diff --git a/community/cv/pointrend/maskrcnn_pointrend/src/dataset.py b/community/cv/pointrend/maskrcnn_pointrend/src/dataset.py index d96e9e45c7e41b843098576579d280b72055f17a..b3d8cf6f305b1498a3d334cb2fc88d1345880192 100644 --- a/community/cv/pointrend/maskrcnn_pointrend/src/dataset.py +++ b/community/cv/pointrend/maskrcnn_pointrend/src/dataset.py @@ -605,7 +605,6 @@ def create_maskrcnn_dataset(mindrecord_file, batch_size=2, device_num=1, rank_id ds = ds.map(operations=compose_map_func, input_columns=["image", "annotation", "mask", "mask_shape"], output_columns=["image", "image_shape", "box", "label", "valid_num", "mask"], - column_order=["image", "image_shape", "box", "label", "valid_num", "mask"], python_multiprocessing=False, num_parallel_workers=num_parallel_workers) ds = ds.batch(batch_size, drop_remainder=True, pad_info={"mask": ([config.max_instance_count, None, None], 0)}) @@ -616,7 +615,6 @@ def create_maskrcnn_dataset(mindrecord_file, batch_size=2, device_num=1, rank_id ds = ds.map(operations=compose_map_func, input_columns=["image_id", "image", "annotation", "mask", "mask_shape"], output_columns=["image_id", "image", "image_shape", "box", "label", "valid_num", "mask"], - column_order=["image_id", "image", "image_shape", "box", "label", "valid_num", "mask"], num_parallel_workers=num_parallel_workers) ds = ds.batch(batch_size, drop_remainder=True) diff --git a/research/cv/CFDT/src/dataset/dataset.py b/research/cv/CFDT/src/dataset/dataset.py index 18b7ccc4fb38efd9ffc8608af25524dec9ff85fa..3c54cd4ba90ab830a6cca0b18f3dfcb35960a60e 100644 --- a/research/cv/CFDT/src/dataset/dataset.py +++ b/research/cv/CFDT/src/dataset/dataset.py @@ -185,7 +185,6 @@ def build_dataset(cfg): partial(pad_image_to_max_size, max_size=cfg.max_img_size * 1328 // 800), input_columns=['image'], output_columns=['image', 'mask'], - column_order=['image', 'mask', 'bboxes', 'labels', 'orig_sizes', 'n_boxes', 'img_id'], num_parallel_workers=cfg.num_workers ) if cfg.eval: diff --git a/research/cv/FSAF/src/dataset.py b/research/cv/FSAF/src/dataset.py index 63b7d52fa4ce54cbbcae28c5428b3f65ab7bec0e..2c3dc9c6b6477b98ca002fda7b51669b6630bd62 100644 --- a/research/cv/FSAF/src/dataset.py +++ b/research/cv/FSAF/src/dataset.py @@ -355,7 +355,6 @@ def create_mindrecord_dataset( ds = ds.map( input_columns=["image", "annotation", "img_id"], output_columns=["image", "image_shape", "box", "label", "valid_num"], - column_order=['image', 'image_shape', 'box', 'label', 'valid_num'], operations=compose_map_func, python_multiprocessing=bool(python_multiprocessing), num_parallel_workers=config.num_parallel_workers @@ -410,7 +409,6 @@ def create_coco_det_dataset( input_columns=['image', 'bbox', 'category_id', 'iscrowd'], output_columns=['image', 'image_shape', 'box', 'label', 'valid_num'], operations=compose_map_func, - column_order=['image', 'image_shape', 'box', 'label', 'valid_num'], python_multiprocessing=python_multiprocessing, num_parallel_workers=config.num_parallel_workers ) diff --git a/research/cv/Focus-DETR/models/focus_detr/dataset.py b/research/cv/Focus-DETR/models/focus_detr/dataset.py index bc62edefd1ab77b7a12b860962b26e4ceacbb794..3d8b5268c43dbf4f9d991ad9930402587fba347e 100644 --- a/research/cv/Focus-DETR/models/focus_detr/dataset.py +++ b/research/cv/Focus-DETR/models/focus_detr/dataset.py @@ -182,7 +182,6 @@ def build_dataset(cfg): partial(pad_image_to_max_size, max_size=cfg.max_img_size), input_columns=["image"], output_columns=["image", "mask"], - column_order=["image", "mask", "bboxes", "labels", "orig_sizes", "n_boxes", "img_id"], num_parallel_workers=cfg.num_workers, ) dataset = dataset.batch(cfg.batch_size) diff --git a/research/cv/FreeAnchor/src/data/dataset.py b/research/cv/FreeAnchor/src/data/dataset.py index e0fb5b1b423f1ed4d2e5ffdbbc7c8ff4e3f6c064..e5bebdcd402fbd0795ebab2fe86188a4dfd8b683 100644 --- a/research/cv/FreeAnchor/src/data/dataset.py +++ b/research/cv/FreeAnchor/src/data/dataset.py @@ -353,7 +353,6 @@ def create_mindrecord_dataset( ds = ds.map( input_columns=["image", "annotation", "img_id"], output_columns=["image", "image_shape", "box", "label", "valid_num"], - column_order=['image', 'image_shape', 'box', 'label', 'valid_num'], operations=compose_map_func, python_multiprocessing=python_multiprocessing, num_parallel_workers=config.num_parallel_workers @@ -403,7 +402,6 @@ def create_coco_det_dataset( output_columns=[ 'image', 'image_shape', 'box', 'label', 'valid_num' ], - column_order=['image', 'image_shape', 'box', 'label', 'valid_num'], operations=compose_map_func, python_multiprocessing=python_multiprocessing, num_parallel_workers=config.num_parallel_workers diff --git a/research/cv/GridRCNN/src/dataset.py b/research/cv/GridRCNN/src/dataset.py index 32fee7dfea0defc0de1533cf509ceac694080f5c..ebd3558b43dfbee20367784e6f9a04bc93f95489 100644 --- a/research/cv/GridRCNN/src/dataset.py +++ b/research/cv/GridRCNN/src/dataset.py @@ -353,7 +353,6 @@ def create_mindrecord_dataset( ds = ds.map( input_columns=["image", "annotation", "img_id"], output_columns=["image", "image_shape", "box", "label", "valid_num"], - column_order=['image', 'image_shape', 'box', 'label', 'valid_num'], operations=compose_map_func, python_multiprocessing=python_multiprocessing, num_parallel_workers=config.num_parallel_workers @@ -403,7 +402,6 @@ def create_coco_det_dataset( output_columns=[ 'image', 'image_shape', 'box', 'label', 'valid_num' ], - column_order=['image', 'image_shape', 'box', 'label', 'valid_num'], operations=compose_map_func, python_multiprocessing=python_multiprocessing, num_parallel_workers=config.num_parallel_workers diff --git a/research/cv/PVAnet/src/dataset.py b/research/cv/PVAnet/src/dataset.py index 3443d3416392301157753b188ad5dfe2a0917c5e..0917ff2a722b34058d514e2438c2c21270f6246e 100644 --- a/research/cv/PVAnet/src/dataset.py +++ b/research/cv/PVAnet/src/dataset.py @@ -553,14 +553,12 @@ def create_fasterrcnn_dataset(config, mindrecord_file, batch_size=2, device_num= if is_training: ds = ds.map(input_columns=["image", "annotation"], output_columns=["image", "image_shape", "box", "label", "valid_num"], - column_order=["image", "image_shape", "box", "label", "valid_num"], operations=compose_map_func, python_multiprocessing=python_multiprocessing, num_parallel_workers=num_parallel_workers) ds = ds.batch(batch_size, drop_remainder=True) else: ds = ds.map(input_columns=["image", "annotation"], output_columns=["image", "image_shape", "box", "label", "valid_num"], - column_order=["image", "image_shape", "box", "label", "valid_num"], operations=compose_map_func, num_parallel_workers=num_parallel_workers) ds = ds.batch(batch_size, drop_remainder=True) diff --git a/research/cv/SPADE/src/data/__init__.py b/research/cv/SPADE/src/data/__init__.py index e123a87118175b6d64a15986c324cd0083178708..c9b9f7950b6ed1a566f0e5b4c23ed8444e8921e6 100644 --- a/research/cv/SPADE/src/data/__init__.py +++ b/research/cv/SPADE/src/data/__init__.py @@ -64,7 +64,6 @@ class DatasetInit: dataset = dataset.map(operations=[self.preprocess_input], input_columns=['label', 'instance'], output_columns=['label', 'instance', 'input_semantics'], - column_order=["label", "instance", "image", 'input_semantics'], num_parallel_workers=8) return dataset @@ -77,7 +76,6 @@ class DatasetInit: dataset = dataset.map(operations=[self.preprocess_input], input_columns=['label', 'instance'], output_columns=['label', 'instance', 'input_semantics'], - column_order=["label", "instance", "image", 'input_semantics'], num_parallel_workers=8) return dataset diff --git a/research/cv/faster_rcnn_ssod/src/dataset.py b/research/cv/faster_rcnn_ssod/src/dataset.py index 0e595578dce6f521790e99285f46608eebcc7214..8f0bd06307ae41310d85854d37a09286f686a983 100644 --- a/research/cv/faster_rcnn_ssod/src/dataset.py +++ b/research/cv/faster_rcnn_ssod/src/dataset.py @@ -353,10 +353,6 @@ def create_semisup_dataset(cfg, is_training=True): "label_gt_bboxes", "label_gt_labels", "label_gt_nums", "unlabel_img_strong", "unlabel_img_weak", "unlabel_img_metas", "unlabel_gt_bboxes", "unlabel_gt_labels", "unlabel_gt_nums"], - column_order=["label_img_strong", "label_img_weak", "label_img_metas", - "label_gt_bboxes", "label_gt_labels", "label_gt_nums", - "unlabel_img_strong", "unlabel_img_weak", "unlabel_img_metas", - "unlabel_gt_bboxes", "unlabel_gt_labels", "unlabel_gt_nums"], num_parallel_workers=cfg.num_parallel_workers) data_loader = data_loader.batch(cfg.batch_size, drop_remainder=True) data_loader = data_loader.repeat(-1) @@ -371,8 +367,6 @@ def create_semisup_dataset(cfg, is_training=True): input_columns=["label_img", "label_annos"], output_columns=["label_img_weak", "label_img_metas", "label_gt_bboxes", "label_gt_labels", "label_gt_nums"], - column_order=["label_img_weak", "label_img_metas", "label_gt_bboxes", - "label_gt_labels", "label_gt_nums", "label_img_id"], num_parallel_workers=cfg.num_parallel_workers) data_loader = data_loader.batch(cfg.test_batch_size, drop_remainder=False) diff --git a/research/cv/unisiam/train.py b/research/cv/unisiam/train.py index e009e2f5441d1574fe5c1ca654a6caf470a20b9b..81d42fa74111d54e359e3c8c28a3459084a15e43 100644 --- a/research/cv/unisiam/train.py +++ b/research/cv/unisiam/train.py @@ -93,7 +93,7 @@ def build_train_loader(args, device_num=None, rank_id=None): num_shards=device_num, shard_id=rank_id) train_dataset = train_dataset.map( operations=copy_column, input_columns=["image", "label"], output_columns=["image1", "image2", "label"], - column_order=["image1", "image2", "label"], num_parallel_workers=args.num_workers) + num_parallel_workers=args.num_workers) train_dataset = train_dataset.map(operations=train_transform, input_columns=["image1"], num_parallel_workers=args.num_workers, python_multiprocessing=True) train_dataset = train_dataset.map(operations=train_transform, input_columns=["image2"],