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Functions379 in github.com/chengyangfu/retinamask

⨍ Functions 379◇ Types & classes 84
Method__call__
Arguments: boxlists (list[BoxList])
maskrcnn_benchmark/modeling/poolers.py:31
Method__call__
Args: match_quality_matrix (Tensor[float]): an MxN tensor, containing the pairwise quality between M ground-truth ele
maskrcnn_benchmark/modeling/matcher.py:44
Method__call__
Arguments: matched idxs: list of tensors containing -1, 0 or positive values. Each tensor corresponds to a specif
maskrcnn_benchmark/modeling/balanced_positive_negative_sampler.py:19
Method__call__
Computes the loss for Faster R-CNN. This requires that the subsample method has been called beforehand. Arguments:
maskrcnn_benchmark/modeling/roi_heads/box_head/loss.py:111
Method__call__
Arguments: proposals (list[BoxList]) mask_logits (Tensor) targets (list[BoxList]) Return:
maskrcnn_benchmark/modeling/roi_heads/mask_head/loss.py:104
Method__call__
(self, masks, boxes)
maskrcnn_benchmark/modeling/roi_heads/mask_head/inference.py:177
Method__call__
Arguments: anchors (list[BoxList]) objectness (list[Tensor]) box_regression (list[Tensor]) ta
maskrcnn_benchmark/modeling/rpn/loss.py:78
Method__call__
Arguments: anchors (list[BoxList]) objectness (list[Tensor]) box_regression (list[Tensor]) ta
maskrcnn_benchmark/modeling/rpn/retinanet_loss.py:95
Method__call__
(self, batch)
maskrcnn_benchmark/data/collate_batch.py:15
Method__call__
(self, image, target)
maskrcnn_benchmark/data/transforms/transforms.py:13
Method__call__
(self, image, target)
maskrcnn_benchmark/data/transforms/transforms.py:55
Method__call__
(self, image, target)
maskrcnn_benchmark/data/transforms/transforms.py:68
Method__call__
(self, image, target)
maskrcnn_benchmark/data/transforms/transforms.py:79
Method__call__
(self, image, target)
maskrcnn_benchmark/data/transforms/transforms.py:87
Method__call__
(self, image, target)
maskrcnn_benchmark/data/transforms/transforms.py:97
Method__getattr__
(self, attr)
maskrcnn_benchmark/utils/metric_logger.py:52
Method__getitem__
(self, item)
maskrcnn_benchmark/data/datasets/list_dataset.py:16
Method__getitem__
(self, idx)
maskrcnn_benchmark/data/datasets/coco.py:35
Method__getitem__
(self, item)
maskrcnn_benchmark/structures/segmentation_mask.py:192
Method__getitem__
(self, item)
maskrcnn_benchmark/structures/bounding_box.py:205
Method__init__
Arguments: k_min (int) k_max (int) canonical_scale (int) canonical_level (int) ep
maskrcnn_benchmark/modeling/poolers.py:16
Method__init__
Arguments: output_size (list[tuple[int]] or list[int]): output size for the pooled region scales (list[float]): scale
maskrcnn_benchmark/modeling/poolers.py:55
Method__init__
Args: high_threshold (float): quality values greater than or equal to this value are candidate matches.
maskrcnn_benchmark/modeling/matcher.py:23
Method__init__
Arguments: batch_size_per_image (int): number of elements to be selected per image positive_fraction (float): percent
maskrcnn_benchmark/modeling/balanced_positive_negative_sampler.py:10
Method__init__
Arguments: weights (4-element tuple) bbox_xform_clip (float)
maskrcnn_benchmark/modeling/box_coder.py:13
Method__init__
(self, out_channels)
maskrcnn_benchmark/modeling/backbone/fpn.py:104
Method__init__
( self, block_module, stages, num_groups=1, width_per_group=64,
maskrcnn_benchmark/modeling/backbone/resnet.py:125
Method__init__
( self, in_channels, bottleneck_channels, out_channels, num_groups=1,
maskrcnn_benchmark/modeling/backbone/resnet.py:200
Method__init__
(self, cfg)
maskrcnn_benchmark/modeling/backbone/resnet.py:275
Method__init__
(self, cfg, heads)
maskrcnn_benchmark/modeling/roi_heads/roi_heads.py:14
Method__init__
(self, cfg)
maskrcnn_benchmark/modeling/roi_heads/box_head/box_head.py:16
Method__init__
Arguments: proposal_matcher (Matcher) fg_bg_sampler (BalancedPositiveNegativeSampler) box_coder (BoxCoder
maskrcnn_benchmark/modeling/roi_heads/box_head/loss.py:21
Method__init__
(self, config, pretrained=None)
maskrcnn_benchmark/modeling/roi_heads/box_head/roi_box_predictors.py:6
Method__init__
Arguments: score_thresh (float) nms (float) detections_per_img (int) box_coder (BoxCoder)
maskrcnn_benchmark/modeling/roi_heads/box_head/inference.py:19
Method__init__
(self, config)
maskrcnn_benchmark/modeling/roi_heads/box_head/roi_box_feature_extractors.py:10
Method__init__
Arguments: proposal_matcher (Matcher) discretization_size (int)
maskrcnn_benchmark/modeling/roi_heads/mask_head/loss.py:48
Method__init__
Arguments: num_classes (int): number of output classes input_size (int): number of channels of the input once it's fl
maskrcnn_benchmark/modeling/roi_heads/mask_head/roi_mask_feature_extractors.py:15
Method__init__
(self, cfg)
maskrcnn_benchmark/modeling/roi_heads/mask_head/mask_head.py:37
Method__init__
(self, masker=None)
maskrcnn_benchmark/modeling/roi_heads/mask_head/inference.py:23
Method__init__
(self, cfg)
maskrcnn_benchmark/modeling/roi_heads/mask_head/roi_mask_predictors.py:10
Method__init__
Arguments: proposal_matcher (Matcher) fg_bg_sampler (BalancedPositiveNegativeSampler) box_coder (BoxCoder
maskrcnn_benchmark/modeling/rpn/loss.py:24
Method__init__
Arguments: proposal_matcher (Matcher) box_coder (BoxCoder)
maskrcnn_benchmark/modeling/rpn/retinanet_loss.py:25
Method__init__
Arguments: pre_nms_thresh (float) pre_nms_top_n (int) nms_thresh (float) fpn_post_nms_top_n (
maskrcnn_benchmark/modeling/rpn/retinanet_infer.py:17
Method__init__
( self, sizes=(128, 256, 512), aspect_ratios=(0.5, 1.0, 2.0), anchor_strides=(
maskrcnn_benchmark/modeling/rpn/anchor_generator.py:40
Method__init__
Arguments: pre_nms_thresh (float) pre_nms_top_n (int) nms_thresh (float) fpn_post_nms_top_n (
maskrcnn_benchmark/modeling/rpn/retinanet_detail_infer.py:17
Method__init__
(self, cfg)
maskrcnn_benchmark/modeling/rpn/retinanet.py:103
Method__init__
Arguments: pre_nms_top_n (int) post_nms_top_n (int) nms_thresh (float) min_size (int)
maskrcnn_benchmark/modeling/rpn/inference.py:19
Method__init__
(self, cfg)
maskrcnn_benchmark/modeling/rpn/rpn.py:52
Method__init__
(self, cfg)
maskrcnn_benchmark/modeling/detector/generalized_rcnn.py:27
Method__init__
(self, cfg)
maskrcnn_benchmark/modeling/detector/retinanet.py:27
Method__init__
( self, cfg, model, optimizer=None, scheduler=None, save_dir="
maskrcnn_benchmark/utils/checkpoint.py:101
Method__init__
(self, window_size=20)
maskrcnn_benchmark/utils/metric_logger.py:13
Method__init__
(self, delimiter="\t")
maskrcnn_benchmark/utils/metric_logger.py:41
Method__init__
( self, optimizer, milestones, gamma=0.1, warmup_factor=1.0 / 3,
maskrcnn_benchmark/solver/lr_scheduler.py:11
Method__init__
(self, size_divisible=0)
maskrcnn_benchmark/data/collate_batch.py:12
Method__init__
(self, dataset, num_replicas=None, rank=None, shuffle=True)
maskrcnn_benchmark/data/samplers/distributed.py:26
Method__init__
(self, batch_sampler, num_iterations, start_iter=0)
maskrcnn_benchmark/data/samplers/iteration_based_batch_sampler.py:11
Method__init__
(self, sampler, group_ids, batch_size, drop_uneven=False)
maskrcnn_benchmark/data/samplers/grouped_batch_sampler.py:24
Method__init__
(self, transforms)
maskrcnn_benchmark/data/transforms/transforms.py:10
Method__init__
(self, min_size, max_size)
maskrcnn_benchmark/data/transforms/transforms.py:28
Method__init__
(self, min_sizes, max_size)
maskrcnn_benchmark/data/transforms/transforms.py:63
Method__init__
(self, prob=0.5)
maskrcnn_benchmark/data/transforms/transforms.py:76
Method__init__
(self, mean, std, to_bgr255=True)
maskrcnn_benchmark/data/transforms/transforms.py:92
Method__init__
(self, image_lists, transforms=None)
maskrcnn_benchmark/data/datasets/list_dataset.py:12
Method__init__
( self, ann_file, root, remove_images_without_annotations, transforms=None )
maskrcnn_benchmark/data/datasets/coco.py:10
Method__init__
(self, *iou_types)
maskrcnn_benchmark/engine/inference.py:299
Method__init__
Arguments: tensors (tensor) image_sizes (list[tuple[int, int]])
maskrcnn_benchmark/structures/image_list.py:15
Method__init__
(self, masks, size, mode)
maskrcnn_benchmark/structures/segmentation_mask.py:18
Method__init__
(self, polygons, size, mode)
maskrcnn_benchmark/structures/segmentation_mask.py:58
Method__init__
Arguments: polygons: a list of list of lists of numbers. The first level of the list correspond to individual ins
maskrcnn_benchmark/structures/segmentation_mask.py:151
Method__init__
(self, bbox, image_size, mode="xyxy")
maskrcnn_benchmark/structures/bounding_box.py:19
Method__init__
(self, beta=1. /9)
maskrcnn_benchmark/layers/smooth_l1_loss.py:6
Method__init__
(self, num_features, momentum=0.1, beta=1. /9)
maskrcnn_benchmark/layers/adjust_smooth_l1_loss.py:9
Method__init__
(self, num_classes, gamma, alpha)
maskrcnn_benchmark/layers/sigmoid_focal_loss.py:40
Method__init__
(self, output_size, spatial_scale, sampling_ratio)
maskrcnn_benchmark/layers/roi_align.py:51
Method__init__
(self, n)
maskrcnn_benchmark/layers/batch_norm.py:12
Method__init__
(self, output_size, spatial_scale)
maskrcnn_benchmark/layers/roi_pool.py:50
Method__init__
(self, indices)
tests/test_data_samplers.py:16
Method__init__
( self, cfg, confidence_threshold=0.7, show_mask_heatmaps=False, masks
demo/predictor.py:98
Method__iter__
(self)
maskrcnn_benchmark/modeling/rpn/anchor_generator.py:30
Method__iter__
(self)
maskrcnn_benchmark/data/samplers/distributed.py:43
Method__iter__
(self)
maskrcnn_benchmark/data/samplers/iteration_based_batch_sampler.py:16
Method__iter__
(self)
maskrcnn_benchmark/data/samplers/grouped_batch_sampler.py:102
Method__iter__
(self)
maskrcnn_benchmark/structures/segmentation_mask.py:206
Method__iter__
(self)
tests/test_data_samplers.py:19
Method__len__
(self)
maskrcnn_benchmark/modeling/rpn/anchor_generator.py:27
Method__len__
(self)
maskrcnn_benchmark/data/samplers/distributed.py:63
Method__len__
(self)
maskrcnn_benchmark/data/samplers/iteration_based_batch_sampler.py:30
Method__len__
(self)
maskrcnn_benchmark/data/samplers/grouped_batch_sampler.py:111
Method__len__
(self)
maskrcnn_benchmark/data/datasets/list_dataset.py:28
Method__len__
(self)
maskrcnn_benchmark/structures/bounding_box.py:211
Method__len__
(self)
tests/test_data_samplers.py:22
Method__repr__
(self)
maskrcnn_benchmark/data/transforms/transforms.py:18
Method__repr__
(self)
maskrcnn_benchmark/engine/inference.py:322
Method__repr__
(self)
maskrcnn_benchmark/structures/segmentation_mask.py:137
Method__repr__
(self)
maskrcnn_benchmark/structures/segmentation_mask.py:209
Method__repr__
(self)
maskrcnn_benchmark/structures/bounding_box.py:247
Method__repr__
(self)
maskrcnn_benchmark/layers/sigmoid_focal_loss.py:52
Method__repr__
(self)
maskrcnn_benchmark/layers/roi_align.py:62
Method__repr__
(self)
maskrcnn_benchmark/layers/roi_pool.py:58
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