dev(narugo): add new model

app.py

@@ -97,7 +97,16 @@ def image_to_tensor(pic: Image.Image, size: int = 512, keep_ratio: float = True,
     return to_tensor(resize(fill_background(pic, background), size, keep_ratio))
 
 
-def get_onnx_model_file(name='TResnet-D-FLq_ema_6-10000.onnx'):
+MODELS = [
+    'TResnet-D-FLq_ema_6-30000.onnx',
+    'TResnet-D-FLq_ema_6-10000.onnx',
+    'TResnet-D-FLq_ema_4-10000.onnx',
+    'TResnet-D-FLq_ema_2-40000.onnx',
+]
+DEFAULT_MODEL = MODELS[0]
+
+
+def get_onnx_model_file(name=DEFAULT_MODEL):
     return hf_hub_download(
         repo_id='deepghs/ml-danbooru-onnx',
         filename=name,
@@ -125,7 +134,7 @@ def load_classes() -> List[str]:
 
 
 def get_tags_from_image(pic: Image.Image, threshold: float = 0.7, size: int = 512, keep_ratio: bool = False,
-                        model_name='TResnet-D-FLq_ema_6-10000.onnx'):
+                        model_name=DEFAULT_MODEL):
     real_input = image_to_tensor(pic, size, keep_ratio)
     real_input = real_input.reshape(1, *real_input.shape)
 
@@ -164,12 +173,6 @@ def image_to_mldanbooru_tags(pic: Image.Image, threshold: float, size: int, keep
     return output_text, filtered_tags
 
 
-MODELS = [
-    'TResnet-D-FLq_ema_6-10000.onnx',
-    'TResnet-D-FLq_ema_4-10000.onnx',
-    'TResnet-D-FLq_ema_2-40000.onnx',
-]
-
 if __name__ == '__main__':
     with gr.Blocks() as demo:
         with gr.Row():
@@ -180,7 +183,7 @@ if __name__ == '__main__':
                     gr_image_size = gr.Slider(128, 960, 640, step=32, label='Image for Recognition')
                     gr_keep_ratio = gr.Checkbox(value=False, label='Keep the Ratio')
                 with gr.Row():
-                    gr_model = gr.Dropdown(MODELS, value=MODELS[0], label='Model')
+                    gr_model = gr.Dropdown(MODELS, value=DEFAULT_MODEL, label='Model')
                 with gr.Row():
                     gr_space = gr.Checkbox(value=False, label='Use Space Instead Of _')
                     gr_escape = gr.Checkbox(value=True, label='Use Text Escape')