# Copyright (c) Facebook, Inc. and its affiliates. # Copyright (c) Meta Platforms, Inc. All Rights Reserved import multiprocessing as mp import numpy as np from PIL import Image try: import detectron2 except: import os os.system('pip install git+https://github.com/facebookresearch/detectron2.git') from detectron2.config import get_cfg from detectron2.projects.deeplab import add_deeplab_config from detectron2.data.detection_utils import read_image from open_vocab_seg import add_ovseg_config from open_vocab_seg.utils import VisualizationDemo import gradio as gr import gdown # ckpt_url = 'https://drive.google.com/uc?id=1cn-ohxgXDrDfkzC1QdO-fi8IjbjXmgKy' # output = './ovseg_swinbase_vitL14_ft_mpt.pth' # gdown.download(ckpt_url, output, quiet=False) def setup_cfg(config_file): # load config from file and command-line arguments cfg = get_cfg() add_deeplab_config(cfg) add_ovseg_config(cfg) cfg.merge_from_file(config_file) cfg.freeze() return cfg def inference(class_names, input_img): mp.set_start_method("spawn", force=True) config_file = './ovseg_swinB_vitL_demo.yaml' cfg = setup_cfg(config_file) demo = VisualizationDemo(cfg) class_names = class_names.split(',') img = read_image(input_img, format="BGR") _, visualized_output = demo.run_on_image(img, class_names) return Image.fromarray(np.uint8(visualized_output.get_image())).convert('RGB') examples = [['Oculus, Ukulele', './resources/demo_samples/sample_03.jpeg'], ['Saturn V, toys, blossom', './resources/demo_samples/sample_01.jpeg'], ['Golden gate, yacht', './resources/demo_samples/sample_02.jpeg'],] output_labels = ['segmentation map'] title = 'OVSeg' description = """ Gradio Demo for Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP. \n OVSeg could perform open vocabulary segmentation, you may input more classes (seperate by comma). You may click on of the examples or upload your own image. \n It might take some time to process. Cheers!

Don't want to wait in queue? Open In Colab

""" article = """

Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP | Github Repo

""" gr.Interface( inference, inputs=[ gr.inputs.Textbox( lines=1, placeholder=None, default='', label='class names'), gr.inputs.Image(type='filepath') ], outputs=gr.outputs.Image(label='segmentation map'), title=title, description=description, article=article, examples=examples).launch(enable_queue=True)