Update dataset.py

dataset.py

@@ -37,24 +37,25 @@ class TunisianProverbsDataset(GeneratorBasedBuilder):
 
     def _generate_examples(self, csv_path, image_dir):
         df = pd.read_csv(csv_path)
-    
+
+        def safe_image_path(path):
+            if pd.isna(path) or not isinstance(path, str) or not path.strip():
+                return None
+            full_path = os.path.join(image_dir, path.strip())
+            return full_path if os.path.isfile(full_path) else None
+
         for idx, row in df.iterrows():
-            def safe_image_path(path):
-                full_path = os.path.join(image_dir, path) if pd.notna(path) else None
-                return full_path if full_path and os.path.exists(full_path) else None
-    
             yield idx, {
-                "tunisan_proverb": row["tunisan_proverb"],
-                "proverb_arabic_explaination": row["proverb_arabic_explaination"],
-                "context": row["context"],
-                "caption": row["caption"],
-                "caption_formal": row["caption_formal"],
-                "dynamic": row["dynamic"],
-                "prompt": row["prompt"],
-                "image_path_1": safe_image_path(row["image_path_1"]),
-                "image_path_2": safe_image_path(row["image_path_2"]),
-                "image_path_3": safe_image_path(row["image_path_3"]),
-                "image_path_4": safe_image_path(row["image_path_4"]),
-                "clip_scores": float(row["clip_scores"]) if pd.notna(row["clip_scores"]) else 0.0,
-            }
-                
+                "tunisan_proverb": row.get("tunisan_proverb", ""),
+                "proverb_arabic_explaination": row.get("proverb_arabic_explaination", ""),
+                "context": row.get("context", ""),
+                "caption": row.get("caption", ""),
+                "caption_formal": row.get("caption_formal", ""),
+                "dynamic": row.get("dynamic", ""),
+                "prompt": row.get("prompt", ""),
+                "image_path_1": safe_image_path(row.get("image_path_1")),
+                "image_path_2": safe_image_path(row.get("image_path_2")),
+                "image_path_3": safe_image_path(row.get("image_path_3")),
+                "image_path_4": safe_image_path(row.get("image_path_4")),
+                "clip_scores": float(row["clip_scores"]) if pd.notna(row.get("clip_scores")) else 0.0,
+            }