Create app.py

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+from paddlenlp import Taskflow
+import json
+import numpy as np
+import requests
+import urllib
+from io import BytesIO
+from PIL import Image
+
+vision_language=Taskflow("feature_extraction", model='PaddlePaddle/ernie_vil-2.0-base-zh')
+
+def getImageTestFeture(content):
+    if content.startswith("http"):
+        response = requests.get(content)
+        x=BytesIO(response.content)
+        f_embeds = vision_language(Image.open(x))
+    else:
+        f_embeds = vision_language(content)
+    text_features = f_embeds["features"][0]
+    text_features=text_features.tolist()
+    return text_features
+
+def greet(name):
+    x=getImageTestFeture(name)
+    return x
+
+demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+    
+if __name__ == "__main__":
+    demo.launch()