Update new_dataset_script.py

new_dataset_script.py

@@ -170,17 +170,25 @@ def _generate_examples(self, filepaths, species_info, data_dir, split):
         image_path = os.path.join(data_dir, f"{image_id}.jpg")
         label_path = os.path.join(data_dir, f"{image_id}.txt")
         
+        # Find the corresponding row in the CSV for the current image
+        species_row = species_info.loc[species_info['FileName'] == image_id]
+        if not species_row.empty:
+            species = species_row['Species'].values[0]
+            scientific_name = species_row['ScientificName'].values[0]
+            width = species_row['Width'].values[0]
+            height = species_row['Height'].values[0]
+        else:
+            # Default values if not found
+            species = None
+            scientific_name = None
+            width = 1024  # or some default value
+            height = 768   # or some default value
+        
         with Image.open(image_path) as img:
-            width, height = img.size
             pics_array = np.array(img)  # Convert the PIL image to a numpy array
-        
-        species_row = species_info.loc[species_info['FileName'] == file_name]
-        species = species_row['Species'].values[0] if not species_row.empty else None
-        scientific_name = species_row['ScientificName'].values[0] if not species_row.empty else None
 
         annotations = self._parse_yolo_labels(label_path, width, height)
         
-        
         yield image_id, {
             "image_id": image_id,
             "species": species,