|
import cv2 |
|
import gradio as gr |
|
import os |
|
import functools |
|
from PIL import Image |
|
from rembg import remove |
|
from io import BytesIO |
|
import numpy as np |
|
import torch |
|
from torch.autograd import Variable |
|
from torchvision import transforms |
|
import torch.nn.functional as F |
|
import gdown |
|
import matplotlib.pyplot as plt |
|
import warnings |
|
warnings.filterwarnings("ignore") |
|
import requests |
|
|
|
@functools.lru_cache() |
|
def get_url_im(t): |
|
user_agent = {'User-agent': 'gradio-app'} |
|
response = requests.get(t, headers=user_agent) |
|
return (BytesIO(response.content)) |
|
|
|
|
|
def inference(image): |
|
im_path = get_url_im(image) |
|
im = Image.open(im_reader(im_path)) |
|
|
|
|
|
return im |
|
|
|
|
|
|
|
|
|
interface = gr.Interface( |
|
fn=inference, |
|
inputs=gr.Textbox(label="Text or Image URL", interactive=True), |
|
outputs=["image"], |
|
title="Dsdsd", |
|
description="dsds", |
|
article="dsd", |
|
allow_flagging='never', |
|
cache_examples=False, |
|
).queue().launch(show_error=True, share = True) |
