update .gitignore

.gitignore

@@ -0,0 +1,32 @@
+ppocr/data/__pycache__
+ppocr/data/imaug/__pycache__
+ppocr/data/imaug/text_image_aug/__pycache__
+ppocr/data/imaug/vqa/__pycache__
+ppocr/data/imaug/vqa/token/__pycache__
+ppocr/modeling/backbones/__pycache__
+ppocr/modeling/heads/__pycache__
+ppocr/modeling/necks/__pycache__
+ppocr/modeling/transforms/__pycache__
+ppocr/modeling/postprocess/__pycache__
+ppocr/modeling/postprocess/utils/__pycache__
+ppocr/modeling/postprocess/utils/e2e_metric/__pycache__
+ppocr/modeling/postprocess/utils/e2e_utils/__pycache__
+ppocr/modeling/postprocess/utils/loggers/__pycache__
+ppstructure/__pycache__
+ppstructure/kie/__pycache__
+ppstructure/layout/__pycache__
+ppstructure/table/__pycache__
+tools/__pycache__
+
+
+
+
+
+
+
+
+
+
+
+
+

app.py

@@ -38,18 +38,45 @@ def inference__ppstructure(img_path):
         rec_image_shape="3, 48, 320",
         ser_dict_path='ppocr/utils/dict/kie/clinical_class_list.txt'
     )
+    samples = ['病歷','身份','姓名','  Medical','No.','Name','性別','中華民國','002480','身分','Attending','M.D','ID','Medical','by','續上頁診斷書內容','出生地','列印時間','以上','年齡','特予']
+    result,_ = ppsutructure.__call__(img_path)
     
-    result,res2 = ppsutructure.__call__(img_path)
+    for element in result:
+        for sample in samples:
+            if sample in element['transcription']:
+                element['pred_id'] = 0
+                element['pred'] ='O'
     image = draw_ser_results(img_path,result,font_path='./simfang.ttf')
     result = [''.join(f"{element['pred']}:{element['transcription']}") for element in result if element['pred']!='O']
     return image, "\n".join(result)
 
-    
-gr.Interface(
-    inference__ppstructure,
-    [gr.Image(type='filepath', label='圖片上傳')],
-    outputs=[
-        gr.Image(type="pil", label="識別結果"),
-        "text"
-    ],
-    ).launch(debug=True)
+with gr.Blocks() as demo:
+    gr.Markdown("Form Understanding Project - Certificate of Diagnosis")
+    gr.Markdown("Support languages：traditinonal chinese")
+    gr.Markdown("""
+    ## Usage Description
+    This interface is designed to process and extract information from Certificates of Diagnosis. 
+    To use this tool:
+    1. Upload an image of a Certificate of Diagnosis using the 'Upload Image' button.
+    2. Optionally, enter the image URL if the certificate is available online.
+    3. Click 'Process' to extract information from the uploaded certificate.
+    4. The processed image and extracted text will be displayed on the right.
+    """)
+    with gr.Row():
+        with gr.Column():
+            image_input = gr.Image(type='filepath', label='Upload Image')
+            url_input = gr.Textbox(label='Or enter Image URL')
+            submit_btn = gr.Button("Process")
+        with gr.Column():
+            gr.Markdown("#### Processed Image")
+            image_output = gr.Image(type="pil", label="Processed Image")
+            gr.Markdown("#### Extracted Text")
+            text_output = gr.Textbox(label="Extracted Text")
+
+    submit_btn.click(
+        inference__ppstructure, 
+        inputs=[image_input], 
+        outputs=[image_output, text_output]
+    )
+
+demo.launch(debug=True)