Spaces:
Runtime error
Runtime error
File size: 9,730 Bytes
5e0b9df |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 |
# ------------------------------------------------------------------------
# HOTR official code : engine/arg_parser.py
# Copyright (c) Kakao Brain, Inc. and its affiliates. All Rights Reserved
# Modified arguments are represented with *
# ------------------------------------------------------------------------
# Modified from DETR (https://github.com/facebookresearch/detr)
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
# ------------------------------------------------------------------------
import argparse
import hotr.util.misc as utils
def get_args_parser():
parser = argparse.ArgumentParser('Set transformer detector', add_help=False)
parser.add_argument('--lr', default=1e-4, type=float)
parser.add_argument('--lr_backbone', default=1e-5, type=float)
parser.add_argument('--batch_size', default=2, type=int)
parser.add_argument('--weight_decay', default=1e-4, type=float)
parser.add_argument('--epochs', default=100, type=int)
parser.add_argument('--lr_drop', default=80, type=int)
parser.add_argument('--clip_max_norm', default=0.1, type=float,
help='gradient clipping max norm')
# DETR Model parameters
parser.add_argument('--frozen_weights', type=str, default=None,
help="Path to the pretrained model. If set, only the mask head will be trained")
parser.add_argument('--pretrain_interaction_tf', type=str, default=None,
help="Path to the pretrained model. If set, only the mask head will be trained")
# DETR Backbone
parser.add_argument('--backbone', default='resnet50', type=str,
help="Name of the convolutional backbone to use")
parser.add_argument('--dilation', action='store_true',
help="If true, we replace stride with dilation in the last convolutional block (DC5)")
parser.add_argument('--position_embedding', default='sine', type=str, choices=('sine', 'learned'),
help="Type of positional embedding to use on top of the image features")
# DETR Transformer (= Encoder, Instance Decoder)
parser.add_argument('--enc_layers', default=6, type=int,
help="Number of encoding layers in the transformer")
parser.add_argument('--dec_layers', default=6, type=int,
help="Number of decoding layers in the transformer")
parser.add_argument('--dim_feedforward', default=2048, type=int,
help="Intermediate size of the feedforward layers in the transformer blocks")
parser.add_argument('--hidden_dim', default=256, type=int,
help="Size of the embeddings (dimension of the transformer)")
parser.add_argument('--dropout', default=0.1, type=float,
help="Dropout applied in the transformer")
parser.add_argument('--nheads', default=8, type=int,
help="Number of attention heads inside the transformer's attentions")
parser.add_argument('--num_queries', default=100, type=int,
help="Number of query slots")
parser.add_argument('--pre_norm', action='store_true')
parser.add_argument('--decoder_form', default=2, type=int,
help="1-decoder or 2-decoder")
# Segmentation
parser.add_argument('--masks', action='store_true',
help="Train segmentation head if the flag is provided")
# Loss Option
parser.add_argument('--no_aux_loss', dest='aux_loss', action='store_false',
help="Disables auxiliary decoding losses (loss at each layer)")
# Loss coefficients (DETR)
parser.add_argument('--mask_loss_coef', default=1, type=float)
parser.add_argument('--dice_loss_coef', default=1, type=float)
parser.add_argument('--bbox_loss_coef', default=5, type=float)
parser.add_argument('--giou_loss_coef', default=2, type=float)
parser.add_argument('--eos_coef', default=0.1, type=float,
help="Relative classification weight of the no-object class")
# Matcher (DETR)
parser.add_argument('--set_cost_class', default=1, type=float,
help="Class coefficient in the matching cost")
parser.add_argument('--set_cost_bbox', default=5, type=float,
help="L1 box coefficient in the matching cost")
parser.add_argument('--set_cost_giou', default=2, type=float,
help="giou box coefficient in the matching cost")
# * HOI Detection
parser.add_argument('--HOIDet', action='store_true',
help="Train HOI Detection head if the flag is provided")
parser.add_argument('--share_enc', action='store_true',
help="Share the Encoder in DETR for HOI Detection if the flag is provided")
parser.add_argument('--pretrained_dec', action='store_true',
help="Use Pre-trained Decoder in DETR for Interaction Decoder if the flag is provided")
parser.add_argument('--hoi_enc_layers', default=1, type=int,
help="Number of decoding layers in HOI transformer")
parser.add_argument('--hoi_dec_layers', default=1, type=int,
help="Number of decoding layers in HOI transformer")
parser.add_argument('--hoi_nheads', default=8, type=int,
help="Number of decoding layers in HOI transformer")
parser.add_argument('--hoi_dim_feedforward', default=2048, type=int,
help="Number of decoding layers in HOI transformer")
# parser.add_argument('--hoi_mode', type=str, default=None, help='[inst | pair | all]')
parser.add_argument('--num_hoi_queries', default=100, type=int,
help="Number of Queries for Interaction Decoder")
parser.add_argument('--hoi_aux_loss', action='store_true')
# * HOTR Matcher
parser.add_argument('--set_cost_idx', default=1, type=float,
help="IDX coefficient in the matching cost")
parser.add_argument('--set_cost_act', default=1, type=float,
help="Action coefficient in the matching cost")
parser.add_argument('--set_cost_tgt', default=1, type=float,
help="Target coefficient in the matching cost")
# * HOTR Loss coefficients
parser.add_argument('--temperature', default=0.05, type=float, help="temperature")
parser.add_argument('--hoi_consistency_loss_coef', default=1, type=float)
parser.add_argument('--hoi_idx_loss_coef', default=1, type=float)
parser.add_argument('--hoi_idx_consistency_loss_coef', default=1, type=float)
parser.add_argument('--hoi_act_loss_coef', default=1, type=float)
parser.add_argument('--hoi_act_consistency_loss_coef', default=1, type=float)
parser.add_argument('--hoi_tgt_loss_coef', default=1, type=float)
parser.add_argument('--hoi_tgt_consistency_loss_coef', default=1, type=float)
parser.add_argument('--hoi_eos_coef', default=0.1, type=float, help="Relative classification weight of the no-object class")
parser.add_argument('--ramp_down_epoch',default=10000,type=int)
parser.add_argument('--ramp_up_epoch',default=0,type=int)
#consistency
parser.add_argument('--use_consis',action='store_true',help='use consistency regularization')
parser.add_argument('--share_dec_param',action='store_true',help = 'share decoder parameters of all stages')
parser.add_argument("--augpath_name", type=utils.arg_as_list,default=[],
help='choose which augmented inference paths to use. (p2:x->HO->I,p3:x->HI->O,p4:x->OI->H)')
parser.add_argument('--stop_grad_stage',action='store_true',help='Do not back propogate loss to previous stage')
parser.add_argument('--path_id', default=0, type=int)
parser.add_argument('--sep_enc_forward',action='store_true')
# * dataset parameters
parser.add_argument('--dataset_file', help='[coco | vcoco]')
parser.add_argument('--data_path', type=str)
parser.add_argument('--object_threshold', type=float, default=0, help='Threshold for object confidence')
# machine parameters
parser.add_argument('--output_dir', default='',
help='path where to save, empty for no saving')
parser.add_argument('--custom_path', default='',
help="Data path for custom inference. Only required for custom_main.py")
parser.add_argument('--device', default='cuda',
help='device to use for training / testing')
parser.add_argument('--seed', default=42, type=int)
parser.add_argument('--resume', default='', help='resume from checkpoint')
parser.add_argument('--start_epoch', default=0, type=int, metavar='N',
help='start epoch')
parser.add_argument('--num_workers', default=2, type=int)
# mode
parser.add_argument('--eval', action='store_true', help="Only evaluate results if the flag is provided")
parser.add_argument('--validate', action='store_true', help="Validate after every epoch")
# distributed training parameters
parser.add_argument('--world_size', default=1, type=int,
help='number of distributed processes')
parser.add_argument('--dist_url', default='env://', help='url used to set up distributed training')
# * WanDB
parser.add_argument('--wandb', action='store_true')
parser.add_argument('--project_name', default='hotr_cpc')
parser.add_argument('--group_name', default='mlv')
parser.add_argument('--run_name', default='run_000001')
return parser
|