Update Stomatal_Images_Datasets.py

Stomatal_Images_Datasets.py

@@ -45,10 +45,14 @@ class NewDataset(datasets.GeneratorBasedBuilder):
             "annotations": datasets.Sequence({
                 "category_id": datasets.Value("int32"),
                 "bounding_box": {
-                    "x_min": datasets.Value("float32"),
-                    "y_min": datasets.Value("float32"),
-                    "x_max": datasets.Value("float32"),
-                    "y_max": datasets.Value("float32"),
+                    # "x_min": datasets.Value("float32"),
+                    # "y_min": datasets.Value("float32"),
+                    # "x_max": datasets.Value("float32"),
+                    # "y_max": datasets.Value("float32"),
+                    "x_center_rel": datasets.Value("float32"),
+                    "y_center_rel": datasets.Value("float32"),
+                    "width_rel": datasets.Value("float32"),
+                    "height_rel": datasets.Value("float32"),
                 },
             }),
         })
@@ -84,27 +88,44 @@ class NewDataset(datasets.GeneratorBasedBuilder):
         )]
     
 
-    def _parse_yolo_labels(self, label_path, width, height):
+    # def _parse_yolo_labels(self, label_path, width, height):
+    #     annotations = []
+    #     with open(label_path, 'r') as file:
+    #         yolo_data = file.readlines()
+    
+    #     for line in yolo_data:
+    #         class_id, x_center_rel, y_center_rel, width_rel, height_rel = map(float, line.split())
+    #         x_min = (x_center_rel - width_rel / 2) * width
+    #         y_min = (y_center_rel - height_rel / 2) * height
+    #         x_max = (x_center_rel + width_rel / 2) * width
+    #         y_max = (y_center_rel + height_rel / 2) * height
+    #         annotations.append({
+    #             "category_id": int(class_id),
+    #             "bounding_box": {
+    #                 "x_min": x_min,
+    #                 "y_min": y_min,
+    #                 "x_max": x_max,
+    #                 "y_max": y_max
+    #             }
+    #         })
+    #     return annotations
+
+    def _parse_yolo_labels(self, label_path):
         annotations = []
         with open(label_path, 'r') as file:
             yolo_data = file.readlines()
     
         for line in yolo_data:
             class_id, x_center_rel, y_center_rel, width_rel, height_rel = map(float, line.split())
-            x_min = (x_center_rel - width_rel / 2) * width
-            y_min = (y_center_rel - height_rel / 2) * height
-            x_max = (x_center_rel + width_rel / 2) * width
-            y_max = (y_center_rel + height_rel / 2) * height
             annotations.append({
                 "category_id": int(class_id),
-                "bounding_box": {
-                    "x_min": x_min,
-                    "y_min": y_min,
-                    "x_max": x_max,
-                    "y_max": y_max
-                }
+                "x_center_rel": x_center_rel,
+                "y_center_rel": y_center_rel,
+                "width_rel": width_rel,
+                "height_rel": height_rel,
             })
         return annotations
+
     
     def _generate_examples(self, filepaths, species_info, data_dir):
         """Yields examples as (key, example) tuples."""
@@ -130,7 +151,7 @@ class NewDataset(datasets.GeneratorBasedBuilder):
                 width = 1024 
                 height = 768   
             
-            annotations = self._parse_yolo_labels(label_path, width, height)
+            annotations = self._parse_yolo_labels(label_path)
             
             # Yield the dataset example
             yield image_id, {