xslandClaude Opus 4.8
f8e30ad32e
- 去掉 hairline_level 入参；middle/high/low 三档都返回
- 入参改为同接口2：gender + hair_style(逗号分隔多选，必填)，缺失/越界返回 1007
- 每个选中发型返回 image_{middle,high,low}_base64 三档叠图 + grown_image_base64 生发图，
按发型分组；order = 发型序号，含 hairline_type
- 生发黑模板仍固定 middle(hairline_texture_black/)，每发型 1 张生发图
- best_hairline_center_point 取首个选中发型的 middle 档
- 同步更新测试页(三档并排展示)、integration.html、stub_worker、接口文档/实现说明、test_api
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
182 lines
7.1 KiB
Python
182 lines
7.1 KiB
Python
"""接口集成测试（FastAPI TestClient）：错误码 + 鉴权 + 正常用例结构。"""
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import base64
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import json
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import pytest
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from fastapi.testclient import TestClient
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from conftest import fixture
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import app as app_module
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# 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）
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app_module.ACCEPT_PASSWORDS = ["testpass"]
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URL = "/api/v1/face/measure"
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H = {"X-Internal-Token": "testpass"}
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@pytest.fixture(scope="module")
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def client():
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# with 触发 lifespan：加载模型单例（detector + 尽力加载 segmenter）
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with TestClient(app_module.app) as c:
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yield c
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def _post(client, fixture_name=None, headers=H, data=None, extra_files=None):
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files = {}
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if fixture_name:
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files["image_file"] = (fixture_name, open(fixture(fixture_name), "rb"), "application/octet-stream")
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if extra_files:
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files.update(extra_files)
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return client.post(URL, headers=headers, files=files or None, data=data)
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def test_auth_missing_token_401(client):
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r = _post(client, "frontal.jpg", headers={})
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assert r.status_code == 401
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def test_health_no_token_200(client):
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r = client.get("/health")
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assert r.status_code == 200
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assert r.json()["status"] == "ok"
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def test_param_none_provided_1007(client):
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r = client.post(URL, headers=H)
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assert r.json()["code"] == 1007
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def test_param_multiple_provided_1007(client):
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r = _post(client, "frontal.jpg", data={"image_url": "http://example.com/x.jpg"})
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assert r.json()["code"] == 1007
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def test_no_face_1001(client):
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r = _post(client, "landscape.jpg")
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assert r.json()["code"] == 1001
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def test_corrupt_1008(client):
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r = _post(client, "corrupt.bin")
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assert r.json()["code"] == 1008
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GROW = "/api/v1/hair/grow"
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def test_grow_missing_gender_1004(client):
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files = {"image_file": ("frontal.jpg", open(fixture("frontal.jpg"), "rb"), "application/octet-stream")}
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r = client.post(GROW, headers=H, files=files)
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assert r.json()["code"] == 1004
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# mock ComfyUI 输出：一张合法 PNG（worker 会把它重编码成 JPG）
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import cv2 as _cv2
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import numpy as _np
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_PNG_1x1 = _cv2.imencode(".png", _np.full((8, 8, 3), 200, _np.uint8))[1].tobytes()
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def test_grow_female_returns_5(client, monkeypatch):
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# mock ComfyUI：不依赖 8182、不跑 Flux，只验证管线接线 + grown 字段
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import hairline.comfyui as comfy
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monkeypatch.setattr(comfy, "run", lambda *a, **k: _PNG_1x1)
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files = {"image_file": ("frontal.jpg", open(fixture("frontal.jpg"), "rb"), "application/octet-stream")}
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# hair_style 必填（cb1989c 起）：指定全部 5 种发型以验证完整管线
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r = client.post(GROW, headers=H, files=files, data={"gender": "female", "hair_style": "1,2,3,4,5"})
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body = r.json()
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assert body["code"] == 0, body
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results = body["data"]["results"]
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assert [x["hairline_type"] for x in results] == ["ellipse", "flower", "heart", "straight", "wave"]
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assert [x["order"] for x in results] == [1, 2, 3, 4, 5]
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assert base64.b64decode(results[0]["image_base64"])[:3] == b"\xff\xd8\xff" # JPEG
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assert base64.b64decode(results[0]["grown_image_base64"])[:3] == b"\xff\xd8\xff" # JPEG
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assert "image_url" not in results[0]
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GROWB = "/api/v1/hair/grow-b"
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def test_growb_missing_marked_1007(client):
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r = client.post(GROWB, headers=H) # 一张图都没传
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assert r.json()["code"] == 1007
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def test_growb_no_line_1001(client):
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files = {"marked_image_file": ("m.jpg", open(fixture("frontal.jpg"), "rb"), "application/octet-stream")}
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r = client.post(GROWB, headers=H, files=files) # 无划线 → 拒识
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assert r.json()["code"] == 1001
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def test_growb_success(client, monkeypatch):
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import hairline.comfyui as comfy
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monkeypatch.setattr(comfy, "run", lambda *a, **k: _PNG_1x1)
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files = {"marked_image_file": ("m.jpg", open(fixture("marked_hairline.jpg"), "rb"), "application/octet-stream")}
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body = client.post(GROWB, headers=H, files=files).json() # 只传划线图一张
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assert body["code"] == 0, body
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d = body["data"]
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assert d["hairline_type"] == "custom"
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assert base64.b64decode(d["hair_growth_image_base64"])[:3] == b"\xff\xd8\xff" # JPEG
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assert "best_hairline_image_base64" not in d # 已去掉该字段
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assert "best_hairline_image_url" not in d
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HLGEN = "/api/v1/hairline/generate"
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def test_hairline_gen_missing_gender_1004(client):
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files = {"image_file": ("frontal.jpg", open(fixture("frontal.jpg"), "rb"), "application/octet-stream")}
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assert client.post(HLGEN, headers=H, files=files).json()["code"] == 1004
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def test_hairline_gen_missing_hairstyle_1007(client):
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# hair_style 已改为必填（同接口2）：只给 gender、不给 hair_style → 1007
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files = {"image_file": ("frontal.jpg", open(fixture("frontal.jpg"), "rb"), "application/octet-stream")}
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assert client.post(HLGEN, headers=H, files=files, data={"gender": "female"}).json()["code"] == 1007
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def test_hairline_gen_female(client, monkeypatch):
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# mock ComfyUI：不依赖 8182，只验证三档叠图 + 生发字段接线
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import hairline.comfyui as comfy
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monkeypatch.setattr(comfy, "run", lambda *a, **k: _PNG_1x1)
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files = {"image_file": ("frontal.jpg", open(fixture("frontal.jpg"), "rb"), "application/octet-stream")}
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body = client.post(HLGEN, headers=H, files=files, data={"gender": "female", "hair_style": "1,3"}).json()
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assert body["code"] == 0, body
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d = body["data"]
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imgs = d["hairline_images"]
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# 只返回选中发型，order = 发型序号
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assert [x["order"] for x in imgs] == [1, 3]
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assert [x["hairline_type"] for x in imgs] == ["ellipse", "heart"]
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# 三档叠图 + 生发图均为 JPEG（worker 返回 base64，非 url）
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for k in ("image_middle_base64", "image_high_base64", "image_low_base64", "grown_image_base64"):
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assert base64.b64decode(imgs[0][k])[:3] == b"\xff\xd8\xff", k
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assert "image_middle_url" not in imgs[0]
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c = d["best_hairline_center_point"]
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assert 0 <= c["x"] <= 682 and 0 <= c["y"] <= 811 # 落在原图范围内
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# 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；
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# 其测试随实现一起在网关侧做，worker 这边不再覆盖。
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def test_success_structure(client):
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r = _post(client, "frontal.jpg")
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body = r.json()
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assert body["code"] == 0, body
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data = body["data"]
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# 业务字段对齐文档
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assert set(["face_total_height_cm", "four_courts", "seven_eyes",
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"landmarks", "hairline_source", "head_pose",
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"annotated_image_base64"]).issubset(data.keys())
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assert set(["top_court_cm", "upper_court_cm", "middle_court_cm",
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"lower_court_cm", "ratios"]).issubset(data["four_courts"].keys())
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assert set(["eye_width_cm", "face_width_cm", "inter_eye_distance_cm",
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"ratios"]).issubset(data["seven_eyes"].keys())
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assert data["hairline_source"] in ("segmentation", "estimated")
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# base64 解码为合法 PNG（非 URL）
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assert "annotated_image_url" not in data
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png = base64.b64decode(data["annotated_image_base64"])
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assert png[:8] == b"\x89PNG\r\n\x1a\n"
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