jI26ddlmZddlZddlmZddlmZddlmZddlm Z ddl Z ddl Z ddl mZddlmZmZdd lmZdd lmZdCdDdZdEdFdZ dGdHd#ZdIdJd*Z dKdLd2Z dMdNd4Z dOdPd=Z dOdPd>Zed?kred@dABed@dABdSdS)Q) annotationsN)glob)ceil)Path)Any)Image) exif_sizeimg2label_paths)TQDM)check_requirementsư>polygon1 np.ndarraybbox2epsfloatreturnc tdddlm|ddd}t j|d}t j|d}t j||gd}t j|d d d d dfd d df}t j |d d d dd fd dd f}t j ||z dtj }|d |d z} fd tdD\} } } } t j | | | | | | | | gdddd}fd|D}fd|D}t j| j}t!t j| D]7}||d||dj||<8t jd|Dtj}|d}t j ||tj }||z }|jdkr|d}|S)aCalculate Intersection over Foreground (IoF) between polygons and bounding boxes. Args: polygon1 (np.ndarray): Polygon coordinates with shape (N, 8). bbox2 (np.ndarray): Bounding boxes with shape (M, 4). eps (float, optional): Small value to prevent division by zero. Returns: (np.ndarray): IoF scores with shape (N, M). Notes: Polygon format: [x1, y1, x2, y2, x3, y3, x4, y4]. Bounding box format: [x_min, y_min, x_max, y_max]. zshapely>=2.0.0r)PolygonaxisN.).r).c3,K|]}d|fVdS.N).0irs `/home/longshao/multi-rider-rag/.venv/lib/python3.11/site-packages/ultralytics/data/split_dota.py zbbox_iof..0s+@@!c1f @@@@@@c&g|] }|Srrr prs r" zbbox_iof..3!......r$c&g|] }|Srrr&s r"r(zbbox_iof..4r)r$cg|] }|j Sr)area)r r's r"r(zbbox_iof..8s111!qv111r$dtyperr)r shapely.geometryrreshapenpminmax concatenatemaximumminimumclipinfrangestackzerosshapezipnonzero intersectionr,arrayfloat32ndim)rrrlt_pointrb_pointbbox1ltrbwh h_overlapslefttoprightbottompolygon2 sg_polys1 sg_polys2overlapsr'unionsoutputsrs ` @r"bbox_iofrTsh'(((((((((Aq))HvhR(((HvhR(((H NHh/b 9 9 9E E!!!T2A2+&c2A2g 7 7B E!!!T122+&c122g 7 7B b!RV $ $BFbj(J@@@@uQxx@@@D#ufxsE3vtVLSUVVV^^_acdfghhH....X...I....X...Ix ())H "*Z(( )JJ!o229QrU3CDDI X11y111 D D DF I F WVS"& ) )FG|q)$ Nr$train data_rootstrsplitlist[dict[str, Any]]c|dvsJd|dt|dz |z }|sJd|dttt|dz |z dz }t |}g}t ||D]\}}t tj|\}} t|d 5} d | D} tj | tj } d d d n #1swxYwY|t!| |f| | |S)a,Load DOTA dataset annotations and image information. Args: data_root (str): Data root directory. split (str, optional): The split data set, could be 'train' or 'val'. Returns: (list[dict[str, Any]]): List of annotation dictionaries containing image information. Notes: The directory structure assumed for the DOTA dataset: - data_root - images - train - val - labels - train - val >valrUz$Split must be 'train' or 'val', not .images Can't find , please check your data root.*utf-8encodingcTg|]%}t||&Sr)lenrX)r xs r"r(z"load_yolo_dota.._s+MMMc!ffM!''))MMMr$r-N)ori_sizelabelfilepath)rexistsrrWr r=r ropenreadstrip splitlinesr1r@rAappenddict) rVrXim_dirim_fileslb_filesannosim_filelb_filewhflbs r"load_yolo_dotar{Bs( $ $ $ $&UU&U&U&U $ $ $ )__x '% /F ==??PPP&PPPPP?CY(2U:S@AABBHx((H E(33HHG,,--1 'G , , , 0MMQVVXX^^%5%5%@%@%B%BMMMB"BJ///B 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0  TAq6gFFFGGGG LsA#EE E 333333?{Gz?im_sizetuple[int, int] crop_sizestuple[int, ...]gaps im_rate_thrc n|\}}g}t||D]\\}} || ksJd|d| d|| z ||krdnt||z z dz} fdt| D} t| dkr| d|z|kr||z | d<||krdnt||z z dz} fdt| D} t| dkr| d|z|kr||z | d<t jt tj| | tj }||z}| t j ||gd ^t j |d }| }t j |d d d d d fd ||d d d d d f<t j |d d dd d fd ||d d dd d f<|d d d f|d d d fz |d d d f|d d dfz z}|d d d f|d d d fz |d d d f|d d dfz z}||z }||ks-|}d|t!||z |k<|||kS)aLGet the coordinates of sliding windows for image cropping. Args: im_size (tuple[int, int]): Original image size, (H, W). crop_sizes (tuple[int, ...], optional): Crop size of windows. gaps (tuple[int, ...], optional): Gap between crops. im_rate_thr (float, optional): Threshold for the ratio of image area within a window to the total window area. eps (float, optional): Epsilon value for math operations. Returns: (np.ndarray): Array of window coordinates of shape (N, 4) where each row is [x_start, y_start, x_stop, y_stop]. zinvalid crop_size gap pair [ ]rcg|]}|zSrrr r!steps r"r(zget_windows.. * * *1dQh * * *r$rcg|]}|zSrrrs r"r(zget_windows..rr$r-rrNr)r=rr9rer1r@list itertoolsproductint64ror4copyr7anyr3abs)rrrrrrxrwwindows crop_sizegapxnxsynysstartstop im_in_winsim_areas win_areasim_ratesmax_raters @r" get_windowsres'& DAqGj$//>> 33 Qy Q Q3 Q Q Q3y..QQdA MT+AA+E&F&F * * * *b * * * r77Q;;2b6I-11]BrFy..QQdA MT+AA+E&F&F * * * *b * * * r77Q;;2b6I-11]BrFi/B7788IIIy r~udm!<<<====nW1---GJ'*QQQ1W"5q!<>34X())C/0 8k) **r$ffffff?annodict[str, Any]riof_thrlist[np.ndarray]c|d\}}|dtrtdddddfxx|zcc<dddddfxx|zcc<tddddf|fdtt|DSdtt|DS)z3Get objects for each window based on IoF threshold.rgrhNrrc<g|]}dd|fkS)Nr)r r!riofsrhs r"r(z"get_window_obj..s/LLL1tAAAqDzW,-LLLr$cNg|]"}tjdtj#S))r r-)r1r;rA)r _s r"r(z"get_window_obj..s)PPPqrz222PPPr$)rerTr9)rrrrxrwrrhs ` @@r"get_window_objrs  DAq ME 5zzQ aaaAg! aaaAg!aaae g..LLLLLLc'll8K8KLLLLPPE#g,,.s'K'K'K55'K'K'Kr$rr )cv2imreadrstem enumeratetolistr<reimwriterWrkwriteintjoin)rrrrqrrimnamer!windowx_starty_startx_stopy_stopnew_namepatch_imphpwrhryrzformatted_coordss r" crop_and_savers8 D$ % %B Z ! ! &Dw''LL 6+1==??(&&GGfw.GG'GGgGGgfngfn45#BA u:: I0 I KDLLh+<+<+<<==x H H H u:: L !!!QTT'NNNg %NNN !!!QTT'NNNg %NNN !!!QTT'NNNb NNN !!!QTT'NNNb NNNd6ll%6%6%66gNNN LRSLLB'K'KBqrrF'K'K'K$GGs2a5zzJJCHH5E,F,FJJJKKKKL L L L L L L L L L L L L L L LLLs1AGG G save_dirc t|dz |z }|ddt|dz |z }|ddt||}t|t ||D]V}t |d||} t || } t|| | t|t|WdS) aSplit both images and labels for a given dataset split. Args: data_root (str): Root directory of the dataset. save_dir (str): Directory to save the split dataset. split (str, optional): The split data set, could be 'train' or 'val'. crop_sizes (tuple[int, ...], optional): Tuple of crop sizes. gaps (tuple[int, ...], optional): Tuple of gaps between crops. Notes: The directory structure assumed for the DOTA dataset: - data_root - images - split - labels - split and the output directory structure is: - save_dir - images - split - labels - split r]Tparentsexist_oklabels)rXtotaldescrgN) rmkdirr{r rerrrrW) rVrrXrrrqrrtrrrs r"split_images_and_labelsrs<(^^h & .F LLL--- (^^h & .F LLL--- 9E 2 2 2EU#e**5999LLd:. DAA$T733 dG[#f++s6{{KKKKLLr$r}rg?rrrratestuple[float, ...]cgg}}|D]L}|t||z |t||z MdD]}t|||||dS)ahSplit train and val sets of DOTA dataset with multiple scaling rates. Args: data_root (str): Root directory of the dataset. save_dir (str): Directory to save the split dataset. crop_size (int, optional): Base crop size. gap (int, optional): Base gap between crops. rates (tuple[float, ...], optional): Scaling rates for crop_size and gap. Notes: The directory structure assumed for the DOTA dataset: - data_root - images - train - val - labels - train - val and the output directory structure is: - save_dir - images - train - val - labels - train - val >r[rUN)rorr) rVrrrrrrrrXs r"split_trainvalrs<2J ""#i!m,,--- CaLL!!!!!NN 8UJMMMMNNr$c |gg}}|D]L}|t||z |t||z Mt|dz dz }|ddt|dz dz }|sJd|dt t |dz } t| t| dD]} ttj | \} } t| | f|| } tj| }t| j}| D]a}|\}}}}|d ||z d |d |}|||||f}tjt ||d z |bd S)aSplit test set of DOTA dataset, labels are not included within this set. Args: data_root (str): Root directory of the dataset. save_dir (str): Directory to save the split dataset. crop_size (int, optional): Base crop size. gap (int, optional): Base gap between crops. rates (tuple[float, ...], optional): Scaling rates for crop_size and gap. Notes: The directory structure assumed for the DOTA dataset: - data_root - images - test and the output directory structure is: - save_dir - images - test r]testTrr^r_r`r)rrrrrN)rorrrrjrrWr rer rrkrrrrrr)rVrrrrrrrrqrrrurwrxrrrrrrrrrrs r" split_testr*s,2J ""#i!m,,--- CaLL!!!!H~~(61H NN4$N/// )__x '& 0F ==??PPP&PPPPP?C %%&&HH FCCC E EG,,--1q!f$GGG Z G}}! E EF/5}} ,GWffKK&7"2KKgKK'KKH'&.'&.89H KH('8'8'88998 D D D D  E E Er$__main__DOTAv2z DOTAv2-split)rVr)r )rrrrrrrr)rU)rVrWrXrWrrY)r|r~rr) rrrrrrrrrrrr)r)rrrrrrrr)T)rrrrrrrqrWrrWrrrr)rUr|r~) rVrWrrWrXrWrrrrrr)r}rr) rVrWrrWrrrrrrrr) __future__rrrmathrpathlibrtypingrrnumpyr1PILrultralytics.data.utilsr r ultralytics.utilsr ultralytics.utils.checksr rTr{rrrrrr__name__rr$r"rs)#""""" ========""""""777777+++++\     J#*" 1+1+1+1+1+h Q Q Q Q Q(%) 0L0L0L0L0Ll")" 'L'L'L'L'LVfl#N#N#N#N#NNfl)E)E)E)E)EX zNX????JN;;;;;;r$