feat: gradio页面改成中文

joytag/app.py

@@ -6,12 +6,8 @@ from pathlib import Path
 import torch
 import torchvision.transforms.functional as TVF
 
-
 MODEL_REPO = "fancyfeast/joytag"
 THRESHOLD = 0.4
-DESCRIPTION = """
-joytag：一款图像多分类打标签工具，预测标签种类多达5000，可生成多标签及相应的概率预测
-"""
 
 
 def prepare_image(image: Image.Image, target_size: int) -> torch.Tensor:
@@ -32,7 +28,8 @@ def prepare_image(image: Image.Image, target_size: int) -> torch.Tensor:
     image_tensor = TVF.pil_to_tensor(padded_image) / 255.0
 
     # Normalize
-	image_tensor = TVF.normalize(image_tensor, mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
+    image_tensor = TVF.normalize(image_tensor, mean=[0.48145466, 0.4578275, 0.40821073],
+                                 std=[0.26862954, 0.26130258, 0.27577711])
 
     return image_tensor
 
@@ -43,15 +40,12 @@ def predict(image: Image.Image):
     batch = {
         'image': image_tensor.unsqueeze(0),
     }
-
     with torch.amp.autocast_mode.autocast('cpu', enabled=True):
         preds = model(batch)
         tag_preds = preds['tags'].sigmoid().cpu()
-	
     scores = {top_tags[i]: tag_preds[0][i] for i in range(len(top_tags))}
     predicted_tags = [tag for tag, score in scores.items() if score > THRESHOLD]
     tag_string = ', '.join(predicted_tags)
-
     return tag_string, scores
 
 
@@ -67,16 +61,14 @@ print("Starting server...")
 
 gradio_app = gr.Interface(
     predict,
-	inputs=gr.Image(label="Source", sources=['upload', 'webcam'], type='pil'),
+    inputs=gr.Image(label="图像", sources=['upload', 'webcam'], type='pil'),
     outputs=[
-		gr.Textbox(label="Tag String"),
-		gr.Label(label="Tag Predictions", num_top_classes=100),
+        gr.Textbox(label="标签字符"),
+        gr.Label(label="标签及概率", num_top_classes=100),
     ],
-	title="JoyTag",
-	description=DESCRIPTION,
+    title="joytag：一款图像多分类打标签工具，预测标签种类多达5000，可生成多标签及相应的概率预测",
     allow_flagging="never",
 )
 
-
 if __name__ == '__main__':
     gradio_app.launch(server_name='0.0.0.0', share=True)