o ߥi3@sddlZddlZddlZddlmZdddZdddZdd d Zd d Z d dZ      dddZ ddZ dddZ dddZdS) N)nmscCsFtjt|t|gdd\}}t||fddd||dfS)Nij)indexing)torchmeshgridarangestackviewfloat)nxnyyvxvrg/home/ubuntu/.local/lib/python3.10/site-packages/modelscope/models/cv/image_driving_perception/utils.py _make_grid s $rc Csg}gd}tdD]j}||j\}}}}|||dd||ddddd||<||} t||||j} | dddfd d | ||| dddf<| dddfdd||| dddf<| | |d dq t |d}|S) N) Urrr.g@g?) rangeshaper permute contiguoussigmoidrtodeviceappendrcat) pred anchor_gridzstibs_rrygrrrrsplit_for_trace_models   0, r.iicCs|dur.t|d|d|d|d}|d|d|d|d|d|df}n |dd}|d}|ddddgf|d8<|ddddgf|d8<|ddddf|<t|||S)Nrrrrr)min clip_coords) img1_shapecoords img0_shape ratio_padgainpadrrr scale_coords s    r8cCst|dddfd|d|dddfd|d|dddfd|d|dddfd|ddS)Nrrrr)clamp_)boxes img_shaperrrr12s r1cCst|tjr |nt|}|dddf|dddfd|dddf<|dddf|dddfd|dddf<|dddf|dddfd|dddf<|dddf|dddfd|dddf<|S)Nrrrr) isinstancerTensorclonenpcopy)xr,rrr xywh2xyxy:s 0000rB333333??FrcCs|jdd}|d|k}d} d} d} d} d} ||d kM}d }t}tjd |jd g|jd }t|D]\}}|||}|rt||r||}tjt||df|jd }|ddd df|ddddf<d|dddf<d|tt||ddd fdf<t ||fd }|jd sq5|ddddf|ddddf9<t |ddddf}|r|ddddf|kj d dj \}}t |||||ddf|dddf fd }n#|ddddfjd dd\}}t ||| fd |d|k}|dur'||ddddftj||jd kd }|jd }|s0q5|| krG||dddfjddd| }|ddddf|rUd n| }|ddddf||dddf}}t|||}|jd | kr|d| }|rd |kr|dkrt||||k}||d}t||ddddf |jd dd||ddf<| r||d d k}||||<t|| krtd| d|Sq5|S)zRuns Non-Maximum Suppression (NMS) on inference results Returns: list of detections, on (n,6) tensor per image [xyxy, conf, cls] r).rii,i0ug$@TrF)r)r"rNrg?)as_tuple)keepdimrrF) descendinggp@zWARNING: NMS time limit z s exceeded)rtimerzerosr" enumeratelenrlongr$rBnonzeroTr maxr tensoranyargsortrbox_ioummsumprint) prediction conf_thres iou_thresclassesagnostic multi_labellabelsncxcmax_whmax_detmax_nms time_limit redundantmergetoutputxirAlbsvboxr)jconfncr:scoresiouweightsrrrnon_max_suppressionDs   $( ,&6"  .  "   " rucCsdd}||j}||j}t|dddddf|ddddft|dddddf|ddddfdd}||dddf||S)aX Return intersection-over-union (Jaccard index) of boxes. Both sets of boxes are expected to be in (x1, y1, x2, y2) format. Args: box1 (Tensor[N, 4]) box2 (Tensor[M, 4]) Returns: iou (Tensor[N, M]): the NxM matrix containing the pairwise IoU values for every element in boxes1 and boxes2 cSs |d|d|d|dS)Nrrrrr)rmrrrbox_areas zbox_iou..box_areaNrr)rPrr0rQclampprod)box1box2rvarea1area2interrrrrUs  ,, rUcCs<tjjj||dd}t|d\}}|}|SNbilinear)sizemoder) rnn functional interpolaterQintsqueezecpunumpy) da_predict out_shape da_seg_maskr+rrrdriving_area_mask rcCs<tjjj||dd}t|d}|}|Sr~) rrrrroundrrrr) ll_predictr ll_seg_maskrrrlane_line_maskrr)rr)NN)r/N)rCrDNFFr)Nr/)rJrr?rtorchvision.opsrrr.r8r1rBrurUrrrrrrs&      `