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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()