o ߥi@sddlmZddlZddlZddlmZddlZddlm Z ddl m Z ddl m Z ddlmZddlmZddlmZGd d d e Z dd d ZdddZdS)N) TorchModel)build_backbone) build_head) build_neck)DetectionOutput) parse_configcsFeZdZdZdeffdd ZddZddZd d Zd d Z Z S) SingleStageDetectorz2 The base class of single stage detector. model_dircstj|g|Ri|t||j}t|}||_t||jj}t||jj }t t |d|_ |jj|_|jjj|_|jjj|_|jjj|_d|jjjjvrat||jjjj|jjj_t|jjj|_t|jjj|_t|jjj|_d|j_||jd|_ |!|dS)z# init model by cfg rbTinyNASFN)"super__init__ospjoin config_namercfgmodelname class_mappickleloadopen label_mapdatasetsize_divisibilitysize_divisiblehead num_classes nms_conf_thre conf_thre nms_iou_threnms_threbackbonestructure_filerrneckrnmsapplyinit_bn onnx_exportload_pretrain_model)selfr argskwargs config_pathconfig model_pathr __class__c/home/ubuntu/.local/lib/python3.10/site-packages/modelscope/models/cv/tinynas_detection/detector.pyrs,       zSingleStageDetector.__init__cCsltj|dd}d|vr|d}nd|vr|d}i}|D]\}}|dd}|||<q|j|dddS) Ncpu) map_locationr state_dictzmodule.T)strict)torchritemsreplaceload_state_dict)r+pretrain_modelckptr7new_state_dictkvr3r3r4r*8s   z'SingleStageDetector.load_pretrain_modelcCs*|D]}t|tjrd|_d|_qdS)NgMbP?gQ?)modules isinstancenn BatchNorm2depsmomentum)r+Mmr3r3r4r(Ds  zSingleStageDetector.init_bncCsP|jrdS||}||}||\}}tj||dd|jfgdd}|S)N.r)dim)trainingr#r%rr:catr)r+x cls_scores bbox_preds predictionr3r3r4forwardJs  zSingleStageDetector.forwardcshjr|St|jjj\}}}|}|}|}fdd|D}t|||dS)Ncs"g|] }j|dddqS)rrr)r).0idxr+r3r4 ^s"z3SingleStageDetector.postprocess..)boxesscores class_ids)r)postprocess_gfocalrr r"r5numpyr)r+predsbboxesrY labels_idxlabelsr3rVr4 postprocessUs   zSingleStageDetector.postprocess) __name__ __module__ __qualname____doc__strrr*r(rSra __classcell__r3r3r1r4r s  r dc Cs4|d}|jddkr||ddd}n|dddf|d|d}|}||k} t|t| | | | fddd}|durM||dddf}t|| }| jdddddf} |dkr|| d}|j d tj d } | d }||| fSt j ||| |} |dkr| d|} || || | | fS) aNMS for multi-class bboxes. Args: multi_bboxes (Tensor): shape (n, #class*4) or (n, 4) multi_scores (Tensor): shape (n, #class), where the last column contains scores of the background class, but this will be ignored. score_thr (float): bbox threshold, bboxes with scores lower than it will not be considered. nms_thr (float): NMS IoU threshold max_num (int): if there are more than max_num bboxes after NMS, only top max_num will be kept. score_factors (Tensor): The factors multiplied to scores before applying NMS Returns: tuple: (bboxes, labels), tensors of shape (k, 5) and (k, 1). Labels are 0-based. rrrKNF)as_tuple)r)r)dtype)sizeshapeviewexpandr: masked_selectstacknonzeronumel new_zeroslong torchvisionops batched_nms) multi_bboxes multi_scores score_thriou_thrmax_num score_factorsrr^rY valid_maskr`keepr3r3r4multiclass_nmsgs:        r皙?ffffff?c Csx|jddks Jt|D])\}}|dsq |ddddf}|ddddf}t||||d\}} } q || | fS)Nrrrii)rn enumeratermr) rRrr r"i image_predrzr{ detectionsrYr`r3r3r4r[s  r[)rhN)rr)os.pathpathrrr:torch.nnrErw'modelscope.models.base.base_torch_modelrAmodelscope.models.cv.tinynas_detection.damo.base_models.backbonesr=modelscope.models.cv.tinynas_detection.damo.base_models.headsr=modelscope.models.cv.tinynas_detection.damo.base_models.necksrmodelscope.outputs.cv_outputsrutilsrr rr[r3r3r3r4s        U @