fixtracks/widgets/classifier.py

@@ -1,134 +0,0 @@
-import logging
-import numpy as np
-
-from PySide6.QtWidgets import QWidget, QVBoxLayout, QTabWidget,QPushButton
-from PySide6.QtCore import Signal
-from PySide6.QtGui import QBrush, QColor
-
-import pyqtgraph as pg
-
-
-class SizeClassifier(QWidget):
-    apply = Signal()
-
-    def __init__(self, parent=None):
-        super().__init__(parent)
-        self._t1_selection = None
-        self._t2_selection = None
-        self._coordinates = None
-        self._sizes = None
-
-        self._plot_widget = self.setupGraph()
-        self._apply_btn = QPushButton("apply")
-        self._apply_btn.clicked.connect(lambda: self.apply.emit())
-
-        layout = QVBoxLayout()
-        layout.addWidget(self._plot_widget)
-        layout.addWidget(self._apply_btn)
-        self.setLayout(layout)
-
-    def setupGraph(self):
-        track1_brush = QBrush(QColor.fromString("orange"))
-        track1_brush.color().setAlphaF(0.5)
-        track2_brush = QBrush(QColor.fromString("green"))
-
-        pg.setConfigOptions(antialias=True)
-        plot_widget = pg.GraphicsLayoutWidget(show=False)
-
-        self._t1_selection = pg.LinearRegionItem([100, 200])
-        self._t1_selection.setZValue(-10)  # what is that?
-        self._t1_selection.setBrush(track1_brush)
-        self._t2_selection = pg.LinearRegionItem([300,400])
-        self._t2_selection.setZValue(-10)  # what is that?
-        self._t2_selection.setBrush(track2_brush)
-        return plot_widget
-
-    def estimate_length(self, coords, bodyaxis =None):
-        if bodyaxis is None:
-            bodyaxis = [0, 1, 2, 5]
-        bodycoords = coords[:, bodyaxis, :]
-        dists = np.sum(np.sqrt(np.sum(np.diff(bodycoords, axis=1)**2, axis=2)), axis=1)
-        return dists
-
-    def estimate_histogram(self, dists, min_threshold=1., max_threshold=99.):
-        min_length = np.percentile(dists, min_threshold)
-        max_length = np.percentile(dists, max_threshold)
-        bins = np.linspace(0.5 * min_length, 1.5 * max_length, 100)
-        hist, edges = np.histogram(dists, bins=bins, density=True)
-        return hist, edges
-
-    def setCoordinates(self, coordinates):
-        self._coordinates = coordinates
-        self._sizes = self.estimate_length(coordinates)
-        n, e = self.estimate_histogram(self._sizes)
-        plot = self._plot_widget.addPlot()
-        bgi = pg.BarGraphItem(x0=e[:-1], x1=e[1:], height=n, pen='w', brush=(0,0,255,150))
-        plot.addItem(bgi)
-        plot.setLabel('left', "prob. density")
-        plot.setLabel('bottom', "bodylength", units="px")
-        plot.addItem(self._t1_selection)
-        plot.addItem(self._t2_selection)
-
-    def selections(self, track1=True):
-        if track1:
-            return self._t1_selection.getRegion()
-        else:
-            return self._t2_selection.getRegion()
-
-    def assignedTracks(self):
-        tracks = np.ones_like(self._sizes, dtype=int) * -1
-        t1lower, t1upper = self.selections()
-        t2lower, t2upper = self.selections(False)
-        tracks[(self._sizes >= t1lower) & (self._sizes < t1upper)] = 1
-        tracks[(self._sizes >= t2lower) & (self._sizes < t2upper)] = 2
-        return tracks
-
-
-class ClassifierWidget(QTabWidget):
-    apply_sizeclassifier = Signal(np.ndarray)
-
-    def __init__(self, parent=None):
-        super().__init__(parent)
-        self._size_classifier = SizeClassifier()
-        self.addTab(self._size_classifier, "Size classifier")
-        self._size_classifier.apply.connect(self._on_applySizeClassifier)
-
-    def _on_applySizeClassifier(self):
-        tracks = self.size_classifier.assignedTracks()
-        self.apply_sizeclassifier.emit(tracks)
-
-    @property
-    def size_classifier(self):
-        return self._size_classifier
-
-
-def main():
-    import pickle
-    from fixtracks.info import PACKAGE_ROOT
-    from PySide6.QtWidgets import QApplication
-
-    datafile = PACKAGE_ROOT / "data/merged_small.pkl"
-    print(datafile)
-    with open(datafile, "rb") as f:
-        df = pickle.load(f)
-
-    coords = np.stack(df.keypoints.values,).astype(np.float32)[:,:,:]
-
-    app = QApplication([])
-    window = QWidget()
-    window.setMinimumSize(200, 200)
-    layout = QVBoxLayout()
-    win = SizeClassifier()
-    win.setCoordinates(coords)
-
-    btn = QPushButton("get bounds")
-    btn.clicked.connect(lambda: win.selections())
-
-    layout.addWidget(win)
-    layout.addWidget(btn)
-    window.setLayout(layout)
-    window.show()
-    app.exec()
-
-if __name__ == "__main__":
-    main()

fixtracks/widgets/skeleton.py

@@ -10,11 +10,9 @@ from fixtracks.widgets.detectionview import DetectionData
 
 class Skeleton(QGraphicsRectItem):
     skeleton_grid = [(0, 1), (1, 2), (1, 3), (1, 4), (2, 5)]
-    bodyaxis = [0, 1, 2, 5]
 
     def __init__(self, x, y, width, height, keypoint_coordinates, brush):
         super().__init__(x, y, width, height)
-        self._keypoints = keypoint_coordinates
         skeleton_pen = QPen(brush.color())
         skeleton_pen.setWidthF(1.0)
         skeleton_marker = 5
@@ -39,12 +37,6 @@ class Skeleton(QGraphicsRectItem):
         # self.setAcceptHoverEvents(True)  # Enable hover events if needed
         self.setFlags(QGraphicsRectItem.ItemIsSelectable)
 
-    @property
-    def length(self):
-        bodykps = self._keypoints[self.bodyaxis, :]
-        dist = np.sum(np.sqrt(np.sum(np.diff(bodykps, axis=0)**2, axis=1)), axis=0)
-        return dist
-
     # def mousePressEvent(self, event):
     #     self.signals.clicked.emit(self.data(0), QPointF(event.scenePos().x(), event.scenePos().y()))
 
@@ -90,11 +82,7 @@ class SkeletonWidget(QWidget):
     def updateInfo(self, index):
         if index > -1:
             s = self._skeletons[index]
-            l = s.length
+            self._info_label.setText(f"Detection id {s.data(DetectionData.ID.value)}, track {s.data(DetectionData.TRACK_ID.value)} on frame {s.data(DetectionData.FRAME.value)}")
-            i = s.data(DetectionData.ID.value)
-            t = s.data(DetectionData.TRACK_ID.value)
-            f = s.data(DetectionData.FRAME.value)
-            self._info_label.setText(f"Id {i}, track {t} on frame {f}, length {l:.1f} px")
         else:
             self._info_label.setText("")
 
@@ -131,8 +119,6 @@ class SkeletonWidget(QWidget):
 
     def addSkeleton(self, coords, detection_id, frame, track, brush, update=True):
         def check_extent(x, y, w, h):
-            if x == 0 and y == 0:
-                return
             if len(self._skeletons) == 0:
                 self._minx = x
                 self._maxx = x + w
@@ -200,9 +186,14 @@ def main():
         df = pickle.load(f)
 
     focus_brush = QBrush(QColor.fromString("red"))
+    second_brush = QBrush(QColor.fromString("blue"))
+
+    scnd_coords = np.stack(df.keypoints[(df.track == 2)].values,).astype(np.float32)[:,:,:]
+    scnd_tracks = df.track[df.track == 2].values
+    scnd_ids = df.track[(df.track == 2)].index.values
+
     focus_coords = np.stack(df.keypoints[df.track == 1].values,).astype(np.float32)[:,:,:]
     focus_tracks = df.track[df.track == 1].values
-    focus_frames = df.track[df.track == 1].values
     focus_ids = df.track[(df.track == 2)].index.values
 
     app = QApplication([])
@@ -218,8 +209,7 @@ def main():
     layout.addWidget(btn)
     # view.addSkeleton(focus_coords[10,:,:], focus_ids[10], focus_brush)
     count = 100
-    view.addSkeletons(focus_coords[:count,:,:], focus_ids[:count],
+    view.addSkeletons(focus_coords[:count,:,:], focus_ids[:count], focus_brush)
-                      focus_frames[:count], focus_tracks[:count], focus_brush)
     # view.addSkeletons(scnd_coords[:count,:,:], scnd_ids[:count], second_brush)
 
     # view.addSkeletons(focus_coords[:10,:,:], focus_ids[:10], focus_brush)

fixtracks/widgets/tracks.py

@@ -14,8 +14,6 @@ from fixtracks.utils.writer import PickleWriter
 from fixtracks.widgets.detectionview import DetectionView, DetectionData
 from fixtracks.widgets.detectiontimeline import DetectionTimeline
 from fixtracks.widgets.skeleton import SkeletonWidget
-from fixtracks.widgets.classifier import ClassifierWidget
-
 
 class PoseTableModel(QAbstractTableModel):
     column_header = ["frame", "track"]
@@ -261,10 +259,6 @@ class DataController(QObject):
             logging.error("Column %s not in dictionary", col)
             return np.nan
 
-    @property
-    def numDetections(self):
-        return self._data["track"].shape[0]
-
     @property
     def selectionRange(self):
         return self._start, self._stop
@@ -292,12 +286,6 @@ class DataController(QObject):
     def assignUserSelection(self, track_id):
         self._data["track"][self._user_selections] = track_id
 
-    def assignTracks(self, tracks):
-        if len(tracks) != self.numDetections:
-            logging.error("DataController: Size of passed tracks does not match data!")
-            return
-        self._data["track"] = tracks
-
     def save(self, filename):
         export_columns = self._columns.copy()
         export_columns.remove("index")
@@ -311,8 +299,6 @@ class DataController(QObject):
             return 0
         return self._data["keypoints"][0].shape[0]
 
-    def coordinates(self):
-        return  np.stack(self._data["keypoints"]).astype(np.float32)
 
 class FixTracks(QWidget):
     back = Signal()
@@ -405,13 +391,9 @@ class FixTracks(QWidget):
         btnBox.addWidget(self._progress_bar)
         btnBox.addWidget(self._saveBtn)
 
-        self._classifier = ClassifierWidget()
-        self._classifier.apply_sizeclassifier.connect(self.on_classifyBySize)
-        self._classifier.setMaximumWidth(500)
         cntrlBox = QHBoxLayout()
-        cntrlBox.addWidget(self._classifier)
+        cntrlBox.addItem(QSpacerItem(200, 100, QSizePolicy.Policy.Fixed, QSizePolicy.Policy.Expanding))
         cntrlBox.addWidget(self._controls_widget, alignment=Qt.AlignmentFlag.AlignCenter)
-        cntrlBox.addItem(QSpacerItem(300, 100, QSizePolicy.Policy.Fixed, QSizePolicy.Policy.Expanding))
 
         vbox = QVBoxLayout()
         vbox.addLayout(timelinebox)
@@ -430,12 +412,6 @@ class FixTracks(QWidget):
         layout.addWidget(splitter)
         self.setLayout(layout)
 
-    def on_classifyBySize(self, tracks):
-        self._data.setSelectionRange("index", 0, self._data.numDetections)
-        self._data.assignTracks(tracks)
-        self._timeline.setDetectionData(self._data.data)
-        self.update()
-
     def on_dataSelection(self):
         filename = self._data_combo.currentText()
         if "please select" in filename.lower() or len(filename.strip()) == 0:
@@ -533,8 +509,6 @@ class FixTracks(QWidget):
             maxframes = self._data.max("frame")
             rel_width = self._windowspinner.value() / maxframes
             self._timeline.setWindowWidth(rel_width)
-            coordinates = self._data.coordinates()
-            self._classifier.size_classifier.setCoordinates(coordinates)
             self.update()
             self._saveBtn.setEnabled(True)