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liuyizhang
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Parent(s):
3f5ffbb
add app_cli.py
Browse files- app.py +7 -5
- app_cli.py +121 -0
- dog.png +0 -0
app.py
CHANGED
@@ -19,11 +19,6 @@ if os.environ.get('IS_MY_DEBUG') is None:
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sys.path.insert(0, './GroundingDINO')
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if not os.path.exists('./sam_vit_h_4b8939.pth'):
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logger.info(f"get sam_vit_h_4b8939.pth...")
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result = subprocess.run(['wget', 'https://dl.fbaipublicfiles.com/segment_anything/sam_vit_h_4b8939.pth'], check=True)
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print(f'wget sam_vit_h_4b8939.pth result = {result}')
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import gradio as gr
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import argparse
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@@ -85,6 +80,12 @@ sd_pipe = None
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lama_cleaner_model= None
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ram_model = None
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def load_model_hf(model_config_path, repo_id, filename, device='cpu'):
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args = SLConfig.fromfile(model_config_path)
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model = build_model(args)
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@@ -702,6 +703,7 @@ if __name__ == "__main__":
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print(f'args = {args}')
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set_device()
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load_groundingdino_model()
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load_sam_model()
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load_sd_model()
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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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lama_cleaner_model= None
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ram_model = None
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def get_sam_vit_h_4b8939():
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if not os.path.exists('./sam_vit_h_4b8939.pth'):
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logger.info(f"get sam_vit_h_4b8939.pth...")
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result = subprocess.run(['wget', 'https://dl.fbaipublicfiles.com/segment_anything/sam_vit_h_4b8939.pth'], check=True)
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print(f'wget sam_vit_h_4b8939.pth result = {result}')
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def load_model_hf(model_config_path, repo_id, filename, device='cpu'):
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args = SLConfig.fromfile(model_config_path)
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model = build_model(args)
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print(f'args = {args}')
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set_device()
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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_sd_model()
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app_cli.py
ADDED
@@ -0,0 +1,121 @@
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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.system("pip install diffuser==0.6.0")
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# os.system("pip install transformers==4.29.1")
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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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# result = subprocess.run(['pip', 'list'], check=True)
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# print(f'pip list = {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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# Grounding DINO
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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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# segment anything
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from segment_anything import build_sam, SamPredictor, SamAutomaticMaskGenerator
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# diffusers
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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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# relate anything
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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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# usage:
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# python app_cli.py --input_image dog.png --text dog --output_image dog_remove.png
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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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# set_device() # If you have enough GPUs, you can open this comment
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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_sd_model()
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load_lama_cleaner_model()
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# load_ram_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", # ["segment", "rectangle"]
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remove_mask_extend = "10",
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num_relation = 5)
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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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dog.png
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