import os import io import json import numpy as np import cv2 import gradio as gr import modules.scripts as scripts from modules import script_callbacks from scripts.td_abg import get_foreground from scripts.convertor import pil2cv def processing(input_image, td_abg_enabled, h_split, v_split, n_cluster, alpha, th_rate, cascadePSP_enabled, fast, psp_L): image = pil2cv(input_image) image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) mask, image = get_foreground(image, td_abg_enabled, h_split, v_split, n_cluster, alpha, th_rate, cascadePSP_enabled, fast, psp_L) return image, mask class Script(scripts.Script): def __init__(self) -> None: super().__init__() def title(self): return "PBRemTools" def show(self, is_img2img): return scripts.AlwaysVisible def ui(self, is_img2img): return () def on_ui_tabs(): with gr.Blocks(analytics_enabled=False) as PBRemTools: with gr.Row(): with gr.Column(): input_image = gr.Image(type="pil") with gr.Accordion("tile division BG Remover", open=True): with gr.Box(): td_abg_enabled = gr.Checkbox(label="enabled", show_label=True) h_split = gr.Slider(1, 2048, value=256, step=4, label="horizontal split num", show_label=True) v_split = gr.Slider(1, 2048, value=256, step=4, label="vertical split num", show_label=True) n_cluster = gr.Slider(1, 1000, value=500, step=10, label="cluster num", show_label=True) alpha = gr.Slider(1, 255, value=50, step=1, label="alpha threshold", show_label=True) th_rate = gr.Slider(0, 1, value=0.1, step=0.01, label="mask content ratio", show_label=True) with gr.Accordion("cascadePSP", open=True): with gr.Box(): cascadePSP_enabled = gr.Checkbox(label="enabled", show_label=True) fast = gr.Checkbox(label="fast", show_label=True) psp_L = gr.Slider(1, 2048, value=900, step=1, label="Memory usage", show_label=True) submit = gr.Button(value="Submit") with gr.Row(): with gr.Column(): with gr.Tab("output"): output_img = gr.Image() with gr.Tab("mask"): output_mask = gr.Image() #dummy_component = gr.Label(visible=False) #preset = gr.Text(visible=False) submit.click( processing, inputs=[input_image, td_abg_enabled, h_split, v_split, n_cluster, alpha, th_rate, cascadePSP_enabled, fast, psp_L], outputs=[output_img, output_mask] ) return [(PBRemTools, "PBRemTools", "pbremtools")] script_callbacks.on_ui_tabs(on_ui_tabs)