## Modified from Akhaliq Hugging Face Demo ## https://huggingface.co/akhaliq import gradio as gr import os import cv2 def inference(file, af, mask, model): im = cv2.imread(file, cv2.IMREAD_COLOR) cv2.imwrite(os.path.join("input.png"), im) from rembg import remove from rembg.session_base import BaseSession from rembg.session_factory import new_session input_path = 'input.png' output_path = 'output.png' with open(input_path, 'rb') as i: with open(output_path, 'wb') as o: input = i.read() sessions: dict[str, BaseSession] = {} output = remove( input, session=sessions.setdefault( model, new_session(model) ), alpha_matting_erode_size = af, only_mask = (True if mask == "Mask only" else False) ) o.write(output) return os.path.join("output.png") title = "RemBG" description = "Gradio demo for RemBG. To use it, simply upload your image and wait. Read more at the link below." article = "
" gr.Interface( inference, [ gr.inputs.Image(type="filepath", label="Input"), gr.inputs.Slider(10, 25, default=10, label="Alpha matting"), gr.inputs.Radio( [ "Default", "Mask only" ], type="value", default="Default", label="Choices" ), gr.inputs.Dropdown([ "u2net", "u2netp", "u2net_human_seg", "u2net_cloth_seg", "silueta" ], type="value", default="u2net", label="Models" ), ], gr.outputs.Image(type="file", label="Output"), title=title, description=description, article=article, examples=[["lion.png", 10, "Default", "u2net"], ["girl.jpg", 10, "Default", "u2net"]], enable_queue=True ).launch()