Make guggenheim-bilbao.jpg the only sample image

AGENTS.md

@@ -84,6 +84,11 @@
 - `/docs/testing.md` documents test tiers, CI expectations, smoke tests, nightly
   tests, and manual validation policy.
 - `/docs/adr/` documents architecture decisions and design contracts.
+- The only showcase/sample image is `libreyolo/assets/guggenheim-bilbao.jpg`
+  (`libreyolo.SAMPLE_IMAGE`). Never use or reintroduce `parkour.jpg` in
+  user-facing material. A test-only copy lives in `tests/data/parkour.jpg`
+  for parity and golden tests; `tests/unit/test_no_parkour_sample.py`
+  enforces this.
 
 ## README policy
 

libreyolo/__init__.py

@@ -140,7 +140,7 @@
     "Identities",
 )
 
-SAMPLE_IMAGE = str(_Path(__file__).parent / "assets" / "parkour.jpg")
+SAMPLE_IMAGE = str(_Path(__file__).parent / "assets" / "guggenheim-bilbao.jpg")
 
 try:
     __version__ = version("libreyolo")

libreyolo/cli/commands/predict.py

@@ -747,7 +747,7 @@ def predict_cmd(
             }
         result_list.append(result_data)
         # Human summary line:
-        # image 1/3 parkour.jpg: 640x480 3 persons, 2 skateboards, 45.2ms
+        # image 1/1 guggenheim-bilbao.jpg: 1536x1194 1 person, 59.5ms avg
         counts_str = ", ".join(
             f"{v} {k}{'s' if v > 1 else ''}" for k, v in class_counts.items()
         )

scripts/run_sample_predict.py

@@ -10,7 +10,7 @@
 from pathlib import Path
 
 SAMPLE_IMAGES = {
-    "parkour": Path(__file__).resolve().parents[1] / "libreyolo" / "assets" / "parkour.jpg",
+    "guggenheim-bilbao": Path(__file__).resolve().parents[1] / "libreyolo" / "assets" / "guggenheim-bilbao.jpg",
 }
 
 

tests/data/rfdetr_keypoint_parkour_golden.json

@@ -1,6 +1,6 @@
 {
- "description": "RF-DETR GroupPose keypoint oracle golden for libreyolo/assets/parkour.jpg (852x1280 HxW). Generated from official_kp_parity.pt blob[final]. conf=0.3, 4 person detections. boxes xyxy and kp_xy in source-image pixels; kp_confidence is findable.sigmoid().",
- "source_image": "libreyolo/assets/parkour.jpg",
+ "description": "RF-DETR GroupPose keypoint oracle golden for tests/data/parkour.jpg (852x1280 HxW). Generated from official_kp_parity.pt blob[final]. conf=0.3, 4 person detections. boxes xyxy and kp_xy in source-image pixels; kp_confidence is findable.sigmoid().",
+ "source_image": "tests/data/parkour.jpg",
  "source_shape_hw": [
   852,
   1280

tests/e2e/cli/test_cli.py

@@ -178,7 +178,7 @@ def app(self):
 
     def test_predict_basic(self, app):
         result = runner.invoke(
-            app, ["predict", "source=libreyolo/assets/parkour.jpg", "model=yolox-s"]
+            app, ["predict", "source=tests/data/parkour.jpg", "model=yolox-s"]
         )
         assert result.exit_code == 0
         assert "person" in result.output
@@ -188,7 +188,7 @@ def test_predict_json(self, app):
             app,
             [
                 "predict",
-                "source=libreyolo/assets/parkour.jpg",
+                "source=tests/data/parkour.jpg",
                 "model=yolox-s",
                 "--json",
             ],
@@ -205,7 +205,7 @@ def test_predict_with_conf(self, app):
             app,
             [
                 "predict",
-                "source=libreyolo/assets/parkour.jpg",
+                "source=tests/data/parkour.jpg",
                 "model=yolox-s",
                 "conf=0.9",
                 "--json",
@@ -222,7 +222,7 @@ def test_predict_key_value_syntax(self, app):
             app,
             [
                 "predict",
-                "source=libreyolo/assets/parkour.jpg",
+                "source=tests/data/parkour.jpg",
                 "model=yolox-s",
                 "conf=0.5",
             ],
@@ -237,7 +237,7 @@ def test_predict_standard_syntax(self, app):
             [
                 "predict",
                 "--source",
-                "libreyolo/assets/parkour.jpg",
+                "tests/data/parkour.jpg",
                 "--model",
                 "yolox-s",
                 "--conf",
@@ -253,7 +253,7 @@ def test_predict_mixed_syntax(self, app):
             app,
             [
                 "predict",
-                "source=libreyolo/assets/parkour.jpg",
+                "source=tests/data/parkour.jpg",
                 "--model",
                 "yolox-s",
                 "conf=0.5",
@@ -270,7 +270,7 @@ def test_predict_bare_bool_flags(self, app):
             app,
             [
                 "predict",
-                "source=libreyolo/assets/parkour.jpg",
+                "source=tests/data/parkour.jpg",
                 "model=yolox-s",
                 "half",
                 "save",
@@ -287,7 +287,7 @@ def test_predict_save(self, app):
             app,
             [
                 "predict",
-                "source=libreyolo/assets/parkour.jpg",
+                "source=tests/data/parkour.jpg",
                 "model=yolox-s",
                 "save",
                 "--json",
@@ -303,7 +303,7 @@ def test_predict_local_weights(self, app):
             app,
             [
                 "predict",
-                "source=libreyolo/assets/parkour.jpg",
+                "source=tests/data/parkour.jpg",
                 "model=weights/LibreYOLOXs.pt",
                 "--json",
             ],
@@ -320,7 +320,7 @@ def test_predict_reports_effective_imgsz(self, app):
             app,
             [
                 "predict",
-                "source=libreyolo/assets/parkour.jpg",
+                "source=tests/data/parkour.jpg",
                 "model=weights/LibreYOLOXs.pt",
                 "imgsz=320",
                 "--json",
@@ -367,7 +367,7 @@ def test_detect_task_prefix(self, app, monkeypatch):
                 "libreyolo",
                 "detect",
                 "predict",
-                "source=libreyolo/assets/parkour.jpg",
+                "source=tests/data/parkour.jpg",
                 "model=yolox-s",
                 "--json",
             ],
@@ -505,7 +505,7 @@ def test_predict_yolo9(self, app):
             app,
             [
                 "predict",
-                "source=libreyolo/assets/parkour.jpg",
+                "source=tests/data/parkour.jpg",
                 "model=yolo9-t",
                 "--json",
             ],
@@ -525,7 +525,7 @@ def test_predict_rfdetr(self, app):
             app,
             [
                 "predict",
-                "source=libreyolo/assets/parkour.jpg",
+                "source=tests/data/parkour.jpg",
                 "model=rfdetr-n",
                 "--json",
             ],

tests/e2e/conftest.py

@@ -409,6 +409,14 @@ def sample_image():
     return SAMPLE_IMAGE
 
 
+@pytest.fixture(scope="session")
+def parkour_fixture_image():
+    """Test-only parity image whose exact pixels some numeric checks rely on."""
+    from tests.fixture_images import PARKOUR_FIXTURE
+
+    return PARKOUR_FIXTURE
+
+
 @pytest.fixture(scope="function")
 def temp_export_dir(tmp_path):
     """Create a temporary directory for export artifacts."""

tests/e2e/test_deeplabv3_exports.py

@@ -75,7 +75,7 @@ def test_official_checkpoint_export_runtime_parity(tmp_path, size, format_name):
 
     device = "cuda" if format_name == "tensorrt" else "cpu"
     native = LibreYOLO(str(checkpoint), device=device)
-    image = Path("libreyolo/assets/parkour.jpg")
+    image = Path("tests/data/parkour.jpg")
     input_tensor, _, _, _ = native._preprocess(image, input_size=520)
     with torch.inference_mode():
         expected_raw = native.model(input_tensor.to(device)).detach().cpu().numpy()

tests/e2e/test_deformable_detr_onnx.py

@@ -127,7 +127,7 @@ def test_official_checkpoint_onnx_predict_parity(
     model.model.eval()
     del state_dict
 
-    image = Path("libreyolo/assets/parkour.jpg")
+    image = Path("tests/data/parkour.jpg")
     input_tensor, _, _, _ = model._preprocess(image, input_size=800)
     trace_device = "cpu" if size == "r50twostage" else device
     trace_tensor = input_tensor.to(trace_device)

tests/e2e/test_dekr_pose.py

@@ -23,7 +23,7 @@
 pytestmark = [pytest.mark.e2e, pytest.mark.dekr]
 
 REPO_ROOT = Path(__file__).resolve().parents[2]
-IMAGE = REPO_ROOT / "libreyolo" / "assets" / "parkour.jpg"
+IMAGE = REPO_ROOT / "tests" / "data" / "parkour.jpg"
 FAMILY, SIZE, WEIGHTS = DEKR_POSE_MODELS[0]
 
 

tests/e2e/test_dinodetr_onnx.py

@@ -128,7 +128,7 @@ def test_official_checkpoint_onnx_predict_parity(
     # lowering this CUDA graph. CPU traces the same operators and is portable.
     device = "cpu"
     model = LibreDINODETR(str(source), size=size, device=device)
-    image = Path("libreyolo/assets/parkour.jpg")
+    image = Path("tests/data/parkour.jpg")
     input_tensor, _, _, _ = model._preprocess(image, input_size=export_size)
     exporter = OnnxExporter(model)
     with (

tests/e2e/test_embed_smoke.py

@@ -23,7 +23,7 @@ def test_clip_embed_text_gallery_and_batch_smoke(tmp_path):
     result = model.predict(SAMPLE_IMAGE)
     image_vector = result.embeddings.data
     text_vectors = model.embed_text(
-        ["people doing parkour outdoors", "a close-up photograph of a dog"]
+        ["a person doing a flip in front of a museum", "a close-up photograph of a dog"]
     )
 
     assert result.boxes is None
@@ -43,7 +43,7 @@ def test_clip_embed_text_gallery_and_batch_smoke(tmp_path):
     assert "embedding" in result.summary(embeddings=True)[0]
 
     gallery = Gallery(model)
-    assert gallery.enroll("parkour", SAMPLE_IMAGE) == 1
+    assert gallery.enroll("guggenheim", SAMPLE_IMAGE) == 1
     gallery_path = tmp_path / "images.gallery.npz"
     gallery.save(gallery_path)
     restored = Gallery.load(gallery_path, model=model)
@@ -53,4 +53,4 @@ def test_clip_embed_text_gallery_and_batch_smoke(tmp_path):
         gallery=restored,
         threshold=0.99,
     )
-    assert identified.identities.name == ["parkour"]
+    assert identified.identities.name == ["guggenheim"]

tests/e2e/test_matte_birefnet.py

@@ -19,7 +19,7 @@
 
 REPO = Path(__file__).resolve().parents[2]
 FIXT = REPO / "tests" / "fixtures" / "matte8"
-_SAMPLE = REPO / "libreyolo" / "assets" / "parkour.jpg"
+_SAMPLE = REPO / "tests" / "data" / "parkour.jpg"
 _LOCAL_T = REPO / "weights" / "LibreBiRefNett-matte.pt"
 
 

tests/e2e/test_ncnn_round18.py

@@ -308,7 +308,7 @@ def _match_detection_rows(expected_data, actual_data):
 
 def _assert_predict_parity(case, model, backend) -> None:
     if case.weights is not None:
-        source = str(Path("libreyolo/assets/parkour.jpg"))
+        source = str(Path("tests/data/parkour.jpg"))
         confidence = 0.05
     else:
         source = np.random.default_rng(118).integers(

tests/e2e/test_ppyoloe_export.py

@@ -117,7 +117,7 @@ def _assert_public_parity(model, backend, image, box_atol, score_atol):
 
 
 @pytest.mark.torchscript
-def test_torchscript_is_bit_exact(tmp_path, sample_image):
+def test_torchscript_is_bit_exact(tmp_path, parkour_fixture_image):
     from libreyolo import LibreYOLO
 
     weights = require_test_weights(WEIGHTS, expected_family="ppyoloe")
@@ -129,12 +129,12 @@ def test_torchscript_is_bit_exact(tmp_path, sample_image):
     assert backend.task == "detect"
     assert backend.imgsz == IMGSZ
 
-    _assert_raw_parity(model, backend, sample_image, box_atol=0.0, score_atol=0.0)
-    _assert_public_parity(model, backend, sample_image, box_atol=0.0, score_atol=0.0)
+    _assert_raw_parity(model, backend, parkour_fixture_image, box_atol=0.0, score_atol=0.0)
+    _assert_public_parity(model, backend, parkour_fixture_image, box_atol=0.0, score_atol=0.0)
 
 
 @pytest.mark.onnx
-def test_onnx_raw_contract_and_parity(tmp_path, sample_image):
+def test_onnx_raw_contract_and_parity(tmp_path, parkour_fixture_image):
     import onnx
 
     from libreyolo import LibreYOLO
@@ -153,8 +153,8 @@ def test_onnx_raw_contract_and_parity(tmp_path, sample_image):
     assert backend.imgsz == IMGSZ
     assert backend.names[0] == "person"
 
-    _assert_raw_parity(model, backend, sample_image, box_atol=1e-2, score_atol=1e-5)
-    _assert_public_parity(model, backend, sample_image, box_atol=1e-2, score_atol=1e-5)
+    _assert_raw_parity(model, backend, parkour_fixture_image, box_atol=1e-2, score_atol=1e-5)
+    _assert_public_parity(model, backend, parkour_fixture_image, box_atol=1e-2, score_atol=1e-5)
 
 
 @pytest.mark.onnx
@@ -171,7 +171,7 @@ def test_onnx_rejects_a_shape_it_was_not_exported_for(tmp_path):
 
 
 @pytest.mark.openvino
-def test_openvino_parity(tmp_path, sample_image):
+def test_openvino_parity(tmp_path, parkour_fixture_image):
     pytest.importorskip("openvino")
     from libreyolo import LibreYOLO
 
@@ -181,12 +181,12 @@ def test_openvino_parity(tmp_path, sample_image):
     backend = LibreYOLO(str(artifact), device="cpu")
 
     assert backend.model_family == "ppyoloe"
-    _assert_raw_parity(model, backend, sample_image, box_atol=5.0, score_atol=1e-2)
-    _assert_public_parity(model, backend, sample_image, box_atol=0.5, score_atol=1e-3)
+    _assert_raw_parity(model, backend, parkour_fixture_image, box_atol=5.0, score_atol=1e-2)
+    _assert_public_parity(model, backend, parkour_fixture_image, box_atol=0.5, score_atol=1e-3)
 
 
 @pytest.mark.tensorrt
-def test_tensorrt_fp32_engine_parity(tmp_path, sample_image):
+def test_tensorrt_fp32_engine_parity(tmp_path, parkour_fixture_image):
     """Build and run a real engine; an ONNX parse alone is not TensorRT support.
 
     Fixed batch 1 on purpose. An engine built with a dynamic batch profile
@@ -207,7 +207,7 @@ def test_tensorrt_fp32_engine_parity(tmp_path, sample_image):
 
     assert backend.model_family == "ppyoloe"
     _assert_raw_parity(
-        model, backend, sample_image, box_atol=2.0, score_atol=1e-2, batches=(1,)
+        model, backend, parkour_fixture_image, box_atol=2.0, score_atol=1e-2, batches=(1,)
     )
-    _assert_public_parity(model, backend, sample_image, box_atol=0.5, score_atol=1e-2)
+    _assert_public_parity(model, backend, parkour_fixture_image, box_atol=0.5, score_atol=1e-2)
 

tests/e2e/test_rfdetr_keypoint_parity.py

@@ -31,7 +31,7 @@
 
 _REPO_ROOT = Path(__file__).resolve().parents[2]
 _GOLDEN = _REPO_ROOT / "tests" / "data" / "rfdetr_keypoint_parkour_golden.json"
-_PARKOUR = _REPO_ROOT / "libreyolo" / "assets" / "parkour.jpg"
+_PARKOUR = _REPO_ROOT / "tests" / "data" / "parkour.jpg"
 _DEFAULT_CKPT = _REPO_ROOT / "downloads" / "LibreRFDETRx-pose.pt"
 
 # Tolerances. The oracle and LibreYOLO run the same weights, so agreement is

tests/fixture_images.py

@@ -0,0 +1,11 @@
+"""Test-only image fixtures.
+
+``PARKOUR_FIXTURE`` is a frozen copy of the old sample photo, kept only for
+parity and golden tests whose expected numbers depend on its exact pixels.
+It is not shipped in the wheel and must never appear in user-facing material;
+the sample image is ``libreyolo.SAMPLE_IMAGE`` (the Guggenheim Bilbao photo).
+"""
+
+from pathlib import Path
+
+PARKOUR_FIXTURE = str(Path(__file__).resolve().parent / "data" / "parkour.jpg")

tests/fixtures/matte8/generate_images.py

@@ -3,7 +3,7 @@
 These procedural images are trivially redistributable (no third-party image
 rights) and their sharp edges, gradients, and thin protrusions exercise the
 resize/normalize + soft-edge behaviour a background-removal model must handle.
-One real photo (the in-repo ``parkour.jpg``, a person) is copied in for a
+One real photo (the test-only ``tests/data/parkour.jpg``, a person) is copied in for a
 natural-image check. Run once to (re)generate ``images/``.
 """