Spaces:
Runtime error
Runtime error
File size: 1,889 Bytes
5410b69 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 |
import gradio as gr
from gradio_imageslider import ImageSlider
from loadimg import load_img
# import spaces
from transformers import AutoModelForImageSegmentation
import torch
from torchvision import transforms
torch.set_float32_matmul_precision(["high", "highest"][0])
birefnet = AutoModelForImageSegmentation.from_pretrained(
"ZhengPeng7/BiRefNet", trust_remote_code=True
)
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
birefnet.to(device)
transform_image = transforms.Compose(
[
transforms.Resize((1024, 1024)),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
]
)
# @spaces.GPU
def fn(image):
im = load_img(image, output_type="pil")
im = im.convert("RGB")
image_size = im.size
origin = im.copy()
image = load_img(im)
input_images = transform_image(image).unsqueeze(0).to(device)
# Prediction
with torch.no_grad():
preds = birefnet(input_images)[-1].sigmoid().cpu()
pred = preds[0].squeeze()
pred_pil = transforms.ToPILImage()(pred)
mask = pred_pil.resize(image_size)
image.putalpha(mask)
# return (image, origin)
image.save("img.png","PNG")
return (image , "img.png")
img1 = gr.Image(type= "pil", image_mode="RGBA")
image = gr.Image(label="Upload an image")
file = gr.File()
chameleon = load_img("chameleon.jpg", output_type="pil")
url = "https://hips.hearstapps.com/hmg-prod/images/gettyimages-1229892983-square.jpg"
demo = gr.Interface(
fn, inputs=image, outputs=[img1,file], examples=[chameleon], api_name="image"
)
# tab2 = gr.Interface(fn, inputs=text, outputs=slider2, examples=[url], api_name="text")
# demo = gr.TabbedInterface(
# [tab1, tab2], ["image", "text"], title="birefnet for background removal (WIP 🛠️, works for linux)"
# )
if __name__ == "__main__":
demo.launch()
|