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import warnings |
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warnings.filterwarnings('ignore') |
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import subprocess, io, os, sys, time |
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from loguru import logger |
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os.environ["CUDA_VISIBLE_DEVICES"] = "0" |
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if os.environ.get('IS_MY_DEBUG') is None: |
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result = subprocess.run(['pip', 'install', '-e', 'GroundingDINO'], check=True) |
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print(f'pip install GroundingDINO = {result}') |
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sys.path.insert(0, './GroundingDINO') |
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import gradio as gr |
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import argparse |
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import copy |
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import numpy as np |
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import torch |
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from PIL import Image, ImageDraw, ImageFont, ImageOps |
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import GroundingDINO.groundingdino.datasets.transforms as T |
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from GroundingDINO.groundingdino.models import build_model |
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from GroundingDINO.groundingdino.util import box_ops |
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from GroundingDINO.groundingdino.util.slconfig import SLConfig |
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from GroundingDINO.groundingdino.util.utils import clean_state_dict, get_phrases_from_posmap |
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import cv2 |
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import numpy as np |
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import matplotlib.pyplot as plt |
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from lama_cleaner.model_manager import ModelManager |
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from lama_cleaner.schema import Config as lama_Config |
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from segment_anything import build_sam, SamPredictor, SamAutomaticMaskGenerator |
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import PIL |
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import requests |
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import torch |
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from io import BytesIO |
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from diffusers import StableDiffusionInpaintPipeline |
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from huggingface_hub import hf_hub_download |
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from utils import computer_info |
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from ram_utils import iou, sort_and_deduplicate, relation_classes, MLP, show_anns, ram_show_mask |
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from ram_train_eval import RamModel,RamPredictor |
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from mmengine.config import Config as mmengine_Config |
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from app import * |
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config_file = 'GroundingDINO/groundingdino/config/GroundingDINO_SwinT_OGC.py' |
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ckpt_repo_id = "ShilongLiu/GroundingDINO" |
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ckpt_filenmae = "groundingdino_swint_ogc.pth" |
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sam_checkpoint = './sam_vit_h_4b8939.pth' |
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output_dir = "outputs" |
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device = 'cpu' |
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os.makedirs(output_dir, exist_ok=True) |
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groundingdino_model = None |
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sam_device = None |
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sam_model = None |
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sam_predictor = None |
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sam_mask_generator = None |
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sd_pipe = None |
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lama_cleaner_model= None |
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ram_model = None |
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def get_args(): |
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argparser = argparse.ArgumentParser() |
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argparser.add_argument("--input_image", "-i", type=str, default="", help="") |
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argparser.add_argument("--text", "-t", type=str, default="", help="") |
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argparser.add_argument("--output_image", "-o", type=str, default="", help="") |
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args = argparser.parse_args() |
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return args |
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if __name__ == '__main__': |
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args = get_args() |
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logger.info(f'\nargs={args}\n') |
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logger.info(f'loading models ... ') |
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get_sam_vit_h_4b8939() |
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load_groundingdino_model() |
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load_sam_model() |
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load_lama_cleaner_model() |
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input_image = Image.open(args.input_image) |
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output_images, _ = run_anything_task(input_image = input_image, |
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text_prompt = args.text, |
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task_type = 'remove', |
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inpaint_prompt = '', |
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box_threshold = 0.3, |
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text_threshold = 0.25, |
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iou_threshold = 0.8, |
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inpaint_mode = "merge", |
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mask_source_radio = "type what to detect below", |
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remove_mode = "rectangle", |
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remove_mask_extend = "10", |
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num_relation = 5, |
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cleaner_size_limit = -1, |
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) |
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if len(output_images) > 0: |
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logger.info(f'save result to {args.output_image} ... ') |
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output_images[-1].save(args.output_image) |
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