app1.py

# import tensorflow as tf
import cv2
import numpy as np
# from glob import glob
# from models import Yolov4
import gradio as gr
# model = Yolov4(weight_path="yolov4.weights", class_name_path='coco_classes.txt')
def gradio_wrapper(img):
    global model
    #print(np.shape(img))
    # results = model.predict(img)
    # return results[0]
demo = gr.Interface(
    gradio_wrapper,
    #gr.Image(source="webcam", streaming=True, flip=True),
    gr.Image(source="webcam", streaming=True),
    "image",
    live=True
)

demo.launch()