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Types & classes166 in github.com/TonyXuQAQ/RNGDetPlusPlus

↓ 15 callersClassPoint
cityscale/lib/geom.py:4
↓ 15 callersClassPoint
spacenet/lib/geom.py:4
↓ 6 callersClassEdgePos
cityscale/lib/graph.py:80
↓ 6 callersClassEdgePos
spacenet/lib/graph.py:80
↓ 5 callersClassGraph
cityscale/lib/graph.py:156
↓ 5 callersClassGraph
spacenet/lib/graph.py:156
↓ 5 callersClassRectangle
cityscale/lib/geom.py:171
↓ 5 callersClassRectangle
spacenet/lib/geom.py:171
↓ 4 callersClassNestedTensor
cityscale/models/util/misc.py:284
↓ 4 callersClassNestedTensor
spacenet/models/util/misc.py:284
↓ 4 callersClassRNGDetNet
cityscale/dataset.py:8
↓ 4 callersClassRNGDetNet
spacenet/dataset.py:8
↓ 3 callersClassEdge
cityscale/prepare_dataset/create_label.py:92
↓ 3 callersClassEdge
spacenet/prepare_dataset/create_label.py:132
↓ 3 callersClassFPoint
cityscale/lib/geom.py:59
↓ 3 callersClassFPoint
spacenet/lib/geom.py:59
↓ 3 callersClassNestedTensor
cityscale/utils/misc.py:283
↓ 3 callersClassNestedTensor
spacenet/utils/misc.py:283
↓ 3 callersClassPath
cityscale/utils/model_utils.py:14
↓ 3 callersClassPath
spacenet/utils/model_utils.py:14
↓ 3 callersClassRoadSegment
cityscale/lib/graph.py:421
↓ 3 callersClassRoadSegment
spacenet/lib/graph.py:421
↓ 2 callersClassAgent
cityscale/agent.py:22
↓ 2 callersClassAgent
spacenet/agent.py:22
↓ 2 callersClassEdge
cityscale/main_val.py:23
↓ 2 callersClassEdge
cityscale/main_test.py:27
↓ 2 callersClassEdge
cityscale/lib/graph.py:40
↓ 2 callersClassEdge
spacenet/main_val.py:23
↓ 2 callersClassEdge
spacenet/main_test.py:27
↓ 2 callersClassEdge
spacenet/lib/graph.py:40
↓ 2 callersClassFPN
Simple convolutional head, using group norm. Upsampling is done using a FPN approach
cityscale/models/detr/segmentation_raw.py:207
↓ 2 callersClassFPN
Simple convolutional head, using group norm. Upsampling is done using a FPN approach
cityscale/models/detr/segmentation.py:306
↓ 2 callersClassFPN
Simple convolutional head, using group norm. Upsampling is done using a FPN approach
spacenet/models/detr/segmentation_raw.py:207
↓ 2 callersClassFPN
Simple convolutional head, using group norm. Upsampling is done using a FPN approach
spacenet/models/detr/segmentation.py:310
↓ 2 callersClassMLP
Very simple multi-layer perceptron (also called FFN)
cityscale/models/detr/detr.py:267
↓ 2 callersClassMLP
Very simple multi-layer perceptron (also called FFN)
spacenet/models/detr/detr.py:267
↓ 2 callersClassSmoothedValue
Track a series of values and provide access to smoothed values over a window or the global series average.
cityscale/utils/misc.py:26
↓ 2 callersClassSmoothedValue
Track a series of values and provide access to smoothed values over a window or the global series average.
cityscale/models/util/misc.py:27
↓ 2 callersClassSmoothedValue
Track a series of values and provide access to smoothed values over a window or the global series average.
spacenet/utils/misc.py:26
↓ 2 callersClassSmoothedValue
Track a series of values and provide access to smoothed values over a window or the global series average.
spacenet/models/util/misc.py:27
↓ 2 callersClassVertex
cityscale/main_val.py:16
↓ 2 callersClassVertex
cityscale/sampler.py:89
↓ 2 callersClassVertex
cityscale/main_test.py:20
↓ 2 callersClassVertex
cityscale/lib/graph.py:10
↓ 2 callersClassVertex
spacenet/main_val.py:16
↓ 2 callersClassVertex
spacenet/sampler.py:92
↓ 2 callersClassVertex
spacenet/main_test.py:20
↓ 2 callersClassVertex
spacenet/lib/graph.py:10
↓ 1 callersClassBackbone
ResNet backbone with frozen BatchNorm.
cityscale/models/detr/backbone.py:74
↓ 1 callersClassBackbone
ResNet backbone with frozen BatchNorm.
spacenet/models/detr/backbone.py:74
↓ 1 callersClassBottleneck
cityscale/models/detr/segmentation_raw.py:178
↓ 1 callersClassBottleneck
spacenet/models/detr/segmentation_raw.py:178
↓ 1 callersClassDETR
This is the DETR module that performs object detection
cityscale/models/detr/detr.py:21
↓ 1 callersClassDETR
This is the DETR module that performs object detection
spacenet/models/detr/detr.py:21
↓ 1 callersClassDETRsegm
cityscale/models/detr/segmentation.py:12
↓ 1 callersClassDETRsegm
spacenet/models/detr/segmentation.py:13
↓ 1 callersClassEdge
cityscale/sampler.py:21
↓ 1 callersClassEdge
spacenet/sampler.py:21
↓ 1 callersClassGraph
cityscale/main_test.py:33
↓ 1 callersClassGraph
cityscale/prepare_dataset/create_label.py:24
↓ 1 callersClassGraph
spacenet/main_test.py:33
↓ 1 callersClassGraph
spacenet/prepare_dataset/create_label.py:24
↓ 1 callersClassGraphContainer
cityscale/lib/graph.py:660
↓ 1 callersClassGraphContainer
spacenet/lib/graph.py:660
↓ 1 callersClassHungarianMatcher
This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no
cityscale/models/detr/matcher.py:12
↓ 1 callersClassHungarianMatcher
This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no
spacenet/models/detr/matcher.py:12
↓ 1 callersClassIndex
cityscale/lib/graph.py:101
↓ 1 callersClassIndex
spacenet/lib/graph.py:101
↓ 1 callersClassJoiner
cityscale/models/detr/backbone.py:88
↓ 1 callersClassJoiner
spacenet/models/detr/backbone.py:88
↓ 1 callersClassMHAttentionMap
This is a 2D attention module, which only returns the attention softmax (no multiplication by value)
cityscale/models/detr/segmentation_raw.py:146
↓ 1 callersClassMHAttentionMap
This is a 2D attention module, which only returns the attention softmax (no multiplication by value)
cityscale/models/detr/segmentation.py:79
↓ 1 callersClassMHAttentionMap
This is a 2D attention module, which only returns the attention softmax (no multiplication by value)
spacenet/models/detr/segmentation_raw.py:146
↓ 1 callersClassMHAttentionMap
This is a 2D attention module, which only returns the attention softmax (no multiplication by value)
spacenet/models/detr/segmentation.py:80
↓ 1 callersClassMaskHeadSmallConv
Simple convolutional head, using group norm. Upsampling is done using a FPN approach
cityscale/models/detr/segmentation_raw.py:72
↓ 1 callersClassMaskHeadSmallConv
Simple convolutional head, using group norm. Upsampling is done using a FPN approach
spacenet/models/detr/segmentation_raw.py:72
↓ 1 callersClassPositionEmbeddingLearned
Absolute pos embedding, learned.
cityscale/models/detr/position_encoding.py:51
↓ 1 callersClassPositionEmbeddingLearned
Absolute pos embedding, learned.
spacenet/models/detr/position_encoding.py:51
↓ 1 callersClassPositionEmbeddingSine
This is a more standard version of the position embedding, very similar to the one used by the Attention is all you need paper, generalized t
cityscale/models/detr/position_encoding.py:12
↓ 1 callersClassPositionEmbeddingSine
This is a more standard version of the position embedding, very similar to the one used by the Attention is all you need paper, generalized t
spacenet/models/detr/position_encoding.py:12
↓ 1 callersClassRegion
cityscale/utils/regions.py:1
↓ 1 callersClassRegion
spacenet/utils/regions.py:1
↓ 1 callersClassRoadSegmentExploration
cityscale/lib/graph.py:561
↓ 1 callersClassRoadSegmentExploration
spacenet/lib/graph.py:561
↓ 1 callersClassSampler
cityscale/sampler.py:100
↓ 1 callersClassSampler
spacenet/sampler.py:106
↓ 1 callersClassSegment
cityscale/lib/geom.py:102
↓ 1 callersClassSegment
spacenet/lib/geom.py:102
↓ 1 callersClassSetCriterion
This class computes the loss for DETR. The process happens in two steps: 1) we compute hungarian assignment between ground truth boxes an
cityscale/models/detr/detr.py:89
↓ 1 callersClassSetCriterion
This class computes the loss for DETR. The process happens in two steps: 1) we compute hungarian assignment between ground truth boxes an
spacenet/models/detr/detr.py:89
↓ 1 callersClassTargetPosesContainer
cityscale/utils/model_utils.py:1051
↓ 1 callersClassTargetPosesContainer
spacenet/utils/model_utils.py:1051
↓ 1 callersClassTileCache
cityscale/utils/tileloader.py:99
↓ 1 callersClassTileCache
spacenet/utils/tileloader.py:99
↓ 1 callersClassTransformer
cityscale/models/detr/transformer.py:18
↓ 1 callersClassTransformer
spacenet/models/detr/transformer.py:18
↓ 1 callersClassTransformerDecoder
cityscale/models/detr/transformer.py:89
↓ 1 callersClassTransformerDecoder
spacenet/models/detr/transformer.py:89
↓ 1 callersClassTransformerDecoderLayer
cityscale/models/detr/transformer.py:190
↓ 1 callersClassTransformerDecoderLayer
spacenet/models/detr/transformer.py:190
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