import gradio as gr
from keras.models import load_model
import cv2
import numpy as np
model = load_model('covid_trained_model.h5')
def sigmoid_to_binary(output_value, threshold=0.705):
    if output_value >= threshold:
        return 1
    else:
        return 0
def covid(img):
    resized_image = cv2.resize(img, (224, 224))
    reshaped_image = np.expand_dims(resized_image, axis=0)
    pred = model.predict(reshaped_image)
    binary = sigmoid_to_binary(pred[0,0])
    if(binary == 0):
        return "COVID POSITIVE +"
    return "COVID NEGATIVE -"
gr.Interface(fn=covid,inputs="image",outputs="text",title="Covid19 Detector by CHEST X-Ray",description="Please upload your CHEST X-RAY in below input field").launch()