学做快餐的视频网站,wordpress 企业主页,做网站的桔子什么,1688网站如果您想使用Pascal Context数据集#xff0c;请安装Detail#xff0c;然后运行以下命令将注释转换为正确的格式。
1.安装Detail
进入项目终端
#即 这是在我自己的项目下直接进行克隆操作#xff1a;
git clone https://github.com/zhanghang1989/detail-api.git $PASCAL…如果您想使用Pascal Context数据集请安装Detail然后运行以下命令将注释转换为正确的格式。
1.安装Detail
进入项目终端
#即 这是在我自己的项目下直接进行克隆操作
git clone https://github.com/zhanghang1989/detail-api.git $PASCAL_CTX
# 获得detail_api
若是出现下面的问题可以手动下载detail-api的压缩包文件到项目中再进行解压.
我的就是git时候出了问题然后手动下载的服务器有时候也不稳定。 5、进行detail_api文件夹的PythonAPI中 cd 你的路径/PythonAPI 然后python setup.py install 可能没有Cython
直接用pip install Cython 再跑python setup.py install 2.格式转换
Pascal Context的训练和验证集可以从这里下
要从原始数据集中分离训练和验证集您可以从此处下载trainval_merged. json。下载链接https://codalabuser.blob.core.windows.net/public/trainval_merged.json python tools/convert_datasets/pascal_context.py data/VOCdevkit data/VOCdevkit/VOC2010/trainval_merged.json 其中pascal_context.py如下
# Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os.path as osp
from functools import partialimport mmcv
import numpy as np
from detail import Detail
from PIL import Image_mapping np.sort(np.array([0, 2, 259, 260, 415, 324, 9, 258, 144, 18, 19, 22, 23, 397, 25, 284,158, 159, 416, 33, 162, 420, 454, 295, 296, 427, 44, 45, 46, 308, 59,440, 445, 31, 232, 65, 354, 424, 68, 326, 72, 458, 34, 207, 80, 355,85, 347, 220, 349, 360, 98, 187, 104, 105, 366, 189, 368, 113, 115]))
_key np.array(range(len(_mapping))).astype(uint8)def generate_labels(img_id, detail, out_dir):def _class_to_index(mask, _mapping, _key):# assert the valuesvalues np.unique(mask)for i in range(len(values)):assert (values[i] in _mapping)index np.digitize(mask.ravel(), _mapping, rightTrue)return _key[index].reshape(mask.shape)mask Image.fromarray(_class_to_index(detail.getMask(img_id), _mapping_mapping, _key_key))filename img_id[file_name]mask.save(osp.join(out_dir, filename.replace(jpg, png)))return osp.splitext(osp.basename(filename))[0]def parse_args():parser argparse.ArgumentParser(descriptionConvert PASCAL VOC annotations to mmsegmentation format)parser.add_argument(devkit_path, helppascal voc devkit path)parser.add_argument(json_path, helpannoation json filepath)parser.add_argument(-o, --out_dir, helpoutput path)args parser.parse_args()return argsdef main():args parse_args()devkit_path args.devkit_pathif args.out_dir is None:out_dir osp.join(devkit_path, VOC2010, SegmentationClassContext)else:out_dir args.out_dirjson_path args.json_pathmmcv.mkdir_or_exist(out_dir)img_dir osp.join(devkit_path, VOC2010, JPEGImages)train_detail Detail(json_path, img_dir, train)train_ids train_detail.getImgs()val_detail Detail(json_path, img_dir, val)val_ids val_detail.getImgs()mmcv.mkdir_or_exist(osp.join(devkit_path, VOC2010/ImageSets/SegmentationContext))train_list mmcv.track_progress(partial(generate_labels, detailtrain_detail, out_dirout_dir),train_ids)with open(osp.join(devkit_path, VOC2010/ImageSets/SegmentationContext,train.txt), w) as f:f.writelines(line \n for line in sorted(train_list))val_list mmcv.track_progress(partial(generate_labels, detailval_detail, out_dirout_dir), val_ids)with open(osp.join(devkit_path, VOC2010/ImageSets/SegmentationContext,val.txt), w) as f:f.writelines(line \n for line in sorted(val_list))print(Done!)if __name__ __main__:main()已经在转换啦慢慢等待就好可以干点其他的或者浅休息一下。 two years later...
