m53297601
/
mindspore
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

!5429 fix yolov3-resnet18&ssd bool argument parse bug and modify README

Browse Source 
Merge pull request !5429 from chengxb7532/r0.7
pull/5429/MERGE
mindspore-ci-bot 5 years ago committed by Gitee
parent 52ed1ea725 3da41e1091
commit b5393e6628
10 changed files with 306 additions and 128 deletions
Show Stats Download Patch File Download Diff File

6
model_zoo/official/cv/ssd/README.md
Unescape View File

@ -98,7 +98,7 @@ sh run_eval.sh [DATASET] [CHECKPOINT_PATH] [DEVICE_ID]
```shell ```shell
. .
└─ model_zoo └─ cv
└─ ssd └─ ssd
├─ README.md ## descriptions about SSD ├─ README.md ## descriptions about SSD
├─ scripts ├─ scripts
@ -226,7 +226,7 @@ mAP: 0.23808886505483504
| Parameters | Ascend | | Parameters | Ascend |
| -------------------------- | -------------------------------------------------------------| | -------------------------- | -------------------------------------------------------------|
| Model Version | V1 | | Model Version | SSD V1 |
| Resource | Ascend 910 ；CPU 2.60GHz，56cores；Memory，314G | | Resource | Ascend 910 ；CPU 2.60GHz，56cores；Memory，314G |
| uploaded Date | 06/01/2020 (month/day/year) | | uploaded Date | 06/01/2020 (month/day/year) |
| MindSpore Version | 0.3.0-alpha | | MindSpore Version | 0.3.0-alpha |
@ -244,7 +244,7 @@ mAP: 0.23808886505483504
| Parameters | Ascend | | Parameters | Ascend |
| ------------------- | ----------------------------| | ------------------- | ----------------------------|
| Model Version | V1 | | Model Version | SSD V1 |
| Resource | Ascend 910 | | Resource | Ascend 910 |
| Uploaded Date | 06/01/2020 (month/day/year) | | Uploaded Date | 06/01/2020 (month/day/year) |
| MindSpore Version | 0.3.0-alpha | | MindSpore Version | 0.3.0-alpha |

6
model_zoo/official/cv/ssd/scripts/run_distribute_train.sh
Unescape View File

@ -31,7 +31,7 @@ fi
# Before start distribute train, first create mindrecord files. # Before start distribute train, first create mindrecord files.
BASE_PATH=$(cd "`dirname $0`" || exit; pwd) BASE_PATH=$(cd "`dirname $0`" || exit; pwd)
cd $BASE_PATH/../ || exit cd $BASE_PATH/../ || exit
python train.py --only_create_dataset=1 python train.py --only_create_dataset=True
echo "After running the scipt, the network runs in the background. The log will be generated in LOGx/log.txt" echo "After running the scipt, the network runs in the background. The log will be generated in LOGx/log.txt"
@ -57,7 +57,7 @@ do
if [ $# == 5 ] if [ $# == 5 ]
then then
python train.py \ python train.py \
--distribute=1 \ --distribute=True \
--lr=$LR \ --lr=$LR \
--dataset=$DATASET \ --dataset=$DATASET \
--device_num=$RANK_SIZE \ --device_num=$RANK_SIZE \
@ -68,7 +68,7 @@ do
if [ $# == 7 ] if [ $# == 7 ]
then then
python train.py \ python train.py \
--distribute=1 \ --distribute=True \
--lr=$LR \ --lr=$LR \
--dataset=$DATASET \ --dataset=$DATASET \
--device_num=$RANK_SIZE \ --device_num=$RANK_SIZE \

11
model_zoo/official/cv/ssd/train.py
Unescape View File

@ -17,6 +17,7 @@
import os import os
import argparse import argparse
import ast
import mindspore.nn as nn import mindspore.nn as nn
from mindspore import context, Tensor from mindspore import context, Tensor
from mindspore.communication.management import init from mindspore.communication.management import init
@ -32,9 +33,10 @@ from src.init_params import init_net_param, filter_checkpoint_parameter
def main(): def main():
parser = argparse.ArgumentParser(description="SSD training") parser = argparse.ArgumentParser(description="SSD training")
parser.add_argument("--only_create_dataset", type=bool, default=False, help="If set it true, only create " parser.add_argument("--only_create_dataset", type=ast.literal_eval, default=False,
"Mindrecord, default is False.") help="If set it true, only create Mindrecord, default is False.")
parser.add_argument("--distribute", type=bool, default=False, help="Run distribute, default is False.") parser.add_argument("--distribute", type=ast.literal_eval, default=False,
help="Run distribute, default is False.")
parser.add_argument("--device_id", type=int, default=0, help="Device id, default is 0.") parser.add_argument("--device_id", type=int, default=0, help="Device id, default is 0.")
parser.add_argument("--device_num", type=int, default=1, help="Use device nums, default is 1.") parser.add_argument("--device_num", type=int, default=1, help="Use device nums, default is 1.")
parser.add_argument("--lr", type=float, default=0.05, help="Learning rate, default is 0.05.") parser.add_argument("--lr", type=float, default=0.05, help="Learning rate, default is 0.05.")
@ -46,7 +48,8 @@ def main():
parser.add_argument("--pre_trained_epoch_size", type=int, default=0, help="Pretrained epoch size.") parser.add_argument("--pre_trained_epoch_size", type=int, default=0, help="Pretrained epoch size.")
parser.add_argument("--save_checkpoint_epochs", type=int, default=10, help="Save checkpoint epochs, default is 10.") parser.add_argument("--save_checkpoint_epochs", type=int, default=10, help="Save checkpoint epochs, default is 10.")
parser.add_argument("--loss_scale", type=int, default=1024, help="Loss scale, default is 1024.") parser.add_argument("--loss_scale", type=int, default=1024, help="Loss scale, default is 1024.")
parser.add_argument("--filter_weight", type=bool, default=False, help="Filter weight parameters, default is False.") parser.add_argument("--filter_weight", type=ast.literal_eval, default=False,
help="Filter weight parameters, default is False.")
args_opt = parser.parse_args() args_opt = parser.parse_args()
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", device_id=args_opt.device_id) context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", device_id=args_opt.device_id)

279
model_zoo/official/cv/yolov3_darknet53_quant/README.md
View File

File diff suppressed because it is too large Load Diff

18
model_zoo/official/cv/yolov3_darknet53_quant/eval.py
Unescape View File

@ -210,20 +210,22 @@ def parse_args():
parser = argparse.ArgumentParser('mindspore coco testing') parser = argparse.ArgumentParser('mindspore coco testing')
# dataset related # dataset related
parser.add_argument('--data_dir', type=str, default='', help='train data dir') parser.add_argument('--data_dir', type=str, default="", help='Train data dir. Default: ""')
parser.add_argument('--per_batch_size', default=1, type=int, help='batch size for per gpu') parser.add_argument('--per_batch_size', default=1, type=int, help='Batch size for per device, Default: 1')
# network related # network related
parser.add_argument('--pretrained', default='', type=str, help='model_path, local pretrained model to load') parser.add_argument('--pretrained', default="", type=str,\
help='The model path, local pretrained model to load, Default: ""')
# logging related # logging related
parser.add_argument('--log_path', type=str, default='outputs/', help='checkpoint save location') parser.add_argument('--log_path', type=str, default="outputs/", help='Log save location, Default: "outputs/"')
# detect_related # detect_related
parser.add_argument('--nms_thresh', type=float, default=0.5, help='threshold for NMS') parser.add_argument('--nms_thresh', type=float, default=0.5, help='Threshold for NMS. Default: 0.5')
parser.add_argument('--annFile', type=str, default='', help='path to annotation') parser.add_argument('--annFile', type=str, default="", help='The path to annotation. Default: ""')
parser.add_argument('--testing_shape', type=str, default='', help='shape for test ') parser.add_argument('--testing_shape', type=str, default="", help='Shape for test. Default: ""')
parser.add_argument('--ignore_threshold', type=float, default=0.001, help='threshold to throw low quality boxes') parser.add_argument('--ignore_threshold', type=float, default=0.001,\
help='Threshold to throw low quality boxes, Default: 0.001')
args, _ = parser.parse_known_args() args, _ = parser.parse_known_args()

85
model_zoo/official/cv/yolov3_darknet53_quant/train.py
Unescape View File

@ -12,7 +12,7 @@
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # limitations under the License.
# ============================================================================ # ============================================================================
"""YoloV3 train.""" """YoloV3-Darknet53-Quant train."""
import os import os
import time import time
@ -32,7 +32,7 @@ from mindspore.train.quant import quant
from src.yolo import YOLOV3DarkNet53, YoloWithLossCell, TrainingWrapper from src.yolo import YOLOV3DarkNet53, YoloWithLossCell, TrainingWrapper
from src.logger import get_logger from src.logger import get_logger
from src.util import AverageMeter, load_backbone, get_param_groups from src.util import AverageMeter, get_param_groups
from src.lr_scheduler import warmup_step_lr, warmup_cosine_annealing_lr, \ from src.lr_scheduler import warmup_step_lr, warmup_cosine_annealing_lr, \
warmup_cosine_annealing_lr_V2, warmup_cosine_annealing_lr_sample warmup_cosine_annealing_lr_V2, warmup_cosine_annealing_lr_sample
from src.yolo_dataset import create_yolo_dataset from src.yolo_dataset import create_yolo_dataset
@ -52,53 +52,60 @@ def parse_args():
parser = argparse.ArgumentParser('mindspore coco training') parser = argparse.ArgumentParser('mindspore coco training')
# dataset related # dataset related
parser.add_argument('--data_dir', type=str, default='', help='train data dir') parser.add_argument('--data_dir', type=str, default='', help='Train data dir. Default: ""')
parser.add_argument('--per_batch_size', default=32, type=int, help='batch size for per gpu') parser.add_argument('--per_batch_size', default=16, type=int, help='Batch size for per device. Default: 16')
# network related # network related
parser.add_argument('--pretrained_backbone', default='', type=str, help='model_path, local pretrained backbone' parser.add_argument('--resume_yolov3', default='', type=str,\
' model to load') help='The ckpt file of yolov3-darknet53, which used to yolov3-darknet53 quant. Default: ""')
parser.add_argument('--resume_yolov3', default='', type=str, help='path of pretrained yolov3')
# optimizer and lr related # optimizer and lr related
parser.add_argument('--lr_scheduler', default='exponential', type=str, parser.add_argument('--lr_scheduler', default='exponential', type=str,\
help='lr-scheduler, option type: exponential, cosine_annealing') help='Learning rate scheduler, option type: exponential, '
parser.add_argument('--lr', default=0.001, type=float, help='learning rate of the training') 'cosine_annealing. Default: exponential')
parser.add_argument('--lr_epochs', type=str, default='220,250', help='epoch of lr changing') parser.add_argument('--lr', default=0.012, type=float, help='Learning rate of the training')
parser.add_argument('--lr_gamma', type=float, default=0.1, parser.add_argument('--lr_epochs', type=str, default='92,105',\
help='decrease lr by a factor of exponential lr_scheduler') help='Epoch of lr changing. Default: 92,105')
parser.add_argument('--eta_min', type=float, default=0., help='eta_min in cosine_annealing scheduler') parser.add_argument('--lr_gamma', type=float, default=0.1,\
parser.add_argument('--T_max', type=int, default=320, help='T-max in cosine_annealing scheduler') help='Decrease lr by a factor of exponential lr_scheduler. Default: 0.1')
parser.add_argument('--max_epoch', type=int, default=320, help='max epoch num to train the model') parser.add_argument('--eta_min', type=float, default=0.,\
parser.add_argument('--warmup_epochs', default=0, type=float, help='warmup epoch') help='Eta_min in cosine_annealing scheduler. Default: 0.')
parser.add_argument('--weight_decay', type=float, default=0.0005, help='weight decay') parser.add_argument('--T_max', type=int, default=135,\
parser.add_argument('--momentum', type=float, default=0.9, help='momentum') help='T-max in cosine_annealing scheduler. Default: 135')
parser.add_argument('--max_epoch', type=int, default=135,\
help='Max epoch num to train the model. Default: 135')
parser.add_argument('--warmup_epochs', type=float, default=0, help='Warmup epochs. Default: 0')
parser.add_argument('--weight_decay', type=float, default=0.0005, help='Weight decay. Default: 0.0005')
parser.add_argument('--momentum', type=float, default=0.9, help='Momentum. Default: 0.9')
# loss related # loss related
parser.add_argument('--loss_scale', type=int, default=1024, help='static loss scale') parser.add_argument('--loss_scale', type=int, default=1024, help='Static loss scale. Default: 1024')
parser.add_argument('--label_smooth', type=int, default=0, help='whether to use label smooth in CE') parser.add_argument('--label_smooth', type=int, default=0, help='Whether to use label smooth in CE. Default: 0')
parser.add_argument('--label_smooth_factor', type=float, default=0.1, help='smooth strength of original one-hot') parser.add_argument('--label_smooth_factor', type=float, default=0.1,\
help='Smooth strength of original one-hot. Default: 0.1')
# logging related # logging related
parser.add_argument('--log_interval', type=int, default=100, help='logging interval') parser.add_argument('--log_interval', type=int, default=100, help='Logging interval steps. Default: 100')
parser.add_argument('--ckpt_path', type=str, default='outputs/', help='checkpoint save location') parser.add_argument('--ckpt_path', type=str, default='outputs/',\
parser.add_argument('--ckpt_interval', type=int, default=None, help='ckpt_interval') help='Checkpoint save location. Default: "outputs/"')
parser.add_argument('--is_save_on_master', type=int, default=1, help='save ckpt on master or all rank') parser.add_argument('--ckpt_interval', type=int, default=None, help='Save checkpoint interval. Default: None')
parser.add_argument('--is_save_on_master', type=int, default=1,\
help='Save ckpt on master or all rank, 1 for master, 0 for all ranks. Default: 1')
# distributed related # distributed related
parser.add_argument('--is_distributed', type=int, default=1, help='if multi device') parser.add_argument('--is_distributed', type=int, default=0,\
parser.add_argument('--rank', type=int, default=0, help='local rank of distributed') help='Distribute train or not, 1 for yes, 0 for no. Default: 0')
parser.add_argument('--group_size', type=int, default=1, help='world size of distributed') parser.add_argument('--rank', type=int, default=0, help='Local rank of distributed, Default: 0')
parser.add_argument('--group_size', type=int, default=1, help='World size of device, Default: 1')
# roma obs
parser.add_argument('--train_url', type=str, default="", help='train url')
# profiler init # profiler init
parser.add_argument('--need_profiler', type=int, default=0, help='whether use profiler') parser.add_argument('--need_profiler', type=int, default=0,\
help='Whether use profiler, 1 for yes, 0 for no, Default: 0')
# reset default config # reset default config
parser.add_argument('--training_shape', type=str, default="", help='fix training shape') parser.add_argument('--training_shape', type=str, default="", help='Fix training shape. Default: ""')
parser.add_argument('--resize_rate', type=int, default=None, help='resize rate for multi-scale training') parser.add_argument('--resize_rate', type=int, default=None,\
help='Resize rate for multi-scale training. Default: None')
args, _ = parser.parse_known_args() args, _ = parser.parse_known_args()
if args.lr_scheduler == 'cosine_annealing' and args.max_epoch > args.T_max: if args.lr_scheduler == 'cosine_annealing' and args.max_epoch > args.T_max:
@ -141,7 +148,7 @@ def train():
args.logger.save_args(args) args.logger.save_args(args)
if args.need_profiler: if args.need_profiler:
from mindinsight.profiler.profiling import Profiler from mindspore.profiler.profiling import Profiler
profiler = Profiler(output_path=args.outputs_dir, is_detail=True, is_show_op_path=True) profiler = Profiler(output_path=args.outputs_dir, is_detail=True, is_show_op_path=True)
loss_meter = AverageMeter('loss') loss_meter = AverageMeter('loss')
@ -159,12 +166,6 @@ def train():
# default is kaiming-normal # default is kaiming-normal
default_recurisive_init(network) default_recurisive_init(network)
if args.pretrained_backbone:
network = load_backbone(network, args.pretrained_backbone, args)
args.logger.info('load pre-trained backbone {} into network'.format(args.pretrained_backbone))
else:
args.logger.info('Not load pre-trained backbone, please be careful')
if args.resume_yolov3: if args.resume_yolov3:
param_dict = load_checkpoint(args.resume_yolov3) param_dict = load_checkpoint(args.resume_yolov3)
param_dict_new = {} param_dict_new = {}

10
model_zoo/official/cv/yolov3_resnet18/README.md
Unescape View File

@ -96,7 +96,7 @@ After installing MindSpore via the official website, you can start training and
## [Script and Sample Code](#contents) ## [Script and Sample Code](#contents)
``` ```
└── model_zoo └── cv
├── README.md // descriptions about all the models ├── README.md // descriptions about all the models
└── yolov3_resnet18 └── yolov3_resnet18
├── README.md // descriptions about yolov3_resnet18 ├── README.md // descriptions about yolov3_resnet18
@ -118,9 +118,9 @@ After installing MindSpore via the official website, you can start training and
``` ```
Major parameters in train.py and config.py as follows: Major parameters in train.py and config.py as follows:
evice_num: Use device nums, default is 1. device_num: Use device nums, default is 1.
lr: Learning rate, default is 0.001. lr: Learning rate, default is 0.001.
epoch_size: Epoch size, default is 10. epoch_size: Epoch size, default is 50.
batch_size: Batch size, default is 32. batch_size: Batch size, default is 32.
pre_trained: Pretrained Checkpoint file path. pre_trained: Pretrained Checkpoint file path.
pre_trained_epoch_size: Pretrained epoch size. pre_trained_epoch_size: Pretrained epoch size.
@ -201,7 +201,7 @@ Note the precision and recall values are results of two-classification(person an
| Parameters | Ascend | | Parameters | Ascend |
| -------------------------- | ----------------------------------------------------------- | | -------------------------- | ----------------------------------------------------------- |
| Model Version | Inception V1 | | Model Version | YOLOv3_Resnet18 V1 |
| Resource | Ascend 910 ；CPU 2.60GHz，56cores；Memory，314G | | Resource | Ascend 910 ；CPU 2.60GHz，56cores；Memory，314G |
| uploaded Date | 06/01/2020 (month/day/year) | | uploaded Date | 06/01/2020 (month/day/year) |
| MindSpore Version | 0.2.0-alpha | | MindSpore Version | 0.2.0-alpha |
@ -220,7 +220,7 @@ Note the precision and recall values are results of two-classification(person an
| Parameters | Ascend | | Parameters | Ascend |
| ------------------- | ----------------------------------------------- | | ------------------- | ----------------------------------------------- |
| Model Version | Inception V1 | | Model Version | YOLOv3_Resnet18 V1 |
| Resource | Ascend 910 | | Resource | Ascend 910 |
| Uploaded Date | 06/01/2020 (month/day/year) | | Uploaded Date | 06/01/2020 (month/day/year) |
| MindSpore Version | 0.2.0-alpha | | MindSpore Version | 0.2.0-alpha |

2
model_zoo/official/cv/yolov3_resnet18/eval.py
Unescape View File

@ -13,7 +13,7 @@
# limitations under the License. # limitations under the License.
# ============================================================================ # ============================================================================
"""Evaluation for yolo_v3""" """Evaluation for yolov3-resnet18"""
import os import os
import argparse import argparse
import time import time

6
model_zoo/official/cv/yolov3_resnet18/scripts/run_distribute_train.sh
Unescape View File

@ -40,7 +40,7 @@ BASE_PATH=$(cd "`dirname $0`" || exit; pwd)
cd $BASE_PATH/../ || exit cd $BASE_PATH/../ || exit
# Before start distribute train, first create mindrecord files. # Before start distribute train, first create mindrecord files.
python train.py --only_create_dataset=1 --mindrecord_dir=$MINDRECORD_DIR --image_dir=$IMAGE_DIR \ python train.py --only_create_dataset=True --mindrecord_dir=$MINDRECORD_DIR --image_dir=$IMAGE_DIR \
--anno_path=$ANNO_PATH --anno_path=$ANNO_PATH
if [ $? -ne 0 ] if [ $? -ne 0 ]
then then
@ -72,7 +72,7 @@ do
if [ $# == 6 ] if [ $# == 6 ]
then then
taskset -c $cmdopt python train.py \ taskset -c $cmdopt python train.py \
--distribute=1 \ --distribute=True \
--lr=0.005 \ --lr=0.005 \
--device_num=$RANK_SIZE \ --device_num=$RANK_SIZE \
--device_id=$DEVICE_ID \ --device_id=$DEVICE_ID \
@ -85,7 +85,7 @@ do
if [ $# == 8 ] if [ $# == 8 ]
then then
taskset -c $cmdopt python train.py \ taskset -c $cmdopt python train.py \
--distribute=1 \ --distribute=True \
--lr=0.005 \ --lr=0.005 \
--device_num=$RANK_SIZE \ --device_num=$RANK_SIZE \
--device_id=$DEVICE_ID \ --device_id=$DEVICE_ID \

11
model_zoo/official/cv/yolov3_resnet18/train.py
Unescape View File

@ -24,6 +24,7 @@ Note if mindrecord_dir isn't empty, it will use mindrecord_dir rather than image
import os import os
import argparse import argparse
import ast
import numpy as np import numpy as np
import mindspore.nn as nn import mindspore.nn as nn
from mindspore import context, Tensor from mindspore import context, Tensor
@ -61,21 +62,21 @@ def init_net_param(network, init_value='ones'):
def main(): def main():
parser = argparse.ArgumentParser(description="YOLOv3 train") parser = argparse.ArgumentParser(description="YOLOv3 train")
parser.add_argument("--only_create_dataset", type=bool, default=False, help="If set it true, only create " parser.add_argument("--only_create_dataset", type=ast.literal_eval, default=False,
"Mindrecord, default is false.") help="If set it true, only create Mindrecord, default is False.")
parser.add_argument("--distribute", type=bool, default=False, help="Run distribute, default is false.") parser.add_argument("--distribute", type=ast.literal_eval, default=False, help="Run distribute, default is False.")
parser.add_argument("--device_id", type=int, default=0, help="Device id, default is 0.") parser.add_argument("--device_id", type=int, default=0, help="Device id, default is 0.")
parser.add_argument("--device_num", type=int, default=1, help="Use device nums, default is 1.") parser.add_argument("--device_num", type=int, default=1, help="Use device nums, default is 1.")
parser.add_argument("--lr", type=float, default=0.001, help="Learning rate, default is 0.001.") parser.add_argument("--lr", type=float, default=0.001, help="Learning rate, default is 0.001.")
parser.add_argument("--mode", type=str, default="sink", help="Run sink mode or not, default is sink") parser.add_argument("--mode", type=str, default="sink", help="Run sink mode or not, default is sink")
parser.add_argument("--epoch_size", type=int, default=10, help="Epoch size, default is 10") parser.add_argument("--epoch_size", type=int, default=50, help="Epoch size, default is 50")
parser.add_argument("--batch_size", type=int, default=32, help="Batch size, default is 32.") parser.add_argument("--batch_size", type=int, default=32, help="Batch size, default is 32.")
parser.add_argument("--pre_trained", type=str, default=None, help="Pretrained checkpoint file path") parser.add_argument("--pre_trained", type=str, default=None, help="Pretrained checkpoint file path")
parser.add_argument("--pre_trained_epoch_size", type=int, default=0, help="Pretrained epoch size") parser.add_argument("--pre_trained_epoch_size", type=int, default=0, help="Pretrained epoch size")
parser.add_argument("--save_checkpoint_epochs", type=int, default=5, help="Save checkpoint epochs, default is 5.") parser.add_argument("--save_checkpoint_epochs", type=int, default=5, help="Save checkpoint epochs, default is 5.")
parser.add_argument("--loss_scale", type=int, default=1024, help="Loss scale, default is 1024.") parser.add_argument("--loss_scale", type=int, default=1024, help="Loss scale, default is 1024.")
parser.add_argument("--mindrecord_dir", type=str, default="./Mindrecord_train", parser.add_argument("--mindrecord_dir", type=str, default="./Mindrecord_train",
help="Mindrecord directory. If the mindrecord_dir is empty, it wil generate mindrecord file by" help="Mindrecord directory. If the mindrecord_dir is empty, it wil generate mindrecord file by "
"image_dir and anno_path. Note if mindrecord_dir isn't empty, it will use mindrecord_dir " "image_dir and anno_path. Note if mindrecord_dir isn't empty, it will use mindrecord_dir "
"rather than image_dir and anno_path. Default is ./Mindrecord_train") "rather than image_dir and anno_path. Default is ./Mindrecord_train")
parser.add_argument("--image_dir", type=str, default="", help="Dataset directory, " parser.add_argument("--image_dir", type=str, default="", help="Dataset directory, "

Write Preview
Loading…
Cancel
Save