fixing tests

Author: alexlib

src/openptv_python/correspondences.py

@@ -565,6 +565,33 @@ def py_correspondences(
     """
     num_cams = get_num_cams(cparam)
 
+    if should_use_native("correspondences") and HAS_NATIVE_CORRESPONDENCES and optv_correspondences is not None:
+        native_cals = [to_native_calibration(cal) for cal in calib]
+        native_vparam = to_native_volume_par(vparam)
+        native_cparam = to_native_control_par(cparam)
+        native_img_pts = [to_native_target_array(img_pts[cam]) for cam in range(num_cams)]
+        native_flat_coords = [
+            optv_correspondences.MatchedCoords(
+                native_img_pts[cam], native_cparam, native_cals[cam], 0.0001
+            )
+            for cam in range(num_cams)
+        ]
+
+        if num_cams == 1:
+            return optv_correspondences.single_cam_correspondence(
+                native_img_pts,
+                native_flat_coords,
+                native_cals,
+            )
+
+        return optv_correspondences.correspondences(
+            native_img_pts,
+            native_flat_coords,
+            native_cals,
+            native_vparam,
+            native_cparam,
+        )
+
     frm = Frame(num_cams, MAX_TARGETS)
 
     # Special case of a single camera, follow the single_cam_correspondence docstring

src/openptv_python/tracking_frame_buf.py

@@ -145,6 +145,9 @@ def __eq__(self, __value) -> bool:
 
 def sort_target_y(targets: List[Target]) -> List[Target]:
     """Sort targets by y coordinate."""
+    if hasattr(targets, "sort_y") and callable(getattr(targets, "sort_y", None)):
+        targets.sort_y()
+        return targets
     return sorted(targets, key=lambda t: _target_pos(t)[1])
 
 

src/pyptv/_backend.py

@@ -60,6 +60,8 @@ def _to_openptv_name(name: str) -> str:
     from optv.parameters import TargetParams
     from optv.parameters import TrackingParams
     from optv.parameters import VolumeParams
+    from optv.correspondences import MatchedCoords
+    from optv.correspondences import correspondences as py_correspondences
     from optv.epipolar import epipolar_curve
     from optv.image_processing import preprocess_image
     from optv.imgcoord import image_coordinates
@@ -77,6 +79,7 @@ def _to_openptv_name(name: str) -> str:
         convert_arr_metric_to_pixel,
         convert_arr_pixel_to_metric,
     )
+    correspondences = py_correspondences
 else:
     from openptv_python.calibration import Calibration
     from openptv_python.parameters import ControlPar as ControlParams
@@ -99,11 +102,11 @@ def _to_openptv_name(name: str) -> str:
     from openptv_python.track import Tracker, default_naming
     from openptv_python.trafo import arr_pixel_to_metric as convert_arr_pixel_to_metric
     from openptv_python.trafo import arr_metric_to_pixel as convert_arr_metric_to_pixel
-from openptv_python.correspondences import (
-    MatchedCoords,
-    py_correspondences,
-    correspondences,
-)
+    from openptv_python.correspondences import (
+        MatchedCoords,
+        py_correspondences,
+        correspondences,
+    )
 from openptv_python.tracking_frame_buf import sort_target_y
 from openptv_python.imgcoord import img_coord
 
@@ -236,6 +239,7 @@ def create_target_params(**kwargs) -> TargetParams:
     "Tracker",
     "MatchedCoords",
     "py_correspondences",
+    "correspondences",
     # Functions
     "preprocess_image",
     "target_recognition",

src/pyptv/ptv.py

@@ -591,10 +591,8 @@ def py_correspondences_proc_c(exp, frame=DEFAULT_FRAME_NUM):
     short_file_bases = exp.target_filenames
     print(f"short_file_bases: {short_file_bases}")
     _ensure_target_output_writable(short_file_bases)
-    native_detections = bool(exp.detections) and type(exp.detections[0]).__module__.startswith("optv.")
-    if not native_detections:
-        for i_cam in range(exp.num_cams):
-            write_targets(exp.detections[i_cam], short_file_bases[i_cam], frame)
+    for i_cam in range(exp.num_cams):
+        write_targets(exp.detections[i_cam], short_file_bases[i_cam], frame)
 
     print(
         f"Frame {frame} had {[s.shape[1] for s in sorted_pos]!r} correspondences."
@@ -832,12 +830,17 @@ def py_sequence_loop(exp) -> None:
         flat = np.array(
             [corr.get_by_pnrs(corresp) for corr, corresp in zip(corrected, sorted_corresp)]
         )
-        legacy_cals = [from_native_calibration(cal) for cal in exp.cals]
-        legacy_cpar = _to_python_cpar(exp.cpar)
-        legacy_vpar = _to_python_vpar(exp.vpar)
+        if should_use_native("orientation"):
+            legacy_cals = exp.cals
+            legacy_cpar = exp.cpar
+            legacy_vpar = exp.vpar
+        else:
+            legacy_cals = [from_native_calibration(cal) for cal in exp.cals]
+            legacy_cpar = _to_python_cpar(exp.cpar)
+            legacy_vpar = _to_python_vpar(exp.vpar)
         pos, _ = point_positions(
             flat.transpose(1, 0, 2),
-            get_multimedia_par(legacy_cpar),
+            legacy_cpar,
             legacy_cals,
             legacy_vpar,
         )
@@ -983,18 +986,25 @@ def _sum_grey_value(target):
                 return target.sum_grey_value()
             return target.sumg
 
-        with open(output_path, "w", encoding="utf-8") as file:
-            file.write(f"{num_targets}\n")
-            for target in target_list:
-                pnr = int(_value(getattr(target, "pnr")))
-                x, y = _pos(target)
-                n, nx, ny = _pixel_counts(target)
-                sumg = int(_sum_grey_value(target))
-                tnr = int(_value(getattr(target, "tnr")))
-                file.write(
-                    f"{pnr:4d} {float(x):9.4f} {float(y):9.4f} "
-                    f"{int(n):5d} {int(nx):5d} {int(ny):5d} {sumg:5d} {tnr:5d}\n"
+        target_arr = np.array(
+            [
+                (
+                    _value(getattr(target, "pnr")),
+                    *_pos(target),
+                    *_pixel_counts(target),
+                    _sum_grey_value(target),
+                    _value(getattr(target, "tnr")),
                 )
+                for target in target_list
+            ]
+        )
+        np.savetxt(
+            output_path,
+            target_arr,
+            fmt="%4d %9.4f %9.4f %5d %5d %5d %5d %5d",
+            header=f"{num_targets}",
+            comments="",
+        )
         success = True
     except OSError as exc:
         _raise_output_write_error(output_path, exc)