feat: extract opengait_studio monorepo module

Move demo implementation into opengait_studio, retire Sports2D runtime integration, and align packaging with root-level monorepo dependency management.

tests/opengait_studio/test_visualizer.py

@@ -0,0 +1,171 @@
+from __future__ import annotations
+
+from pathlib import Path
+from typing import cast
+from unittest import mock
+
+import numpy as np
+import pytest
+
+from opengait_studio.input import create_source
+from opengait_studio.visualizer import (
+    DISPLAY_HEIGHT,
+    DISPLAY_WIDTH,
+    ImageArray,
+    OpenCVVisualizer,
+)
+from opengait_studio.window import select_person
+
+REPO_ROOT = Path(__file__).resolve().parents[2]
+SAMPLE_VIDEO_PATH = REPO_ROOT / "assets" / "sample.mp4"
+YOLO_MODEL_PATH = REPO_ROOT / "ckpt" / "yolo11n-seg.pt"
+
+
+def test_prepare_raw_view_float_mask_has_visible_signal() -> None:
+    viz = OpenCVVisualizer()
+
+    mask_float = np.zeros((64, 64), dtype=np.float32)
+    mask_float[16:48, 16:48] = 1.0
+
+    rendered = viz._prepare_raw_view(cast(ImageArray, mask_float))
+    assert rendered.dtype == np.uint8
+    assert rendered.shape == (256, 176, 3)
+
+    mask_zero = np.zeros((64, 64), dtype=np.float32)
+    rendered_zero = viz._prepare_raw_view(cast(ImageArray, mask_zero))
+
+    roi = slice(0, DISPLAY_HEIGHT - 40)
+    diff = np.abs(rendered[roi].astype(np.int16) - rendered_zero[roi].astype(np.int16))
+    assert int(np.count_nonzero(diff)) > 0
+
+
+def test_prepare_raw_view_handles_values_slightly_above_one() -> None:
+    viz = OpenCVVisualizer()
+
+    mask = np.zeros((64, 64), dtype=np.float32)
+    mask[20:40, 20:40] = 1.0001
+    rendered = viz._prepare_raw_view(cast(ImageArray, mask))
+
+    roi = rendered[: DISPLAY_HEIGHT - 40, :, 0]
+    assert int(np.count_nonzero(roi)) > 0
+
+
+def test_segmentation_view_is_normalized_only_shape() -> None:
+    viz = OpenCVVisualizer()
+    mask = np.zeros((480, 640), dtype=np.uint8)
+    sil = np.random.rand(64, 44).astype(np.float32)
+
+    seg = viz._prepare_segmentation_view(cast(ImageArray, mask), sil, (0, 0, 100, 100))
+    assert seg.shape == (DISPLAY_HEIGHT, DISPLAY_WIDTH, 3)
+
+
+def test_update_toggles_raw_window_with_r_key() -> None:
+    viz = OpenCVVisualizer()
+    frame = np.zeros((240, 320, 3), dtype=np.uint8)
+    mask = np.zeros((240, 320), dtype=np.uint8)
+    mask[20:100, 30:120] = 255
+    sil = np.random.rand(64, 44).astype(np.float32)
+    seg_input = np.random.rand(4, 64, 44).astype(np.float32)
+
+    with (
+        mock.patch("cv2.namedWindow") as named_window,
+        mock.patch("cv2.imshow"),
+        mock.patch("cv2.destroyWindow") as destroy_window,
+        mock.patch("cv2.waitKey", side_effect=[ord("r"), ord("r"), ord("q")]),
+    ):
+        assert viz.update(
+            frame,
+            (10, 10, 120, 150),
+            (10, 10, 120, 150),
+            1,
+            cast(ImageArray, mask),
+            sil,
+            seg_input,
+            None,
+            None,
+            15.0,
+        )
+        assert viz.show_raw_window is True
+        assert viz._raw_window_created is True
+
+        assert viz.update(
+            frame,
+            (10, 10, 120, 150),
+            (10, 10, 120, 150),
+            1,
+            cast(ImageArray, mask),
+            sil,
+            seg_input,
+            None,
+            None,
+            15.0,
+        )
+        assert viz.show_raw_window is False
+        assert viz._raw_window_created is False
+        assert destroy_window.called
+
+        assert (
+            viz.update(
+                frame,
+                (10, 10, 120, 150),
+                (10, 10, 120, 150),
+                1,
+                cast(ImageArray, mask),
+                sil,
+                seg_input,
+                None,
+                None,
+                15.0,
+            )
+            is False
+        )
+        assert named_window.called
+
+
+def test_sample_video_raw_mask_shape_range_and_render_signal() -> None:
+    if not SAMPLE_VIDEO_PATH.is_file():
+        pytest.skip(f"Missing sample video: {SAMPLE_VIDEO_PATH}")
+    if not YOLO_MODEL_PATH.is_file():
+        pytest.skip(f"Missing YOLO model file: {YOLO_MODEL_PATH}")
+
+    ultralytics = pytest.importorskip("ultralytics")
+    yolo_cls = getattr(ultralytics, "YOLO")
+
+    viz = OpenCVVisualizer()
+    detector = yolo_cls(str(YOLO_MODEL_PATH))
+
+    masks_seen = 0
+    rendered_nonzero: list[int] = []
+
+    for frame, _meta in create_source(str(SAMPLE_VIDEO_PATH), max_frames=30):
+        detections = detector.track(
+            frame,
+            persist=True,
+            verbose=False,
+            classes=[0],
+            device="cpu",
+        )
+        if not isinstance(detections, list) or not detections:
+            continue
+
+        selected = select_person(detections[0])
+        if selected is None:
+            continue
+
+        mask_raw, _, _, _ = selected
+        masks_seen += 1
+
+        arr = np.asarray(mask_raw)
+        assert arr.ndim == 2
+        assert arr.shape[0] > 0 and arr.shape[1] > 0
+        assert np.issubdtype(arr.dtype, np.number)
+        assert float(arr.min()) >= 0.0
+        assert float(arr.max()) <= 255.0
+        assert int(np.count_nonzero(arr)) > 0
+
+        rendered = viz._prepare_raw_view(arr)
+        roi = rendered[: DISPLAY_HEIGHT - 40, :, 0]
+        rendered_nonzero.append(int(np.count_nonzero(roi)))
+
+    assert masks_seen > 0
+    assert min(rendered_nonzero) > 0