^j* fddlmZddlmZddlmZedeGddeZdgZy ) )strict)PreTrainedConfig)auto_docstringzmagic-leap-community/superpoint) checkpointceZdZUdZdZdZeeeedfze d<dZ ee d<dZ ee d <dZ ee d <d Z ee d <d Zee d<dZee d<dZee d<dZee d<y)SuperPointConfiga) encoder_hidden_sizes (`List`, *optional*, defaults to `[64, 64, 128, 128]`): The number of channels in each convolutional layer in the encoder. keypoint_decoder_dim (`int`, *optional*, defaults to 65): The output dimension of the keypoint decoder. descriptor_decoder_dim (`int`, *optional*, defaults to 256): The output dimension of the descriptor decoder. keypoint_threshold (`float`, *optional*, defaults to 0.005): The threshold to use for extracting keypoints. max_keypoints (`int`, *optional*, defaults to -1): The maximum number of keypoints to extract. If `-1`, will extract all keypoints. nms_radius (`int`, *optional*, defaults to 4): The radius for non-maximum suppression. border_removal_distance (`int`, *optional*, defaults to 4): The distance from the border to remove keypoints. Example: ```python >>> from transformers import SuperPointConfig, SuperPointForKeypointDetection >>> # Initializing a SuperPoint superpoint style configuration >>> configuration = SuperPointConfig() >>> # Initializing a model from the superpoint style configuration >>> model = SuperPointForKeypointDetection(configuration) >>> # Accessing the model configuration >>> configuration = model.config ``` superpoint)@r r .encoder_hidden_sizesdecoder_hidden_sizeAkeypoint_decoder_dimdescriptor_decoder_dimg{Gzt?keypoint_threshold max_keypoints nms_radiusborder_removal_distanceg{Gz?initializer_rangeN)__name__ __module__ __qualname____doc__ model_typer listinttuple__annotations__rrrrfloatrrrr/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/transformers/models/superpoint/configuration_superpoint.pyr r s 8J8J$s)eCHo5J"" "#""%C% %%M3J#$S$#u#r%r N)huggingface_hub.dataclassesrconfiguration_utilsrutilsrr __all__r$r%r&r+sE /3#<='$''$>'$T  r%