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import gradio as gr
import numpy as np
import imageio
from PIL import Image
source_img = gr.Image(source="upload", type="numpy", tool="sketch");
outputs = [gr.outputs.Image(type="file",label="output"),gr.outputs.Image(type="file",label="Mask")]
def resize(height,img):
baseheight = height
img = Image.open(img)
hpercent = (baseheight/float(img.size[1]))
wsize = int((float(img.size[0])*float(hpercent)))
img = img.resize((wsize,baseheight), Image.Resampling.LANCZOS)
return img
def predict(source_img):
#print(sketch)
#print(sketch.mode)
#sketch_png = resize(512,source_img)
#sketch_png.save('source.png')
#print(sketch_png)
imageio.imwrite("data.png", source_img["image"])
imageio.imwrite("data_mask.png", source_img["mask"])
return "data.png", "data_mask.png"
gr.Interface(fn=predict, inputs=source_img, outputs=outputs).launch(enable_queue=True) |