add api

app.py

@@ -19,6 +19,12 @@ def predict(image: PIL.Image.Image):
     result_text = '<div id="m5dd_result">' + ', '.join(result_filter.keys()) + '</div>'
     return result_html, result_text
 
+def predict_api(image: PIL.Image.Image):
+    result_threshold = genTag(image, 0.5)
+    result_filter = {key: value for key, value in result_threshold.items() if not is_ignore(key, 2)}
+    tag = ', '.join(result_filter.keys())
+    return str(tag)
+
 def predict_batch(zip_file, progress=gr.Progress()):
     result = ''
     with zipfile.ZipFile(zip_file) as zf:
@@ -53,6 +59,7 @@ with gr.Blocks(head_paths="head.html") as demo:
                 batch_file = gr.File(label="Upload a ZIP file containing images",
                                      file_types=['.zip'])
                 run_button2 = gr.Button('Run')
+                run_button_api = gr.Button(value: 'Run', visible: False)
             with gr.Column(scale=2):
                 result_text2 = gr.Textbox(lines=20,
                                           max_lines=20,
@@ -63,13 +70,19 @@ with gr.Blocks(head_paths="head.html") as demo:
         fn=predict,
         inputs=[image],
         outputs=[result_html, result_text],
-        api_name='predict',
+        api_name=False,
     )
     run_button2.click(
         fn=predict_batch,
         inputs=[batch_file],
         outputs=[result_text2],
-        api_name='predict_batch',
+        api_name=False,
+    )
+    run_button_api.click(
+        fn=predict_api,
+        inputs=[image],
+        outputs=[result_text2],
+        api_name='predict',
     )
 
 if __name__ == "__main__":