b

app.py

@@ -2,21 +2,39 @@ import gradio as gr
 import os.path
 from PIL import Image
 
-def output(image_path):
-    output_path = 'output'
+def output(image_path,img_id,rule):
+    print(image_path)
+    output_path = './output'
     caption = 'person . mask'
     flag = False
-    save_image_path = os.path.join(output_path,os.path.split(image_path)[-1])
+    save_image_path = os.path.join(output_path,'test'+img_id+'.jpg')
+    print(save_image_path)
     save_image = Image.open(save_image_path).convert("RGB")
     return save_image
 
 with gr.Blocks() as demo:
-    gr.Markdown("<h1><center>Demo</center></h1>")
-    img_obj = gr.Image(value ='image/test.jpg',type = "filepath",label='object_img')
-    btn = gr.Button("Submit",variant="primary")
-    img_output = gr.Image(type = "pil",label='output_img')
-    btn.click(fn=output,inputs=[img_obj],
-    outputs=[img_output],
-    )
+    gr.Markdown("<h1><center>服务监管效果Demo</center></h1>")
+    gr.Markdown("""
+    Tips:
+    - 由于huggingface space不支持提供GPU,本Demo只支持cache中的三个样例效果展示
+    - 目前基于GLIP的架构仅支持口罩佩戴监管,后续可以增加和选择其他规则
+    - 判断部分采用的模型为ALBEF_14M.pth
+    """)
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("<h2>数据导入:</h2>")
+            img_obj = gr.Image(value ='image/test.jpg',type = "filepath",label='object_img')
+            index = gr.Radio(["0", "1", "2"],value ='0',label='img_id')
+            gr.Markdown("<h2>规则选择(目前仅支持口罩佩戴规则):</h2>")
+            rule = gr.Dropdown(["口罩佩戴规则", "隔位就坐规则", "核酸检测规则"],value='请选择规则...',label='规则选择')
+        with gr.Column():
+            gr.Markdown("<h2>效果展示:</h2>")
+            img_output = gr.Image(type = "pil",label='output_img')
+            btn = gr.Button("Submit",variant="primary")
+    
+    with  gr.Row():
+        gr.Examples([['image/test.jpg','0','口罩佩戴规则'],['image/test1.jpg','1','口罩佩戴规则'],['image/test2.jpg','2','口罩佩戴规则']],[img_obj,index,rule],[img_output],output,True)
+
+    btn.click(fn=output,inputs=[img_obj,index,rule],outputs=[img_output],)
 
 demo.launch()