Update Stomatal_Images_Datasets.py

Stomatal_Images_Datasets.py

@@ -45,14 +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_center_rel": datasets.Value("float32"),
-                    "y_center_rel": datasets.Value("float32"),
-                    "width_rel": datasets.Value("float32"),
-                    "height_rel": 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"),
                 },
             }),
         })
@@ -91,44 +91,44 @@ class NewDataset(datasets.GeneratorBasedBuilder):
    
 
         
-     # 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, 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),
-                "x_center_rel": x_center_rel,
-                "y_center_rel": y_center_rel,
-                "width_rel": width_rel,
-                "height_rel": height_rel,
+                "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, 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())
+    #         annotations.append({
+    #             "category_id": int(class_id),
+    #             "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):