2026-05-18-17-40-02 构建导丝分割Web系统

tests/test_api.py

@@ -0,0 +1,35 @@
+from pathlib import Path
+
+from fastapi.testclient import TestClient
+
+from backend.main import app
+from scripts.generate_sample import make_frame
+
+import cv2
+
+
+client = TestClient(app)
+
+
+def test_health_and_methods():
+    health = client.get("/api/health")
+    assert health.status_code == 200
+    assert health.json()["status"] == "ok"
+    methods = client.get("/api/methods")
+    assert methods.status_code == 200
+    assert "fusion" in methods.json()["methods"]
+
+
+def test_segment_image(tmp_path: Path):
+    image_path = tmp_path / "sample.png"
+    cv2.imwrite(str(image_path), make_frame(8, 320, 220))
+    with image_path.open("rb") as handle:
+        response = client.post(
+            "/api/segment",
+            files={"file": ("sample.png", handle, "image/png")},
+            data={"method": "fusion", "sensitivity": "0.68"},
+        )
+    assert response.status_code == 200
+    payload = response.json()
+    assert payload["kind"] == "image"
+    assert payload["frames"][0]["metrics"]["mask_pixels"] > 0

tests/test_segmentation.py

@@ -0,0 +1,39 @@
+import cv2
+import numpy as np
+
+from backend.segmentation import compare_frame, segment_frame
+
+
+def synthetic_frame(shift: int = 0) -> np.ndarray:
+    frame = np.full((220, 320, 3), 158, dtype=np.uint8)
+    noise = np.random.default_rng(42 + shift).normal(0, 6, frame.shape[:2]).astype(np.int16)
+    gray = np.clip(frame[:, :, 0].astype(np.int16) + noise, 0, 255).astype(np.uint8)
+    frame = cv2.cvtColor(gray, cv2.COLOR_GRAY2BGR)
+    points = np.array([[28, 142 + shift], [92, 108 + shift], [174, 124 + shift], [286, 80 + shift]], dtype=np.int32)
+    cv2.polylines(frame, [points.reshape((-1, 1, 2))], False, (32, 32, 32), 2, cv2.LINE_AA)
+    return frame
+
+
+def assert_output(output):
+    assert output.mask.shape[:2] == (220, 320)
+    assert output.overlay.shape == (220, 320, 3)
+    assert output.metrics["mask_pixels"] > 0
+    assert 0 <= output.metrics["coverage"] <= 1
+
+
+def test_segmentation_methods_return_non_empty_masks():
+    previous = synthetic_frame(0)
+    current = synthetic_frame(2)
+    for method in ["hessian_ridge", "edge_morphology", "temporal_difference", "fusion"]:
+        assert_output(segment_frame(current, method=method, previous_frame=previous, sensitivity=0.7))
+
+
+def test_compare_frame_returns_all_methods():
+    outputs = compare_frame(synthetic_frame(1), synthetic_frame(0), sensitivity=0.65)
+    assert [item.method for item in outputs] == [
+        "hessian_ridge",
+        "edge_morphology",
+        "temporal_difference",
+        "fusion",
+    ]
+    assert all(item.metrics["mask_pixels"] > 0 for item in outputs)