import gradio as gr import os import cv2 from rembg import new_session, remove from PIL import Image from io import BytesIO def inference(file, mask, model, alpha_influence, segmentation_strength, smoothing): im = cv2.imread(file, cv2.IMREAD_COLOR) cv2.imwrite(os.path.join("input.png"), im) 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, only_mask=(True if mask == "Mask only" else False), alpha_matting=True, # Habilitar el modo alpha matting alpha_matting_foreground_threshold=alpha_influence, # Control de influencia del canal alfa alpha_matting_background_threshold=1 - alpha_influence, # Control del canal alfa para el fondo alpha_matting_erode_size=int(segmentation_strength * 10), # Control de fuerza de segmentación alpha_matting_smoothing=smoothing, # Control de suavizado de bordes de la segmentación session=new_session(model) ) o.write(output) return Image.open(BytesIO(output)) title = "Background Using RemBG" description = "Help me improve my computer equipment, I need RTX 4070 :)Gradio demo for RemBG. erase the background of any image, To use it, simply upload your image and adjust the sliders and choose a eraser plugin from the U2net library. / Original article made by KenjieDec / Github Repo

" article = "

Github Repo

" article = "

Model on Hugging Face

" 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.inputs.Slider(minimum=0.0, maximum=1.0, default=0.5, label="Alpha Influence"), gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.5, label="Segmentation Strength"), gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.5, label="Smoothing"), ], gr.outputs.Image(type="PIL", label="Output"), #description = "Original article made by KenjieDecGithub Repo

" title=title, description=description, article=article, examples=[["lion.png", "Default", "u2net", 0.5, 0.5, 0.5], ["girl.jpg", "Default", "u2net", 0.5, 0.5, 0.5], ["anime-girl.jpg", "Default", "isnet-anime", 0.5, 0.5, 0.5]], enable_queue=True ).launch()