 顶/上庭置 null、标注图不画头顶/发际线。 # 0.95×中庭反推发际线；若反推后越过头顶，则顶庭固定为 0.7cm（发际线钉在头顶下方
HAIRLINE_DISCARD_TOP_CM = 0.7 # 0.7cm），上庭取眉心→发际线剩余距离。修正后始终返回完整四庭，不再置 null。
HAIRLINE_CORRECT_TOP_CM = 0.7
UPPER_TO_MIDDLE_RATIO = 0.95 # 贴近头顶时，上庭 = 中庭 × 此比例
def __init__(self, vertical, eyes, px_per_cm, hairline_source, head_pose, def __init__(self, vertical, eyes, px_per_cm, hairline_source, head_pose,
landmarks=None, image_width=None, image_height=None): landmarks=None, image_width=None, image_height=None):
@@ -170,19 +172,32 @@ class MeasureResult:
self.w = image_width self.w = image_width
self.h = image_height self.h = image_height
# 各庭厘米 # 发际线修正：顶庭（头顶→发际线）< 阈值视为发际线贴近头顶、不可靠。
# 改写：上庭 = 0.95×中庭 → 由眉心反推发际线 y；若发际线越过头顶
# （hairline_y < hair_top_y），顶庭固定为 0.7cm（发际线钉在头顶下方 0.7cm）。
# 回写 vertical，使 to_response/标注图/v6 复用全部拿到修正后的发际线。
self.detected_top_cm = vertical["top_court_px"] / px_per_cm
self.hairline_corrected = self.detected_top_cm < self.HAIRLINE_CORRECT_TOP_CM
if self.hairline_corrected:
brow_x, brow_y = vertical["brow_center"]
hair_top_y = vertical["hair_top"][1]
new_upper_px = vertical["middle_court_px"] * self.UPPER_TO_MIDDLE_RATIO
hairline_y = brow_y - new_upper_px
if hairline_y < hair_top_y: # 反推发际线越过头顶 → 顶庭固定 0.7cm
hairline_y = hair_top_y + self.HAIRLINE_CORRECT_TOP_CM * px_per_cm
new_upper_px = brow_y - hairline_y
vertical["hairline"] = (brow_x, float(hairline_y))
vertical["upper_court_px"] = new_upper_px
vertical["top_court_px"] = hairline_y - hair_top_y
self.hairline_source = "corrected"
# 各庭厘米（修正后）
self.top_cm = vertical["top_court_px"] / px_per_cm self.top_cm = vertical["top_court_px"] / px_per_cm
self.upper_cm = vertical["upper_court_px"] / px_per_cm self.upper_cm = vertical["upper_court_px"] / px_per_cm
self.middle_cm = vertical["middle_court_px"] / px_per_cm self.middle_cm = vertical["middle_court_px"] / px_per_cm
self.lower_cm = vertical["lower_court_px"] / px_per_cm self.lower_cm = vertical["lower_court_px"] / px_per_cm
# 发际线弃用判定：顶庭（头顶→发际线）过小视为发际线贴近头顶、不可靠。 self.face_total_cm = (self.top_cm + self.upper_cm
# 弃用时 hairline_source 改为 "discarded"，face_total 只算中庭+下庭。 + self.middle_cm + self.lower_cm)
self.hairline_discarded = self.top_cm < self.HAIRLINE_DISCARD_TOP_CM
if self.hairline_discarded:
self.hairline_source = "discarded"
self.face_total_cm = self.middle_cm + self.lower_cm
else:
self.face_total_cm = self.top_cm + self.upper_cm + self.middle_cm + self.lower_cm
# 七眼厘米 # 七眼厘米
self.eye_width_cm = eyes["eye_width_px"] / px_per_cm self.eye_width_cm = eyes["eye_width_px"] / px_per_cm
@@ -190,77 +205,41 @@ class MeasureResult:
self.inter_eye_cm = eyes["inter_eye_distance_px"] / px_per_cm self.inter_eye_cm = eyes["inter_eye_distance_px"] / px_per_cm
def to_response(self): def to_response(self):
# 发际线弃用：顶/上庭相关字段置 null（保留键），ratio 分母只算中下庭； # 四庭完整输出（发际线贴近头顶时已在 __init__ 修正 vertical，无 null 分支）。
# landmarks.hair_top/hairline 置 null。否则按四庭正常输出。 total_px = (self.vertical["top_court_px"] + self.vertical["upper_court_px"]
if self.hairline_discarded: + self.vertical["middle_court_px"] + self.vertical["lower_court_px"])
base_px = (self.vertical["middle_court_px"] + self.vertical["lower_court_px"]) data = {
data = { "face_total_height_cm": round(self.face_total_cm, 2),
"face_total_height_cm": round(self.face_total_cm, 2), "four_courts": {
"four_courts": { "top_court_cm": round(self.top_cm, 2),
"top_court_cm": None, "upper_court_cm": round(self.upper_cm, 2),
"upper_court_cm": None, "middle_court_cm": round(self.middle_cm, 2),
"middle_court_cm": round(self.middle_cm, 2), "lower_court_cm": round(self.lower_cm, 2),
"lower_court_cm": round(self.lower_cm, 2), "ratios": {
"ratios": { "top_court": round(self.vertical["top_court_px"] / total_px, 3),
"top_court": None, "upper_court": round(self.vertical["upper_court_px"] / total_px, 3),
"upper_court": None, "middle_court": round(self.vertical["middle_court_px"] / total_px, 3),
"middle_court": round(self.vertical["middle_court_px"] / base_px, 3), "lower_court": round(self.vertical["lower_court_px"] / total_px, 3),
"lower_court": round(self.vertical["lower_court_px"] / base_px, 3),
},
}, },
"seven_eyes": { },
"eye_width_cm": round(self.eye_width_cm, 2), "seven_eyes": {
"face_width_cm": round(self.face_width_cm, 2), "eye_width_cm": round(self.eye_width_cm, 2),
"inter_eye_distance_cm": round(self.inter_eye_cm, 2), "face_width_cm": round(self.face_width_cm, 2),
"ratios": { "inter_eye_distance_cm": round(self.inter_eye_cm, 2),
"eye_width": round(self.eyes["eye_width_px"] / self.eyes["face_width_px"], 3), "ratios": {
"inter_eye_distance": round(self.eyes["inter_eye_distance_px"] / self.eyes["face_width_px"], 3), "eye_width": round(self.eyes["eye_width_px"] / self.eyes["face_width_px"], 3),
}, "inter_eye_distance": round(self.eyes["inter_eye_distance_px"] / self.eyes["face_width_px"], 3),
}, },
"landmarks": { },
"hair_top": None, "landmarks": {
"hairline": None, "hair_top": pt_or_none(self.vertical, "hair_top"),
"brow_center": pt_or_none(self.vertical, "brow_center"), "hairline": pt_or_none(self.vertical, "hairline"),
"nose_bottom": pt_or_none(self.vertical, "nose_bottom"), "brow_center": pt_or_none(self.vertical, "brow_center"),
"chin_tip": pt_or_none(self.vertical, "chin_tip"), "nose_bottom": pt_or_none(self.vertical, "nose_bottom"),
}, "chin_tip": pt_or_none(self.vertical, "chin_tip"),
"hairline_source": self.hairline_source, },
} "hairline_source": self.hairline_source,
else: }
total_px = (self.vertical["top_court_px"] + self.vertical["upper_court_px"]
+ self.vertical["middle_court_px"] + self.vertical["lower_court_px"])
data = {
"face_total_height_cm": round(self.face_total_cm, 2),
"four_courts": {
"top_court_cm": round(self.top_cm, 2),
"upper_court_cm": round(self.upper_cm, 2),
"middle_court_cm": round(self.middle_cm, 2),
"lower_court_cm": round(self.lower_cm, 2),
"ratios": {
"top_court": round(self.vertical["top_court_px"] / total_px, 3),
"upper_court": round(self.vertical["upper_court_px"] / total_px, 3),
"middle_court": round(self.vertical["middle_court_px"] / total_px, 3),
"lower_court": round(self.vertical["lower_court_px"] / total_px, 3),
},
},
"seven_eyes": {
"eye_width_cm": round(self.eye_width_cm, 2),
"face_width_cm": round(self.face_width_cm, 2),
"inter_eye_distance_cm": round(self.inter_eye_cm, 2),
"ratios": {
"eye_width": round(self.eyes["eye_width_px"] / self.eyes["face_width_px"], 3),
"inter_eye_distance": round(self.eyes["inter_eye_distance_px"] / self.eyes["face_width_px"], 3),
},
},
"landmarks": {
"hair_top": pt_or_none(self.vertical, "hair_top"),
"hairline": pt_or_none(self.vertical, "hairline"),
"brow_center": pt_or_none(self.vertical, "brow_center"),
"nose_bottom": pt_or_none(self.vertical, "nose_bottom"),
"chin_tip": pt_or_none(self.vertical, "chin_tip"),
},
"hairline_source": self.hairline_source,
}
# left/right_position：mediapipe 21/251 号定位点（原图像素，与 landmarks 同坐标系）。 # left/right_position：mediapipe 21/251 号定位点（原图像素，与 landmarks 同坐标系）。
# landmarks 缺省（如测试直构 MeasureResult）时不输出，保持向后兼容。 # landmarks 缺省（如测试直构 MeasureResult）时不输出，保持向后兼容。
if self.landmarks is not None and self.w and self.h: if self.landmarks is not None and self.w and self.h:
tests/test_api.py
+2 -2
View File
@@ -173,7 +173,7 @@ def test_hairline_gen_female(client, monkeypatch):
assert set([f"eye{i}" for i in range(1, 8)]).issubset(fm["seven_eyes"].keys()) assert set([f"eye{i}" for i in range(1, 8)]).issubset(fm["seven_eyes"].keys())
assert set(["hair_top", "hairline", "brow_center", assert set(["hair_top", "hairline", "brow_center",
"nose_bottom", "chin_tip"]).issubset(fm["landmarks"].keys()) "nose_bottom", "chin_tip"]).issubset(fm["landmarks"].keys())
assert fm["hairline_source"] in ("segmentation", "estimated") assert fm["hairline_source"] in ("segmentation", "estimated", "corrected")
assert set(["yaw", "pitch", "roll"]).issubset(fm["head_pose"].keys()) assert set(["yaw", "pitch", "roll"]).issubset(fm["head_pose"].keys())
@@ -200,7 +200,7 @@ def test_success_structure(client):
assert data["seven_eyes"]["eye3"] is not None assert data["seven_eyes"]["eye3"] is not None
assert data["seven_eyes"]["eye4"] is not None assert data["seven_eyes"]["eye4"] is not None
assert data["seven_eyes"]["eye5"] is not None assert data["seven_eyes"]["eye5"] is not None
assert data["hairline_source"] in ("segmentation", "estimated") assert data["hairline_source"] in ("segmentation", "estimated", "corrected")
# base64 解码为合法 PNG（非 URL） # base64 解码为合法 PNG（非 URL）
assert "annotated_image_url" not in data assert "annotated_image_url" not in data
png = base64.b64decode(data["annotated_image_base64"]) png = base64.b64decode(data["annotated_image_base64"])