[AZ-139] [AZ-140] [AZ-141] [AZ-142] Implement integration tests for health, single image, tiling, and async SSE

Made-with: Cursor

e2e/tests/test_single_image.py

@@ -1 +1,209 @@
-"""Synchronous POST /detect single-image scenarios (bounding boxes, config, class mapping)."""
+import json
+from pathlib import Path
+
+import pytest
+
+_DETECT_SLOW_TIMEOUT = 120
+_EPS = 1e-6
+_WEATHER_CLASS_STRIDE = 20
+
+
+def _jpeg_width_height(data):
+    if len(data) < 2 or data[0:2] != b"\xff\xd8":
+        return None
+    i = 2
+    while i + 1 < len(data):
+        if data[i] != 0xFF:
+            i += 1
+            continue
+        i += 1
+        while i < len(data) and data[i] == 0xFF:
+            i += 1
+        if i >= len(data):
+            break
+        m = data[i]
+        i += 1
+        if m in (0xD8, 0xD9):
+            continue
+        if i + 3 > len(data):
+            break
+        seg_len = (data[i] << 8) | data[i + 1]
+        i += 2
+        if m in (0xC0, 0xC1, 0xC2, 0xC3, 0xC5, 0xC6, 0xC7):
+            if i + 5 > len(data):
+                return None
+            h = (data[i + 1] << 8) | data[i + 2]
+            w = (data[i + 3] << 8) | data[i + 4]
+            return w, h
+        i += max(0, seg_len - 2)
+    return None
+
+
+def _overlap_to_min_area_ratio(a, b):
+    ox = 0.5 * (a["width"] + b["width"]) - abs(a["centerX"] - b["centerX"])
+    oy = 0.5 * (a["height"] + b["height"]) - abs(a["centerY"] - b["centerY"])
+    overlap_area = max(0.0, ox) * max(0.0, oy)
+    aa = a["width"] * a["height"]
+    ab = b["width"] * b["height"]
+    m = min(aa, ab)
+    if m <= 0:
+        return 0.0
+    return overlap_area / m
+
+
+def _load_classes_media():
+    p = Path("/media/classes.json")
+    if not p.is_file():
+        pytest.skip(f"missing {p}")
+    raw = json.loads(p.read_text())
+    by_id = {}
+    names = []
+    for row in raw:
+        cid = row["Id"]
+        by_id[cid] = float(row["MaxSizeM"])
+        names.append(row["Name"])
+    return by_id, names
+
+
+def _weather_label_ok(label, base_names):
+    for n in base_names:
+        if label == n:
+            return True
+        if label == n + "(Wint)" or label == n + "(Night)":
+            return True
+    return False
+
+
+@pytest.mark.slow
+def test_ft_p_03_detection_response_structure_ac1(http_client, image_small, warm_engine):
+    r = http_client.post(
+        "/detect",
+        files={"file": ("img.jpg", image_small, "image/jpeg")},
+    )
+    assert r.status_code == 200
+    body = r.json()
+    assert isinstance(body, list)
+    for d in body:
+        assert isinstance(d["centerX"], (int, float))
+        assert isinstance(d["centerY"], (int, float))
+        assert isinstance(d["width"], (int, float))
+        assert isinstance(d["height"], (int, float))
+        assert 0.0 <= float(d["centerX"]) <= 1.0
+        assert 0.0 <= float(d["centerY"]) <= 1.0
+        assert 0.0 <= float(d["width"]) <= 1.0
+        assert 0.0 <= float(d["height"]) <= 1.0
+        assert isinstance(d["classNum"], int)
+        assert isinstance(d["label"], str)
+        assert isinstance(d["confidence"], (int, float))
+        assert 0.0 <= float(d["confidence"]) <= 1.0
+
+
+@pytest.mark.slow
+def test_ft_p_05_confidence_filtering_ac2(http_client, image_small, warm_engine):
+    cfg_hi = json.dumps({"probability_threshold": 0.8})
+    r_hi = http_client.post(
+        "/detect",
+        files={"file": ("img.jpg", image_small, "image/jpeg")},
+        data={"config": cfg_hi},
+    )
+    assert r_hi.status_code == 200
+    hi = r_hi.json()
+    assert isinstance(hi, list)
+    for d in hi:
+        assert float(d["confidence"]) + _EPS >= 0.8
+    cfg_lo = json.dumps({"probability_threshold": 0.1})
+    r_lo = http_client.post(
+        "/detect",
+        files={"file": ("img.jpg", image_small, "image/jpeg")},
+        data={"config": cfg_lo},
+    )
+    assert r_lo.status_code == 200
+    lo = r_lo.json()
+    assert isinstance(lo, list)
+    assert len(lo) >= len(hi)
+
+
+@pytest.mark.slow
+def test_ft_p_06_overlap_deduplication_ac3(http_client, image_dense, warm_engine):
+    cfg_loose = json.dumps({"tracking_intersection_threshold": 0.6})
+    r1 = http_client.post(
+        "/detect",
+        files={"file": ("img.jpg", image_dense, "image/jpeg")},
+        data={"config": cfg_loose},
+        timeout=_DETECT_SLOW_TIMEOUT,
+    )
+    assert r1.status_code == 200
+    dets = r1.json()
+    assert isinstance(dets, list)
+    by_label = {}
+    for d in dets:
+        by_label.setdefault(d["label"], []).append(d)
+    for label, group in by_label.items():
+        for i in range(len(group)):
+            for j in range(i + 1, len(group)):
+                ratio = _overlap_to_min_area_ratio(group[i], group[j])
+                assert ratio <= 0.6 + _EPS, (label, ratio)
+    cfg_strict = json.dumps({"tracking_intersection_threshold": 0.01})
+    r2 = http_client.post(
+        "/detect",
+        files={"file": ("img.jpg", image_dense, "image/jpeg")},
+        data={"config": cfg_strict},
+        timeout=_DETECT_SLOW_TIMEOUT,
+    )
+    assert r2.status_code == 200
+    strict = r2.json()
+    assert isinstance(strict, list)
+    assert len(strict) <= len(dets)
+
+
+@pytest.mark.slow
+def test_ft_p_07_physical_size_filtering_ac4(http_client, image_small, warm_engine):
+    by_id, _ = _load_classes_media()
+    wh = _jpeg_width_height(image_small)
+    assert wh is not None
+    image_width_px, _ = wh
+    altitude = 400.0
+    focal_length = 24.0
+    sensor_width = 23.5
+    gsd = (sensor_width * altitude) / (focal_length * image_width_px)
+    cfg = json.dumps(
+        {
+            "altitude": altitude,
+            "focal_length": focal_length,
+            "sensor_width": sensor_width,
+        }
+    )
+    r = http_client.post(
+        "/detect",
+        files={"file": ("img.jpg", image_small, "image/jpeg")},
+        data={"config": cfg},
+        timeout=_DETECT_SLOW_TIMEOUT,
+    )
+    assert r.status_code == 200
+    body = r.json()
+    assert isinstance(body, list)
+    for d in body:
+        base_id = d["classNum"] % _WEATHER_CLASS_STRIDE
+        assert base_id in by_id
+        physical_width = float(d["width"]) * image_width_px * gsd
+        assert physical_width <= by_id[base_id] + _EPS
+
+
+@pytest.mark.slow
+def test_ft_p_13_weather_mode_class_variants_ac5(
+    http_client, image_different_types, warm_engine
+):
+    _, base_names = _load_classes_media()
+    r = http_client.post(
+        "/detect",
+        files={"file": ("img.jpg", image_different_types, "image/jpeg")},
+        timeout=_DETECT_SLOW_TIMEOUT,
+    )
+    assert r.status_code == 200
+    body = r.json()
+    assert isinstance(body, list)
+    for d in body:
+        label = d["label"]
+        assert isinstance(label, str)
+        assert len(label) > 0
+        assert _weather_label_ok(label, base_names)