xsl
95c6a2d929
接口2（/api/v1/hair/grow）的 image_url 和接口5（/api/v1/hairline/generate） 的 image_middle/high/low_url 从「原图+白线合成 JPG」改为「透明底 PNG（仅含 发际线曲线）」，前端需叠加原图显示。grown_image_url 生发图保持不变（ComfyUI 完整人像照片）。 实现： - app.py 新增 _rgba_png_b64() 编码 RGBA 透明层为 PNG base64（保留 alpha） - hairline/service.py 接口2/5 改用 build_overlay_layer（返回 RGBA 透明层） 替代 render_hairline_overlay（合成到原图） - 网关零改动：rewrite_base64_to_url 已按 \x89PNG 魔数嗅探落盘为 .png 测试页：test_interface2/5.html 改为「原图打底 + 透明PNG 绝对定位叠加」显示 （复用 .img-stack 结构，固定叠加无开关）。 文档：接口文档.md / integration.html 更新接口2/5 图片字段说明。 测试：43 passed，接口2 image_base64 改断言为 PNG 魔数，接口5 三档叠图同。
208 lines
8.9 KiB
Python
208 lines
8.9 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"])[:8] == b"\x89PNG\r\n\x1a\n" # 透明 PNG（发际线曲线）
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assert base64.b64decode(results[0]["grown_image_base64"])[:3] == b"\xff\xd8\xff" # JPEG（生发图）
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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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# 三档叠图为透明 PNG（发际线曲线，含 alpha），生发图为 JPEG（完整人像）
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for k in ("image_middle_base64", "image_high_base64", "image_low_base64"):
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assert base64.b64decode(imgs[0][k])[:8] == b"\x89PNG\r\n\x1a\n", k
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assert base64.b64decode(imgs[0]["grown_image_base64"])[:3] == b"\xff\xd8\xff"
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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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# 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）
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fm = d["face_measure"]
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assert fm is not None, "face_measure 不应为 null（正常正面照）"
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assert set(["face_total_height_cm", "four_courts", "seven_eyes",
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"landmarks", "hairline_source", "head_pose"]).issubset(fm.keys())
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# 不应含标注图字段（接口5 只要数值，不要画线图）
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assert "annotated_image_base64" not in fm
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assert "annotated_image_url" not in fm
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# 子结构
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assert set(["top_court_cm", "upper_court_cm", "middle_court_cm",
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"lower_court_cm", "ratios"]).issubset(fm["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(fm["seven_eyes"].keys())
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# 七眼 eye1~eye7 键必须存在（eye1/eye7 在耳朵不可见时可为 null）
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assert set([f"eye{i}" for i in range(1, 8)]).issubset(fm["seven_eyes"].keys())
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assert set(["hair_top", "hairline", "brow_center",
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"nose_bottom", "chin_tip"]).issubset(fm["landmarks"].keys())
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assert fm["hairline_source"] in ("segmentation", "estimated")
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assert set(["yaw", "pitch", "roll"]).issubset(fm["head_pose"].keys())
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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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# 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）
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assert set([f"eye{i}" for i in range(1, 8)]).issubset(data["seven_eyes"].keys())
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# 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
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assert data["seven_eyes"]["eye3"] is not None
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assert data["seven_eyes"]["eye4"] is not None
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assert data["seven_eyes"]["eye5"] is not None
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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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