import numpy as np import gradio as gr from model import api from PIL import Image sign_api = api() def sign(input_img): input_img = Image.fromarray(input_img) prediction = sign_api.predict(input_img) print('prediction',prediction) return prediction['class'] css = '' # with gr.Blocks(css=css) as demo: # gr.HTML("

Signsapp: Classify the signs based on the hands sign images

") # gr.Interface(sign,inputs=gr.Image(shape=(200, 200)), outputs=gr.Label()) title = r"Signsapp" description = r"""
Classify the signs based on the hands sign images
""" article = r""" - [Coursera](https://arxiv.org/pdf/1512.03385) """ demo = gr.Interface( title = title, description = description, article = article, fn=sign, inputs = gr.Image(shape=(200, 200)), outputs = gr.Label(), # allow_flagging = "manual", # flagging_options = ['recule', 'tournedroite', 'arretetoi', 'tournegauche', 'gauche', 'avance', 'droite'], # flagging_dir = "./flag/men" ) # demo.queue() demo.launch(debug=True)