from tensorflow.keras.models import load_model 
import numpy as np
import cv2

model = load_model('sentimentality.h5')

def sentiment(text):
    result = model(text)[0]
    label = result['label']
    score = round(result['score'], 3)
    return f"{label} ({score})"

input_text = gr.inputs.Textbox(label="Enter text here to be classified:")
label = gr.outputs.Label(num_top_classes=2)
gr.Interface(fn=predict_from_img, inputs=image, outputs=label,title = 'Sentiment-Analysis').launch()