66import os
77import json
88from collections import OrderedDict
9- import torch
10- import sys
119import detectron2 .utils .comm as comm
1210from detectron2 .checkpoint import DetectionCheckpointer
1311from detectron2 .config import get_cfg
1412
15- from detectron2 .data import MetadataCatalog , DatasetCatalog
1613from detectron2 .data .datasets import register_coco_instances
1714
1815from detectron2 .engine import DefaultTrainer , default_argument_parser , default_setup , hooks , launch
1916from detectron2 .evaluation import (
2017 COCOEvaluator ,
21- DatasetEvaluators ,
22- SemSegEvaluator ,
2318 verify_results ,
2419)
2520from detectron2 .modeling import GeneralizedRCNNWithTTA
@@ -114,6 +109,9 @@ def main(args):
114109 pd .DataFrame (res ).to_csv (f'{ cfg .OUTPUT_DIR } /eval.csv' )
115110 return res
116111
112+ # Ensure that the Output directory exists
113+ os .makedirs (cfg .OUTPUT_DIR , exist_ok = True )
114+
117115 """
118116 If you'd like to do anything fancier than the standard training logic,
119117 consider writing your own training loop (see plain_train_net.py) or
@@ -135,22 +133,22 @@ def main(args):
135133 parser = default_argument_parser ()
136134
137135 # Extra Configurations for dataset names and paths
138- parser .add_argument ("--dataset_name" , default = "" , help = "The Dataset Name" )
136+ parser .add_argument ("--dataset_name" , default = "" , help = "The Dataset Name" )
139137 parser .add_argument ("--json_annotation_train" , default = "" , metavar = "FILE" , help = "The path to the training set JSON annotation" )
140- parser .add_argument ("--image_path_train" , default = "" , metavar = "FILE" , help = "The path to the training set image folder" )
141- parser .add_argument ("--json_annotation_val" , default = "" , metavar = "FILE" , help = "The path to the validation set JSON annotation" )
142- parser .add_argument ("--image_path_val" , default = "" , metavar = "FILE" , help = "The path to the validation set image folder" )
138+ parser .add_argument ("--image_path_train" , default = "" , metavar = "FILE" , help = "The path to the training set image folder" )
139+ parser .add_argument ("--json_annotation_val" , default = "" , metavar = "FILE" , help = "The path to the validation set JSON annotation" )
140+ parser .add_argument ("--image_path_val" , default = "" , metavar = "FILE" , help = "The path to the validation set image folder" )
143141
144142 args = parser .parse_args ()
145143 print ("Command Line Args:" , args )
146-
144+
147145 # Register Datasets
148146 dataset_name = args .dataset_name
149147 register_coco_instances (f"{ dataset_name } -train" , {},
150148 args .json_annotation_train ,
151149 args .image_path_train )
152150
153- register_coco_instances (f"{ dataset_name } -val" , {},
151+ register_coco_instances (f"{ dataset_name } -val" , {},
154152 args .json_annotation_val ,
155153 args .image_path_val )
156154
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