feat: add features

fights-segmentation.py

@@ -49,9 +49,10 @@ class FightsSegmentation(datasets.GeneratorBasedBuilder):
                     "name": datasets.Value("string"),
                     "image": datasets.Image(),
                     "mask": datasets.Image(),
+                    "width": datasets.Value("uint16"),
+                    "height": datasets.Value("uint16"),
                     "shapes": datasets.Sequence(
                         {
-                            "track_id": datasets.Value("uint32"),
                             "label": datasets.ClassLabel(
                                 num_classes=len(_LABELS),
                                 names=_LABELS,
@@ -91,26 +92,9 @@ class FightsSegmentation(datasets.GeneratorBasedBuilder):
             ),
         ]
 
-    @staticmethod
-    def extract_shapes_from_tracks(
-        root: ET.Element, file: str, index: int
-    ) -> ET.Element:
-        img = ET.Element("image")
-        img.set("name", file)
-        img.set("id", str(index))
-        for track in root.iter("track"):
-            shape = track.find(f".//*[@frame='{index}']")
-            if not (shape is None):
-                shape.set("label", track.get("label"))
-                shape.set("track_id", track.get("id"))
-                img.append(shape)
-
-        return img
-
     @staticmethod
     def parse_shape(shape: ET.Element) -> dict:
         label = shape.get("label")
-        track_id = shape.get("track_id")
         shape_type = shape.tag
         rotation = shape.get("rotation", 0.0)
         occluded = shape.get("occluded", 0)
@@ -142,7 +126,6 @@ class FightsSegmentation(datasets.GeneratorBasedBuilder):
 
         shape_data = {
             "label": label,
-            "track_id": track_id,
             "type": shape_type,
             "points": points,
             "rotation": rotation,
@@ -158,10 +141,13 @@ class FightsSegmentation(datasets.GeneratorBasedBuilder):
         root = tree.getroot()
 
         for idx, file in enumerate(sorted(os.listdir(os.path.join(data, "images")))):
-            img = self.extract_shapes_from_tracks(root, file, idx)
+            image_name = file.split("/")[-1]
+            img = root.find(f"./image[@name='images/{image_name}']")
 
             image_id = img.get("id")
             name = img.get("name")
+            width = img.get("width")
+            height = img.get("height")
             shapes = [self.parse_shape(shape) for shape in img]
 
             yield idx, {
@@ -169,5 +155,7 @@ class FightsSegmentation(datasets.GeneratorBasedBuilder):
                 "name": name,
                 "image": os.path.join(data, "images", file),
                 "mask": os.path.join(data, "masks", file),
+                "width": width,
+                "height": height,
                 "shapes": shapes,
             }