First model version

app.py

@@ -1,8 +1,8 @@
 import os
 os.system('pip install --upgrade --no-cache-dir gdown')
-os.system('gdown -O ./model_ctw.pth 16qgtD4UOhp0q5e2RYXE1dvuTz_ylZMyb')
+os.system('gdown -O ./model_ctw.pth 1Ajslu_9WisuZ2nJGzE6qbD87aK6_ozzA')
 #os.system('unzip model_ctw.zip')
-os.system('gdown -O ./workdir.zip 1mYM_26qHUom_5NU7iutHneB_KHlLjL5y')
+os.system('gdown -O ./workdir.zip 10HxLehcJMY9rLd_OyH40HmrySZItuNDt')
 os.system('unzip workdir.zip')
 os.system('pip install "git+https://github.com/philferriere/cocoapi.git#egg=pycocotools&subdirectory=PythonAPI"')
 os.system('python setup.py build develop --user')
@@ -58,13 +58,13 @@ output_image = gr.Image(label="out_img", type="filepath")
 output_word = gr.Dataframe(label="out_word", headers=['word'])
 
 with blocks:
-    description = gr.Markdown('''## Step 1 (Preprocess Input Image)
-    - Drop an image containing a near-frontal face to the **Input Image**.
-    - If there are multiple faces in the image, hit the Edit button in the upper right corner and crop the input image beforehand.
-    - Hit the **Detect & Align Face** button.
-    - Hit the **Reconstruct Face** button.
-    - The final result will be based on this **Reconstructed Face**. So, if the reconstructed image is not satisfactory, you may want to change the input image.
+    gr.Markdown('''
+    <h1 id="title">张博强毕设展示</h1>
+    <center> 西北工业大学 航海学院本科 张博强 </center>
+    <center> 毕设题目：自然场景中任意形状文字的检测与识别 </center>
+    <center> 检测：基于<a href="https://github.com/wangyuxin87/ContourNet">ContourNet</a> 识别：基于<a href="https://github.com/FangShancheng/ABINet">ABINet</a> </center>
     ''')
+    
     with gr.Row():
         with gr.Column():
             input_image.render()