Add --use_rating_tags and --character_tags_first for WD Tagger

finetune/tag_images_by_wd14_tagger.py

@@ -130,10 +130,10 @@ def main(args):
         input_name = model.graph.input[0].name
         try:
             batch_size = model.graph.input[0].type.tensor_type.shape.dim[0].dim_value
-        except:
+        except Exception:
             batch_size = model.graph.input[0].type.tensor_type.shape.dim[0].dim_param
 
-        if args.batch_size != batch_size and type(batch_size) != str and batch_size > 0:
+        if args.batch_size != batch_size and not isinstance(batch_size, str) and batch_size > 0:
             # some rebatch model may use 'N' as dynamic axes
             logger.warning(
                 f"Batch size {args.batch_size} doesn't match onnx model batch size {batch_size}, use model batch size {batch_size}"
@@ -169,9 +169,9 @@ def main(args):
 
     with open(os.path.join(model_location, CSV_FILE), "r", encoding="utf-8") as f:
         reader = csv.reader(f)
-        l = [row for row in reader]
-        header = l[0]  # tag_id,name,category,count
-        rows = l[1:]
+        line = [row for row in reader]
+        header = line[0]  # tag_id,name,category,count
+        rows = line[1:]
     assert header[0] == "tag_id" and header[1] == "name" and header[2] == "category", f"unexpected csv format: {header}"
 
     rating_tags = [row[1] for row in rows[0:] if row[2] == "9"]
@@ -228,20 +228,24 @@ def main(args):
                     if tag_name not in undesired_tags:
                         tag_freq[tag_name] = tag_freq.get(tag_name, 0) + 1
                         character_tag_text += caption_separator + tag_name
-                        combined_tags.insert(0,tag_name) # insert to the beginning
+                        if args.character_tags_first: # insert to the beginning
+                            combined_tags.insert(0,tag_name)
+                        else:
+                            combined_tags.append(tag_name)
 
             #最初の4つはratingなので無視する
             # First 4 labels are actually ratings: pick one with argmax
-            ratings_names = prob[:4]
-            rating_index = ratings_names.argmax()
-            found_rating = rating_tags[rating_index]
-            if args.remove_underscore and len(found_rating) > 3:
-                found_rating = found_rating.replace("_", " ")
+            if args.use_rating_tags:
+                ratings_names = prob[:4]
+                rating_index = ratings_names.argmax()
+                found_rating = rating_tags[rating_index]
+                if args.remove_underscore and len(found_rating) > 3:
+                    found_rating = found_rating.replace("_", " ")
 
-            if found_rating not in undesired_tags:
-                tag_freq[found_rating] = tag_freq.get(found_rating, 0) + 1
-                rating_tag_text = found_rating
-                combined_tags.insert(0,found_rating) # insert to the beginning
+                if found_rating not in undesired_tags:
+                    tag_freq[found_rating] = tag_freq.get(found_rating, 0) + 1
+                    rating_tag_text = found_rating
+                    combined_tags.insert(0,found_rating) # insert to the beginning
 
             # 先頭のカンマを取る
             if len(general_tag_text) > 0:
@@ -332,7 +336,9 @@ def main(args):
 
 def setup_parser() -> argparse.ArgumentParser:
     parser = argparse.ArgumentParser()
-    parser.add_argument("train_data_dir", type=str, help="directory for train images / 学習画像データのディレクトリ")
+    parser.add_argument(
+        "train_data_dir", type=str, help="directory for train images / 学習画像データのディレクトリ"
+    )
     parser.add_argument(
         "--repo_id",
         type=str,
@@ -350,7 +356,9 @@ def setup_parser() -> argparse.ArgumentParser:
         action="store_true",
         help="force downloading wd14 tagger models / wd14 taggerのモデルを再ダウンロードします",
     )
-    parser.add_argument("--batch_size", type=int, default=1, help="batch size in inference / 推論時のバッチサイズ")
+    parser.add_argument(
+        "--batch_size", type=int, default=1, help="batch size in inference / 推論時のバッチサイズ"
+    )
     parser.add_argument(
         "--max_data_loader_n_workers",
         type=int,
@@ -389,7 +397,9 @@ def setup_parser() -> argparse.ArgumentParser:
         action="store_true",
         help="replace underscores with spaces in the output tags / 出力されるタグのアンダースコアをスペースに置き換える",
     )
-    parser.add_argument("--debug", action="store_true", help="debug mode")
+    parser.add_argument(
+        "--debug", action="store_true", help="debug mode"
+    )
     parser.add_argument(
         "--undesired_tags",
         type=str,
@@ -399,10 +409,18 @@ def setup_parser() -> argparse.ArgumentParser:
     parser.add_argument(
         "--frequency_tags", action="store_true", help="Show frequency of tags for images / 画像ごとのタグの出現頻度を表示する"
     )
-    parser.add_argument("--onnx", action="store_true", help="use onnx model for inference / onnxモデルを推論に使用する")
+    parser.add_argument(
+        "--onnx", action="store_true", help="use onnx model for inference / onnxモデルを推論に使用する"
+    )
     parser.add_argument(
         "--append_tags", action="store_true", help="Append captions instead of overwriting / 上書きではなくキャプションを追記する"
     )
+    parser.add_argument(
+        "--use_rating_tags", action="store_true", help="Adds rating tags as the first tag",
+    )
+    parser.add_argument(
+        "--character_tags_first", action="store_true", help="Always inserts character tags before the general tags",
+    )
     parser.add_argument(
         "--caption_separator",
         type=str,