xsl
28255ef7c2
接口5（/api/v1/hairline/generate）在发际线结果基础上新增 data.face_measure， 复用接口1的四庭七眼测量数值（四庭/七眼 eye1~eye7/landmarks/姿态）， 不含标注图；独立流程容错，测量失败时为 null 不影响发际线主结果。 重构：提取 _run_face_measure_data() 共用函数，接口1/6 改调它再补标注图， 行为不变（43 测试全过，错误码 1001/1003/1008 回归正常）。 接口1/5 七眼新增 eye1~eye7 从左到右 7 段宽度（cm），eye1/eye7 耳朵不可见 时为 null（保留键）。 测试页 test_interface5.html：移除点击切换卡片网格改为所有发型平铺， 新增四庭七眼测量卡片。前端接入页 integration.html / 接口文档同步更新。
207 lines
8.8 KiB
Python
207 lines
8.8 KiB
Python
"""接口集成测试（FastAPI TestClient）：错误码 + 鉴权 + 正常用例结构。"""
|
||
import base64
|
||
import json
|
||
|
||
import pytest
|
||
from fastapi.testclient import TestClient
|
||
from conftest import fixture
|
||
|
||
import app as app_module
|
||
|
||
# 测试自带固定密码，避免依赖 worker_config.json 的实际值（中间件运行期读模块全局）
|
||
app_module.ACCEPT_PASSWORDS = ["testpass"]
|
||
|
||
URL = "/api/v1/face/measure"
|
||
H = {"X-Internal-Token": "testpass"}
|
||
|
||
|
||
@pytest.fixture(scope="module")
|
||
def client():
|
||
# with 触发 lifespan：加载模型单例（detector + 尽力加载 segmenter）
|
||
with TestClient(app_module.app) as c:
|
||
yield c
|
||
|
||
|
||
def _post(client, fixture_name=None, headers=H, data=None, extra_files=None):
|
||
files = {}
|
||
if fixture_name:
|
||
files["image_file"] = (fixture_name, open(fixture(fixture_name), "rb"), "application/octet-stream")
|
||
if extra_files:
|
||
files.update(extra_files)
|
||
return client.post(URL, headers=headers, files=files or None, data=data)
|
||
|
||
|
||
def test_auth_missing_token_401(client):
|
||
r = _post(client, "frontal.jpg", headers={})
|
||
assert r.status_code == 401
|
||
|
||
|
||
def test_health_no_token_200(client):
|
||
r = client.get("/health")
|
||
assert r.status_code == 200
|
||
assert r.json()["status"] == "ok"
|
||
|
||
|
||
def test_param_none_provided_1007(client):
|
||
r = client.post(URL, headers=H)
|
||
assert r.json()["code"] == 1007
|
||
|
||
|
||
def test_param_multiple_provided_1007(client):
|
||
r = _post(client, "frontal.jpg", data={"image_url": "http://example.com/x.jpg"})
|
||
assert r.json()["code"] == 1007
|
||
|
||
|
||
def test_no_face_1001(client):
|
||
r = _post(client, "landscape.jpg")
|
||
assert r.json()["code"] == 1001
|
||
|
||
|
||
def test_corrupt_1008(client):
|
||
r = _post(client, "corrupt.bin")
|
||
assert r.json()["code"] == 1008
|
||
|
||
|
||
GROW = "/api/v1/hair/grow"
|
||
|
||
|
||
def test_grow_missing_gender_1004(client):
|
||
files = {"image_file": ("frontal.jpg", open(fixture("frontal.jpg"), "rb"), "application/octet-stream")}
|
||
r = client.post(GROW, headers=H, files=files)
|
||
assert r.json()["code"] == 1004
|
||
|
||
|
||
# mock ComfyUI 输出：一张合法 PNG（worker 会把它重编码成 JPG）
|
||
import cv2 as _cv2
|
||
import numpy as _np
|
||
_PNG_1x1 = _cv2.imencode(".png", _np.full((8, 8, 3), 200, _np.uint8))[1].tobytes()
|
||
|
||
|
||
def test_grow_female_returns_5(client, monkeypatch):
|
||
# mock ComfyUI：不依赖 8182、不跑 Flux，只验证管线接线 + grown 字段
|
||
import hairline.comfyui as comfy
|
||
monkeypatch.setattr(comfy, "run", lambda *a, **k: _PNG_1x1)
|
||
|
||
files = {"image_file": ("frontal.jpg", open(fixture("frontal.jpg"), "rb"), "application/octet-stream")}
|
||
# hair_style 必填（cb1989c 起）：指定全部 5 种发型以验证完整管线
|
||
r = client.post(GROW, headers=H, files=files, data={"gender": "female", "hair_style": "1,2,3,4,5"})
|
||
body = r.json()
|
||
assert body["code"] == 0, body
|
||
results = body["data"]["results"]
|
||
assert [x["hairline_type"] for x in results] == ["ellipse", "flower", "heart", "straight", "wave"]
|
||
assert [x["order"] for x in results] == [1, 2, 3, 4, 5]
|
||
assert base64.b64decode(results[0]["image_base64"])[:3] == b"\xff\xd8\xff" # JPEG
|
||
assert base64.b64decode(results[0]["grown_image_base64"])[:3] == b"\xff\xd8\xff" # JPEG
|
||
assert "image_url" not in results[0]
|
||
|
||
|
||
GROWB = "/api/v1/hair/grow-b"
|
||
|
||
|
||
def test_growb_missing_marked_1007(client):
|
||
r = client.post(GROWB, headers=H) # 一张图都没传
|
||
assert r.json()["code"] == 1007
|
||
|
||
|
||
def test_growb_no_line_1001(client):
|
||
files = {"marked_image_file": ("m.jpg", open(fixture("frontal.jpg"), "rb"), "application/octet-stream")}
|
||
r = client.post(GROWB, headers=H, files=files) # 无划线 → 拒识
|
||
assert r.json()["code"] == 1001
|
||
|
||
|
||
def test_growb_success(client, monkeypatch):
|
||
import hairline.comfyui as comfy
|
||
monkeypatch.setattr(comfy, "run", lambda *a, **k: _PNG_1x1)
|
||
files = {"marked_image_file": ("m.jpg", open(fixture("marked_hairline.jpg"), "rb"), "application/octet-stream")}
|
||
body = client.post(GROWB, headers=H, files=files).json() # 只传划线图一张
|
||
assert body["code"] == 0, body
|
||
d = body["data"]
|
||
assert d["hairline_type"] == "custom"
|
||
assert base64.b64decode(d["hair_growth_image_base64"])[:3] == b"\xff\xd8\xff" # JPEG
|
||
assert "best_hairline_image_base64" not in d # 已去掉该字段
|
||
assert "best_hairline_image_url" not in d
|
||
|
||
|
||
HLGEN = "/api/v1/hairline/generate"
|
||
|
||
|
||
def test_hairline_gen_missing_gender_1004(client):
|
||
files = {"image_file": ("frontal.jpg", open(fixture("frontal.jpg"), "rb"), "application/octet-stream")}
|
||
assert client.post(HLGEN, headers=H, files=files).json()["code"] == 1004
|
||
|
||
|
||
def test_hairline_gen_missing_hairstyle_1007(client):
|
||
# hair_style 已改为必填（同接口2）：只给 gender、不给 hair_style → 1007
|
||
files = {"image_file": ("frontal.jpg", open(fixture("frontal.jpg"), "rb"), "application/octet-stream")}
|
||
assert client.post(HLGEN, headers=H, files=files, data={"gender": "female"}).json()["code"] == 1007
|
||
|
||
|
||
def test_hairline_gen_female(client, monkeypatch):
|
||
# mock ComfyUI：不依赖 8182，只验证三档叠图 + 生发字段接线
|
||
import hairline.comfyui as comfy
|
||
monkeypatch.setattr(comfy, "run", lambda *a, **k: _PNG_1x1)
|
||
|
||
files = {"image_file": ("frontal.jpg", open(fixture("frontal.jpg"), "rb"), "application/octet-stream")}
|
||
body = client.post(HLGEN, headers=H, files=files, data={"gender": "female", "hair_style": "1,3"}).json()
|
||
assert body["code"] == 0, body
|
||
d = body["data"]
|
||
imgs = d["hairline_images"]
|
||
# 只返回选中发型，order = 发型序号
|
||
assert [x["order"] for x in imgs] == [1, 3]
|
||
assert [x["hairline_type"] for x in imgs] == ["ellipse", "heart"]
|
||
# 三档叠图 + 生发图均为 JPEG（worker 返回 base64，非 url）
|
||
for k in ("image_middle_base64", "image_high_base64", "image_low_base64", "grown_image_base64"):
|
||
assert base64.b64decode(imgs[0][k])[:3] == b"\xff\xd8\xff", k
|
||
assert "image_middle_url" not in imgs[0]
|
||
c = d["best_hairline_center_point"]
|
||
assert 0 <= c["x"] <= 682 and 0 <= c["y"] <= 811 # 落在原图范围内
|
||
# face_measure：复用接口1测量数值（容错，失败为 null；本用例正常 → 必须有完整结构）
|
||
fm = d["face_measure"]
|
||
assert fm is not None, "face_measure 不应为 null（正常正面照）"
|
||
assert set(["face_total_height_cm", "four_courts", "seven_eyes",
|
||
"landmarks", "hairline_source", "head_pose"]).issubset(fm.keys())
|
||
# 不应含标注图字段（接口5 只要数值，不要画线图）
|
||
assert "annotated_image_base64" not in fm
|
||
assert "annotated_image_url" not in fm
|
||
# 子结构
|
||
assert set(["top_court_cm", "upper_court_cm", "middle_court_cm",
|
||
"lower_court_cm", "ratios"]).issubset(fm["four_courts"].keys())
|
||
assert set(["eye_width_cm", "face_width_cm", "inter_eye_distance_cm",
|
||
"ratios"]).issubset(fm["seven_eyes"].keys())
|
||
# 七眼 eye1~eye7 键必须存在（eye1/eye7 在耳朵不可见时可为 null）
|
||
assert set([f"eye{i}" for i in range(1, 8)]).issubset(fm["seven_eyes"].keys())
|
||
assert set(["hair_top", "hairline", "brow_center",
|
||
"nose_bottom", "chin_tip"]).issubset(fm["landmarks"].keys())
|
||
assert fm["hairline_source"] in ("segmentation", "estimated")
|
||
assert set(["yaw", "pitch", "roll"]).issubset(fm["head_pose"].keys())
|
||
|
||
|
||
# 接口4（用户特征）已迁到网关本机实现（直接调豆包），不再在 worker；
|
||
# 其测试随实现一起在网关侧做，worker 这边不再覆盖。
|
||
|
||
|
||
def test_success_structure(client):
|
||
r = _post(client, "frontal.jpg")
|
||
body = r.json()
|
||
assert body["code"] == 0, body
|
||
data = body["data"]
|
||
# 业务字段对齐文档
|
||
assert set(["face_total_height_cm", "four_courts", "seven_eyes",
|
||
"landmarks", "hairline_source", "head_pose",
|
||
"annotated_image_base64"]).issubset(data.keys())
|
||
assert set(["top_court_cm", "upper_court_cm", "middle_court_cm",
|
||
"lower_court_cm", "ratios"]).issubset(data["four_courts"].keys())
|
||
assert set(["eye_width_cm", "face_width_cm", "inter_eye_distance_cm",
|
||
"ratios"]).issubset(data["seven_eyes"].keys())
|
||
# 七眼：从左到右 eye1~eye7（eye1/eye7 在耳朵不可见时可为 null，但键必须存在）
|
||
assert set([f"eye{i}" for i in range(1, 8)]).issubset(data["seven_eyes"].keys())
|
||
# eye3/eye5 为左右眼宽、eye4 为两眼间距，与 eye_width_cm/inter_eye_distance_cm 语义一致
|
||
assert data["seven_eyes"]["eye3"] is not None
|
||
assert data["seven_eyes"]["eye4"] is not None
|
||
assert data["seven_eyes"]["eye5"] is not None
|
||
assert data["hairline_source"] in ("segmentation", "estimated")
|
||
# base64 解码为合法 PNG（非 URL）
|
||
assert "annotated_image_url" not in data
|
||
png = base64.b64decode(data["annotated_image_base64"])
|
||
assert png[:8] == b"\x89PNG\r\n\x1a\n"
|