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import os | |
os.system('python setup.py install --user') | |
import argparse | |
import csv | |
import sys | |
sys.path.append("/home/user/.local/lib/python3.8/site-packages/diffvg-0.0.1-py3.8-linux-x86_64.egg") | |
print(sys.path) | |
from pathlib import Path | |
import gradio as gr | |
import torch | |
import yaml | |
from PIL import Image | |
from subprocess import call | |
import torch | |
import cv2 | |
import matplotlib.pyplot as plt | |
import random | |
import argparse | |
import math | |
import errno | |
from tqdm import tqdm | |
import yaml | |
from easydict import EasyDict as edict | |
def run_cmd(command): | |
try: | |
print(command) | |
call(command, shell=True) | |
except KeyboardInterrupt: | |
print("Process interrupted") | |
sys.exit(1) | |
# run_cmd("gcc --version") | |
# run_cmd("pwd") | |
# run_cmd("ls") | |
# run_cmd("git submodule update --init --recursive") | |
# run_cmd("python setup.py install --user") | |
# run_cmd("pip3 list") | |
# import pydiffvg | |
# | |
# print("Sccuessfuly import diffvg ") | |
# run_cmd("pwd") | |
# run_cmd("ls") | |
# run_cmd("git submodule update --init --recursive") | |
# run_cmd("python setup.py install --user") | |
# run_cmd("python main.py --config config/base.yaml --experiment experiment_5x1 --signature smile --target figures/smile.png --log_dir log/") | |
from main import main_func | |
def parse_args(): | |
parser = argparse.ArgumentParser() | |
parser.add_argument('--debug', action='store_true', default=False) | |
parser.add_argument("--config", default="config/base.yaml", type=str) | |
parser.add_argument("--experiment", type=str) | |
parser.add_argument("--seed", type=int) | |
parser.add_argument("--target", type=str, help="target image path") | |
parser.add_argument('--log_dir', metavar='DIR', default="log/debug") | |
parser.add_argument('--initial', type=str, default="random", choices=['random', 'circle']) | |
parser.add_argument('--signature', default="demo", nargs='+', type=str) | |
parser.add_argument('--seginit', nargs='+', type=str) | |
parser.add_argument("--num_segments", type=int, default=4) | |
# parser.add_argument("--num_paths", type=str, default="1,1,1") | |
# parser.add_argument("--num_iter", type=int, default=500) | |
# parser.add_argument('--free', action='store_true') | |
# Please ensure that image resolution is divisible by pool_size; otherwise the performance would drop a lot. | |
# parser.add_argument('--pool_size', type=int, default=40, help="the pooled image size for next path initialization") | |
# parser.add_argument('--save_loss', action='store_true') | |
# parser.add_argument('--save_init', action='store_true') | |
# parser.add_argument('--save_image', action='store_true') | |
# parser.add_argument('--save_video', action='store_true') | |
# parser.add_argument('--print_weight', action='store_true') | |
# parser.add_argument('--circle_init_radius', type=float) | |
cfg = edict() | |
args = parser.parse_args() | |
cfg.debug = args.debug | |
cfg.config = args.config | |
cfg.experiment = args.experiment | |
cfg.seed = args.seed | |
cfg.target = args.target | |
cfg.log_dir = args.log_dir | |
cfg.initial = args.initial | |
cfg.signature = args.signature | |
# set cfg num_segments in command | |
cfg.num_segments = args.num_segments | |
if args.seginit is not None: | |
cfg.seginit = edict() | |
cfg.seginit.type = args.seginit[0] | |
if cfg.seginit.type == 'circle': | |
cfg.seginit.radius = float(args.seginit[1]) | |
return cfg | |
def app_experiment_change(experiment_id): | |
if experiment_id == "add [1, 1, 1, 1, 1] total 5 paths": | |
return "experiment_5x1" | |
elif experiment_id == "add [1, 1, 1, 1, 1, 1, 1, 1] total 8 paths": | |
return "experiment_8x1" | |
elif experiment_id == "add [1,2,4,8,16,32, ...] total 128 paths": | |
return "experiment_exp2_128" | |
elif experiment_id == "add [1,2,4,8,16,32, ...] total 256 paths": | |
return "experiment_exp2_256" | |
cfg_arg = parse_args() | |
def run_live(img, experiment_id, cfg_arg=cfg_arg): | |
experiment = app_experiment_change(experiment_id) | |
cfg_arg.target = img | |
cfg_arg.experiment = experiment | |
main_func(img, experiment_id, cfg_arg=cfg_arg) | |
return 0, 1 | |
# ROOT_PATH = sys.path[0] # 根目录 | |
# # 模型路径 | |
# model_path = "ultralytics/yolov5" | |
# # 模型名称临时变量 | |
# model_name_tmp = "" | |
# # 设备临时变量 | |
# device_tmp = "" | |
# # 文件后缀 | |
# suffix_list = [".csv", ".yaml"] | |
# def parse_args(known=False): | |
# parser = argparse.ArgumentParser(description="Gradio LIVE") | |
# parser.add_argument( | |
# "--model_name", "-mn", default="yolov5s", type=str, help="model name" | |
# ) | |
# parser.add_argument( | |
# "--model_cfg", | |
# "-mc", | |
# default="./model_config/model_name_p5_all.yaml", | |
# type=str, | |
# help="model config", | |
# ) | |
# parser.add_argument( | |
# "--cls_name", | |
# "-cls", | |
# default="./cls_name/cls_name.yaml", | |
# type=str, | |
# help="cls name", | |
# ) | |
# parser.add_argument( | |
# "--nms_conf", | |
# "-conf", | |
# default=0.5, | |
# type=float, | |
# help="model NMS confidence threshold", | |
# ) | |
# parser.add_argument( | |
# "--nms_iou", "-iou", default=0.45, type=float, help="model NMS IoU threshold" | |
# ) | |
# | |
# parser.add_argument( | |
# "--label_dnt_show", | |
# "-lds", | |
# action="store_false", | |
# default=True, | |
# help="label show", | |
# ) | |
# parser.add_argument( | |
# "--device", | |
# "-dev", | |
# default="cpu", | |
# type=str, | |
# help="cuda or cpu, hugging face only cpu", | |
# ) | |
# parser.add_argument( | |
# "--inference_size", "-isz", default=640, type=int, help="model inference size" | |
# ) | |
# | |
# args = parser.parse_known_args()[0] if known else parser.parse_args() | |
# return args | |
# # 模型加载 | |
# def model_loading(model_name, device): | |
# | |
# # 加载本地模型 | |
# model = torch.hub.load(model_path, model_name, force_reload=True, device=device) | |
# | |
# return model | |
# # 检测信息 | |
# def export_json(results, model, img_size): | |
# | |
# return [ | |
# [ | |
# { | |
# "id": int(i), | |
# "class": int(result[i][5]), | |
# "class_name": model.model.names[int(result[i][5])], | |
# "normalized_box": { | |
# "x0": round(result[i][:4].tolist()[0], 6), | |
# "y0": round(result[i][:4].tolist()[1], 6), | |
# "x1": round(result[i][:4].tolist()[2], 6), | |
# "y1": round(result[i][:4].tolist()[3], 6), | |
# }, | |
# "confidence": round(float(result[i][4]), 2), | |
# "fps": round(1000 / float(results.t[1]), 2), | |
# "width": img_size[0], | |
# "height": img_size[1], | |
# } | |
# for i in range(len(result)) | |
# ] | |
# for result in results.xyxyn | |
# ] | |
# def yolo_det(img, experiment_id, device=None, model_name=None, inference_size=None, conf=None, iou=None, label_opt=None, model_cls=None): | |
# | |
# global model, model_name_tmp, device_tmp | |
# | |
# if model_name_tmp != model_name: | |
# # 模型判断,避免反复加载 | |
# model_name_tmp = model_name | |
# model = model_loading(model_name_tmp, device) | |
# elif device_tmp != device: | |
# device_tmp = device | |
# model = model_loading(model_name_tmp, device) | |
# | |
# # -----------模型调参----------- | |
# model.conf = conf # NMS 置信度阈值 | |
# model.iou = iou # NMS IOU阈值 | |
# model.max_det = 1000 # 最大检测框数 | |
# model.classes = model_cls # 模型类别 | |
# | |
# results = model(img, size=inference_size) # 检测 | |
# results.render(labels=label_opt) # 渲染 | |
# | |
# det_img = Image.fromarray(results.imgs[0]) # 检测图片 | |
# | |
# det_json = export_json(results, model, img.size)[0] # 检测信息 | |
# | |
# return det_img, det_json | |
# def run_cmd(command): | |
# try: | |
# print(command) | |
# call(command, shell=True) | |
# except KeyboardInterrupt: | |
# print("Process interrupted") | |
# sys.exit(1) | |
# | |
# run_cmd("gcc --version") | |
# run_cmd("pwd") | |
# run_cmd("ls") | |
# run_cmd("git submodule update --init --recursive") | |
# run_cmd("python setup.py install --user") | |
# run_cmd("ls") | |
# run_cmd("python main.py --config config/base.yaml --experiment experiment_5x1 --signature smile --target figures/smile.png --log_dir log/") | |
# # yaml文件解析 | |
# def yaml_parse(file_path): | |
# return yaml.safe_load(open(file_path, "r", encoding="utf-8").read()) | |
# | |
# | |
# # yaml csv 文件解析 | |
# def yaml_csv(file_path, file_tag): | |
# file_suffix = Path(file_path).suffix | |
# if file_suffix == suffix_list[0]: | |
# # 模型名称 | |
# file_names = [i[0] for i in list(csv.reader(open(file_path)))] # csv版 | |
# elif file_suffix == suffix_list[1]: | |
# # 模型名称 | |
# file_names = yaml_parse(file_path).get(file_tag) # yaml版 | |
# else: | |
# print(f"{file_path}格式不正确!程序退出!") | |
# sys.exit() | |
# | |
# return file_names | |
def main(args): | |
gr.close_all() | |
# -------------------Inputs------------------- | |
inputs_img = gr.inputs.Image(type="pil", label="Input Image") | |
experiment_id = gr.inputs.Radio( | |
choices=[ | |
"add [1, 1, 1, 1, 1] total 5 paths", | |
"add [1, 1, 1, 1, 1, 1, 1, 1] total 8 paths", | |
"add [1,2,4,8,16,32, ...] total 128 paths", | |
"add [1,2,4,8,16,32, ...] total 256 paths"], type="value", default="add [1, 1, 1, 1, 1] total 5 paths", label="Path Adding Scheduler" | |
) | |
# inputs | |
inputs = [ | |
inputs_img, # input image | |
experiment_id, # path adding scheduler | |
] | |
# outputs | |
outputs = gr.outputs.Image(type="numpy", label="检测图片") | |
outputs02 = gr.outputs.JSON(label="检测信息") | |
# title | |
title = "LIVE: Towards Layer-wise Image Vectorization" | |
# description | |
description = "<div align='center'>(CVPR 2022 Oral Presentation)</div>" \ | |
"<div align='center'>Without GPUs, it will cost longer time.</div>" | |
# examples | |
examples = [ | |
[ | |
"./examples/1.png", | |
"add [1, 1, 1, 1, 1] total 5 paths", | |
], | |
[ | |
"./examples/2.png", | |
"add [1, 1, 1, 1, 1] total 5 paths", | |
], | |
[ | |
"./examples/3.jpg", | |
"add [1,2,4,8,16,32, ...] total 128 paths", | |
], | |
[ | |
"./examples/4.png", | |
"add [1,2,4,8,16,32, ...] total 256 paths", | |
], | |
[ | |
"./examples/5.png", | |
"add [1, 1, 1, 1, 1] total 5 paths", | |
], | |
] | |
# Interface | |
gr.Interface( | |
fn=run_live, | |
inputs=inputs, | |
outputs=[outputs, outputs02], | |
title=title, | |
description=description, | |
examples=examples, | |
theme="seafoam", | |
# live=True, # 实时变更输出 | |
flagging_dir="run" # 输出目录 | |
# ).launch(inbrowser=True, auth=['admin', 'admin']) | |
).launch( | |
inbrowser=True, # 自动打开默认浏览器 | |
show_tips=True, # 自动显示gradio最新功能 | |
enable_queue=True | |
# favicon_path="./icon/logo.ico", | |
) | |
if __name__ == "__main__": | |
args = parse_args() | |
main(args) | |