a yf)@sddlZddlmZddlmZddlmZddlZddlZddl m Z ddl m Z ddl m Z mZddlmZed dd lmZd*d d Zd+ddZd,ddZd-ddZd.ddZd/ddZd0d"d#Zd1d$d%Zed&kred'd(d)ed'd(d)dS)2N)glob)ceil)Path)Image)tqdm) exif_sizeimg2label_paths)check_requirementsZshapelyPolygonư>c s|ddd}tj|dd}tj|dd}tj||gdd}t|dddddfdddf}t|dddddfdddf}t||dtj}|d |d } fd d t dD\} } } } tj | | | | | | | | gddddd}d d|D}dd|D}t | j }t t| D]&}||d||dj||<q0tjdd|Dtjd}|d}t||tj}||}|jdkr|d}|S)a Calculate Intersection over Foreground (IoF) between polygons and bounding boxes. Args: polygon1 (np.ndarray): Polygon coordinates, shape (n, 8). bbox2 (np.ndarray): Bounding boxes, shape (n, 4). eps (float, optional): Small value to prevent division by zero. Defaults to 1e-6. Returns: (np.ndarray): IoF scores, shape (n, 1) or (n, m) if bbox2 is (m, 4). Note: Polygon format: [x1, y1, x2, y2, x3, y3, x4, y4]. Bounding box format: [x_min, y_min, x_max, y_max]. ZaxisN.r).r).c3s|]}d|fVqdS.N.0ibbox2rW/var/www/html/django/DPS/env/lib/python3.9/site-packages/ultralytics/data/split_dota.py .zbbox_iof..cSsg|] }t|qSrr rprrr 1rzbbox_iof..cSsg|] }t|qSrr rrrrr2rcSsg|] }|jqSr)arearrrrr6rZdtyperr)Zreshapenpminmax concatenatemaximumminimumclipinfrangestackzerosshapezipZnonzero intersectionr arrayfloat32ndim)Zpolygon1repsZlt_pointZrb_pointZbbox1ltrbZwhZ h_overlapslefttoprightbottomZpolygon2Z sg_polys1Z sg_polys2overlapsrZunionsoutputsrrrbbox_iofs,**( $ r<trainc Cs|dvsJd|dt|d|}|s@Jd|dttt|d|d}t|}g}t||D]\}}tt|\}} t|:} dd | D} t j | t jd } Wd n1s0Y|t| |f| |d qr|S) a Load DOTA dataset. Args: data_root (str): Data root. split (str): The split data set, could be train or val. Notes: The directory structure assumed for the DOTA dataset: - data_root - images - train - val - labels - train - val >valr=z$Split must be 'train' or 'val', not .images Can't find , please check your data root.*cSsg|]}t|r|qSr)lensplit)rxrrrr[rz"load_yolo_dota..r!N)ori_sizelabelfilepath)rexistsrstrrr.rropenreadstrip splitlinesr"r0r1appenddict) data_rootrEim_dirim_filesZlb_filesannosim_fileZlb_filewhflbrrrload_yolo_dota@s .r[333333?{Gz?cs||\}}g}t||D]*\}} || ks>Jd|d| d|| ||krRdnt||d} fddt| D} t| dkr| d||kr||| d<||krdnt||d} fddt| D} t| dkr| d||kr||| d<tjtt| | tj d }||}| tj ||gdd qtj |d d }| }t |d d d d d fd ||d d d d d f<t |d d dd d fd ||d d dd d f<|d d d f|d d d f|d d df|d d df}|d d d f|d d d f|d d df|d d df}||}||ksp|}d|t|||k<|||kS)aT Get the coordinates of windows. Args: im_size (tuple): Original image size, (h, w). crop_sizes (List(int)): Crop size of windows. gaps (List(int)): Gap between crops. im_rate_thr (float): Threshold of windows areas divided by image ares. eps (float): Epsilon value for math operations. zinvalid crop_size gap pair [ ]rcsg|] }|qSrrrsteprrrsrzget_windows..r csg|] }|qSrrrrdrrrxrr!rrNr)r.rr*rDr"r0list itertoolsproductZint64rPr%copyr(anyr$abs)Zim_size crop_sizesgapsZ im_rate_thrr3rXrWwindows crop_sizegapZxnZxsZynZysstartstopZ im_in_winsZim_areasZ win_areasZim_ratesZmax_raterrdr get_windowsas6      22@@rtffffff?cs|d\}}|dtrdddddf|9<dddddf|9<tddddf|fddtt|DSddtt|DSdS) zGet objects for each window.rGrHNrrcs$g|]}dd|fkqS)Nrriof_thrZiofsrHrrrrz"get_window_obj..cSsg|]}tjdtjdqS))r r!)r"r,r1)r_rrrrr)rDr<r*)annororwrXrWrrvrget_window_objs r{Tc Cst|d}t|dj}t|D]\}} | \} } } } |d| | d| d| }|| | | | f}|jdd\}}||}t|s|rtt t||d|t|r$|dddddf| 8<|dddddf| 8<|dddddf|<|dddddf|<t t||dd V}|D]@}d d |ddD}| t |d d d |dqRWdq$1s0Yq$dS)a Crop images and save new labels. Args: anno (dict): Annotation dict, including `filepath`, `label`, `ori_size` as its keys. windows (list): A list of windows coordinates. window_objs (list): A list of labels inside each window. im_dir (str): The output directory path of images. lb_dir (str): The output directory path of labels. allow_background_images (bool): Whether to include background images without labels. Notes: The directory structure assumed for the DOTA dataset: - data_root - images - train - val - labels - train - val rI_____Nr.jpgrz.txtrWcSsg|] }|dqS)z.6gr)rZcoordrrrrrz!crop_and_save..rrb )cv2imreadrstem enumeratetolistr-rDimwriterKrLwriteintjoin)rzro window_objsrSlb_dirZallow_background_imagesimnamerwindowx_starty_startx_stopy_stopnew_namepatch_imphpwrHrYrZZformatted_coordsrrr crop_and_saves& rc Cst|d|}|jdddt|d|}|jdddt||d}t|t||dD]6}t|d||} t|| } t|| | t|t|qZdS) a Split both images and labels. 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)rEtotaldescrGN) rmkdirr[rrDrtr{rrK) rRsave_dirrErmrnrSrrUrzrorrrrsplit_images_and_labelss  rr]r_g?c CsVgg}}|D](}|t|||t||qdD]}t|||||qN)rPrr) rRrrprqratesrmrnrrErrrsplit_trainvals  rc CsHgg}}|D](}|t|||t||qt|dd}|jdddt|dd}|s~Jd|dtt|d} t| t| ddD]} t t | \} } t | | f||d } t | }t| j}| D]`}|\}}}}|d ||d |d |}|||||f}t t||d |qqd S)aZ Split test set of DOTA, labels are not included within this set. Notes: The directory structure assumed for the DOTA dataset: - data_root - images - test and the output directory structure is: - save_dir - images - test r@testTrrArBrCr)rmrnr|r}r~N)rPrrrrJrrKrrDrrrLrtrrrrr)rRrrprqrrmrnrrSrTrVrWrXrorrrrrrrrrrrr split_tests&   r__main__ZDOTAv2z DOTAv2-split)rRr)r )r=)r\r^r`ra)ru)T)r=r\r^)r]r_r)r]r_r)rhrmathrpathlibrrnumpyr"ZPILrrZultralytics.data.utilsrrZultralytics.utils.checksr Zshapely.geometryr r<r[rtr{rrrr__name__rrrrs,        , ! ,  -   $