## Modified from Akhaliq Hugging Face Demo ## https://huggingface.co/akhaliq import gradio as gr import os import cv2 def inference(file, mask, model): im = cv2.imread(file, cv2.IMREAD_COLOR) cv2.imwrite(os.path.join("input.png"), im) from rembg import new_session, remove 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() output = remove( input, session = new_session(model), 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 = "

Github Repo

" gr.Interface( inference, [ gr.inputs.Image(type="filepath", label="Input"), gr.inputs.Radio( [ "Default", "Mask only" ], type="value", default="Default", label="Choices" ), gr.inputs.Dropdown([ "u2net", "u2netp", "u2net_human_seg", "u2net_cloth_seg", "silueta", "isnet-general-use", "isnet-anime", "sam", ], type="value", default="isnet-general-use", label="Models" ), ], gr.outputs.Image(type="filepath", label="Output"), title=title, description=description, article=article, examples=[["lion.png", "Default", "u2net"], ["girl.jpg", "Default", "u2net"], ["anime-girl.jpg", "Default", "isnet-anime"]], enable_queue=True ).launch()