| import gradio as gr | |
| from paddlenlp import Taskflow | |
| from PIL import Image | |
| vision_language=Taskflow("feature_extraction", model='PaddlePaddle/ernie_vil-2.0-base-zh') | |
| def getImageTestFeture(content,flag): | |
| if flag==1: | |
| f_embeds = vision_language(Image.open(content)) | |
| else: | |
| f_embeds = vision_language(content) | |
| text_features = f_embeds["features"][0] | |
| text_features=text_features.tolist() | |
| return text_features | |
| def quickstart(name,fileinfo): | |
| pname=name | |
| flag=0 | |
| if not fileinfo is None: | |
| pname=fileinfo.name | |
| flag=1 | |
| xp=getImageTestFeture(pname,flag) | |
| return xp | |
| demo = gr.Interface(fn=quickstart, inputs=["text","file"], outputs="text") | |
| demo.launch() | |