FPhVPddlZddlZddlZddlZddlmZddlmZddlm Z ddl m Z ddl Z ddl ZddlZddlZddlmZddlmZmZddlmZmZmZmZdd lmZeGd d ZGd d ZGddZGddZ GddZ!GddZ"dZ#ee!e efZ$ddZ%y)N) dataclass)Path)Thread)urlparse)Image) IMG_FORMATS VID_FORMATS)LOGGERis_colab is_kaggleops)check_requirementscJeZdZUdZdZeed<dZeed<dZeed<dZ eed<y) SourceTypeszBClass to represent various types of input sources for predictions.Fwebcam screenshotfrom_imgtensorN) __name__ __module__ __qualname____doc__rbool__annotations__rrrcC:\Users\daisl\Desktop\realtime-object-detection\venv\Lib\site-packages\ultralytics/data/loaders.pyrrs-LFDJHdFDrrc6eZdZdZd dZdZdZdZdZdZ y) LoadStreamsa Stream Loader for various types of video streams. Suitable for use with `yolo predict source='rtsp://example.com/media.mp4'`, supports RTSP, RTMP, HTTP, and TCP streams. Attributes: sources (str): The source input paths or URLs for the video streams. imgsz (int): The image size for processing, defaults to 640. vid_stride (int): Video frame-rate stride, defaults to 1. buffer (bool): Whether to buffer input streams, defaults to False. running (bool): Flag to indicate if the streaming thread is running. mode (str): Set to 'stream' indicating real-time capture. imgs (list): List of image frames for each stream. fps (list): List of FPS for each stream. frames (list): List of total frames for each stream. threads (list): List of threads for each stream. shape (list): List of shapes for each stream. caps (list): List of cv2.VideoCapture objects for each stream. bs (int): Batch size for processing. Methods: __init__: Initialize the stream loader. update: Read stream frames in daemon thread. close: Close stream loader and release resources. __iter__: Returns an iterator object for the class. __next__: Returns source paths, transformed, and original images for processing. __len__: Return the length of the sources object. c Vdtjj_||_d|_d|_||_||_tjj|r't|jjn|g}t|}|Dcgc]}t!j"|c}|_gg|zdg|zdg|zdg|zgg|zf\|_|_|_|_|_dg|z|_t3|D]\}}|dzd|d|d} t5|j6d vr t9|}|j;r t=|n|}|dk(rt?s tAr tCd tEjF||j0|<|j0|jIstK| d |tM|j0|jOtDjP} tM|j0|jOtDjR} |j0|jOtDjT} tWtM|j0|jOtDjXdxs t[d |j*|<tWt]j^| r| ndd zdxsd|j(|<|j0|ja\} }| r|tK| d||j&|jc||j.|j.|<te|jf||j0||gd|j,|<tijj| d|j*|d| d| d|j(|dd |j,|jmtijjd|jo|_8ycc}w)zKInitialize instance variables and check for consistent input stream shapes.TstreamrN/: z... )zwww.youtube.comz youtube.comzyoutu.bezm'source=0' webcam not supported in Colab and Kaggle notebooks. Try running 'source=0' in a local environment.zFailed to open infdzFailed to read images from )targetargsdaemonu Success ✅ (z frames of shape xz at z.2fz FPS))9torchbackendscudnn benchmarkbufferrunningmodeimgsz vid_strideospathisfiler read_textrsplitlenr clean_strsourcesimgsfpsframesthreadsshapecaps enumeraterhostnameget_best_youtube_url isnumericevalr r NotImplementedErrorcv2 VideoCaptureisOpenedConnectionErrorintgetCAP_PROP_FRAME_WIDTHCAP_PROP_FRAME_HEIGHT CAP_PROP_FPSmaxCAP_PROP_FRAME_COUNTfloatmathisfinitereadappendrupdater infostart__len__bs)selfr=r4r5r1nr+isstwhr?successims r__init__zLoadStreams.__init__>s)-&    $8:w8O$w-))+224V]U^ L29:'Q a(': FHTAXPQsUVwYZX[^_X_bfagjkaknpmqtumuEuB 48T[$, FQJ g&DAqE7!A3b4(B{##'UU(+;;=QaAAv8:)+[\\++A.DIIaL99Q<((*%OA3&?@@DIIaL$$S%=%=>?ADIIaL$$S%>%>?@A))A,""3#3#34C TYYq\%5%5c6N6N%O!PRSTX]YDKKNdmmC&8sa3FJPbDHHQK))A,++-KGRbj%,Gs&KLL IIaL   #HHDJJqM$DKK499Qgrabr5retrievenpzerosrBuint8r warningopenr1rYtimesleep)r_racapr!r`frfrgs rrZzLoadStreams.updatels$++a.1lls||~!q1u+499Q< 2%Q t&!+"%,,.KGR"XXdjjm288D'z{({{ ! ++B/(*t !  4 lls||~!q1u+~l+~lrcBd|_|jD]%}|js|jd'|jD]} |j tjy#t $r"}tjd|Yd}~Qd}~wwxYw)z*Close stream loader and release resources.F)timeoutu6WARNING ⚠️ Could not release VideoCapture object: N) r2rAis_alivejoinrCrelease Exceptionr rqrJdestroyAllWindows)r_threadrues rclosezLoadStreams.closes llF  A &#99C ]   ]!WXYWZ[\\ ]s A33 B<BBcd|_|S)zCIterates through YOLO image feed and re-opens unresponsive streams.countr_s r__iter__zLoadStreams.__iter__s  rc |xjdz c_g}t|jD]D\}}|s|j|j r!t j dtdk(r|jttjdt|jz |j|}|stjd||s|j r!|j#|j%d|j#|r|j%dn1t'j(|j*|t&j,|j/G|j0|ddfS) zEReturns source paths, transformed and original images for processing.r"qu"WARNING ⚠️ Waiting for stream rrrjNr,)rrDr>rArzrJwaitKeyordr StopIterationrsrtminr?r rqr1rYpoprnrorBrpclearr=)r_imagesrar+s r__next__zLoadStreams.__next__s a dii(DAq||A//1S[[^s3x5OJJL'' 1s488},-IIaLNN%Gs#KL{{ aeeAh' 1aeeBi"((4::a=PRPXPX2YZ ')*||VT2--rc,t|jS)z(Return the length of the sources object.)r;r=rs rr]zLoadStreams.__len__s4<<  rN)z file.streamsr"F) rrrrrhrZrrrr]rrrrr s&:,!\!(   .8!rrc$eZdZdZddZdZdZy)LoadScreenshotsa YOLOv8 screenshot dataloader. This class manages the loading of screenshot images for processing with YOLOv8. Suitable for use with `yolo predict source=screen`. Attributes: source (str): The source input indicating which screen to capture. imgsz (int): The image size for processing, defaults to 640. screen (int): The screen number to capture. left (int): The left coordinate for screen capture area. top (int): The top coordinate for screen capture area. width (int): The width of the screen capture area. height (int): The height of the screen capture area. mode (str): Set to 'stream' indicating real-time capture. frame (int): Counter for captured frames. sct (mss.mss): Screen capture object from `mss` library. bs (int): Batch size, set to 1. monitor (dict): Monitor configuration details. Methods: __iter__: Returns an iterator object. __next__: Captures the next screenshot and returns it. ctdddl}|j^}}d\|_}}}}t |dk(rt |d|_n?t |dk(rd|D\}}}}n"t |dk(rd |D\|_}}}}||_d |_d|_|j|_ d|_ |jj|j} || d n| d |z|_ || d n| d |z|_ |xs| d |_|xs| d|_|j|j|j|jd|_y)z8Source = [screen_number left top width height] (pixels).mssrN)rNNNNr"c32K|]}t|ywNrN.0r+s r z+LoadScreenshots.__init__..s'?1Arxc32K|]}t|ywrrrs rrz+LoadScreenshots.__init__..s4LVSVVrr!topleftwidthheight)rrrr)rrsplitscreenr;rNr4r3framesctr^monitorsrrrrmonitor) r_sourcer4rparamsrrrrrs rrhzLoadScreenshots.__init__sG5! ,,.0I- T3v v;! fQi.DK [A '?'? $D#uf [A 4LV4L 1DKsE6   779((##DKK0%([75>wu~7K'+|GFO'&/D:P .gg. 1 1 $ $((TZZ[_[f[fg rc|S)z"Returns an iterator of the object.rrs rrzLoadScreenshots.__iter__s rc rtj|jj|jddddddf}d|j d|j d|jd|jd|jd }|xjdz c_ t|j g|gd|fS)z?mss screen capture: get raw pixels from the screen as np array.Nzscreen z (LTWH): ,r$r") rnasarrayrrlrrrrrrrstr)r_im0rbs rrzLoadScreenshots.__next__sjjt||45aBQBh?dkk])DII;az4::,aPTP[P[}\^ _ a DKK !C5$11rNr)rrrrrhrrrrrrrs2h62rrc0eZdZdZddZdZdZdZdZy) LoadImagesa0 YOLOv8 image/video dataloader. This class manages the loading and pre-processing of image and video data for YOLOv8. It supports loading from various formats, including single image files, video files, and lists of image and video paths. Attributes: imgsz (int): Image size, defaults to 640. files (list): List of image and video file paths. nf (int): Total number of files (images and videos). video_flag (list): Flags indicating whether a file is a video (True) or an image (False). mode (str): Current mode, 'image' or 'video'. vid_stride (int): Stride for video frame-rate, defaults to 1. bs (int): Batch size, set to 1 for this class. cap (cv2.VideoCapture): Video capture object for OpenCV. frame (int): Frame counter for video. frames (int): Total number of frames in the video. count (int): Counter for iteration, initialized at 0 during `__iter__()`. Methods: _new_video(path): Create a new cv2.VideoCapture object for a given video path. c d}t|trTt|jdk(r>M#NUaggcl2&6&<&<&>+&M!UN"NUaggcl2&6&<&<&>+&M!UNVc&kB f_ r' 'B,$"4 $ v; OOF1I &DH 77a<#&CA3GGGRmS]^i]j%lm m ONs-K/K/-K4>K4cd|_|S)z:Returns an iterator object for VideoStream or ImageFolder.rrrs rrzLoadImages.__iter__4  rc |j|jk(rt|j|j}|j|jrEd|_t |jD]}|jj|jj\}}|s|xjdz c_|jj|j|jk(rt|j|j}|j||jj\}}|s|xjdz c_d|jdzd|jd|jd|jd|d }nZ|xjdz c_t!j"|}|t%d|d |jd|jd |d}|g|g|j|fS) z2Return next image, path and metadata from dataset.videor"zvideo r#z (z) r$zImage Not Found zimage  )rrrrrr3ranger5rurlrmr|rrXrr@rJimreadr)r_r7_rfrrbs rrzLoadImages.__next__9s ::  zz$**% ??4:: &DI4??+ ,88,,.LGS a   "::(''zz$**-%#xx}}  JJ!OJa($''"TZZL$++bQUPVVXYA JJ!OJ**T"C{'*:4&(ABB AdggYavR8Avudhh))rcd|_tj||_t |jj tj |jz |_y)z"Create a new video capture object.rN) rrJrKrurNrOrTr5r@)r_r7s rrzLoadImages._new_video\sC ##D)$((,,s'?'?@4??RS rc|jS)z*Returns the number of files in the object.)rrs rr]zLoadImages.__len__b wwrN)rr") rrrrrhrrrr]rrrrrs$.%mN !*FT rrc:eZdZdZddZedZdZdZdZ y) LoadPilAndNumpya< Load images from PIL and Numpy arrays for batch processing. This class is designed to manage loading and pre-processing of image data from both PIL and Numpy formats. It performs basic validation and format conversion to ensure that the images are in the required format for downstream processing. Attributes: paths (list): List of image paths or autogenerated filenames. im0 (list): List of images stored as Numpy arrays. imgsz (int): Image size, defaults to 640. mode (str): Type of data being processed, defaults to 'image'. bs (int): Batch size, equivalent to the length of `im0`. count (int): Counter for iteration, initialized at 0 during `__iter__()`. Methods: _single_check(im): Validate and format a single image to a Numpy array. c <t|ts|g}t|Dcgc]\}}t|dd|dc}}|_|Dcgc]}|j |c}|_||_d|_t|j |_ ycc}}wcc}w)z$Initialize PIL and Numpy Dataloader.filenamer.jpgN) rrrDgetattrpaths _single_checkrr4r3r;r^)r_rr4rargs rrhzLoadPilAndNumpy.__init__{s#t$%CLUVYN[N51bgb*aSo>N[ 589SrD&&r*S9  dhh- \9s B Bcbt|tjtjfsJdt |t|tjrW|j dk7r|j d}tj|dddddddf}tj|}|S)z,Validate and format an image to numpy array.z,Expected PIL/np.ndarray image type, but got RGBNr) rrrnndarraytyper3convertrascontiguousarray)rgs rrzLoadPilAndNumpy._single_checks"u{{BJJ78sN[ [s A/cd|dt|jd}t|jdk7rIt|jdk7r t|t j ||j d}|jd|zs|jd|zr t||jdkDr:t j d |jd |jd z }|S) z-Validate and format an image to torch.Tensor.uaWARNING ⚠️ torch.Tensor inputs should be BCHW i.e. shape(1, 3, 640, 640) divisible by stride z . Input shapez is incompatible.rrrg?uQWARNING ⚠️ torch.Tensor inputs should be normalized 0.0-1.0 but max value is z. Dividing input by 255.go@) rrBr; ValueErrorr rq unsqueezerSrU)rgstriderbs rrzLoadTensor._single_checks##)(-bhh7HHY [ rxx=A 288}! m# NN1 aB 88A; 288A;#7Q-  668c> NNnoqououownxy45 6e#B rcd|_|S)zReturns an iterator object.rrrs rrzLoadTensor.__iter__rrc|jdk(rt|xjdz c_|j|jddfS)z!Return next item in the iterator.r"Nr,rrs rrzLoadTensor.__next__rrc|jS)zReturns the batch size.)r^rs rr]zLoadTensor.__len__rr)returnN) ) rrrrrhrrrrr]rrrrrs0 \$ .rrc g}|D]}t|ttfr`|jt j t|j dr!tj|djn|yt|tjtjfr|j|tdt|jd|S)zUMerges a list of source of different types into a list of numpy arrays or PIL images.httpT)r!ztype z is not a supported Ultralytics prediction source type. See https://docs.ultralytics.com/modes/predict for supported source types.)rrrrYrrr startswithrequestsrOrawrnr TypeErrorrr)rrrgs r autocast_listrs E b3+ & LLRI[I[\bIcHLLD$A$E$Eikl m U[["**5 6 LL eDH$5$5#67ijk k  Lrc|r:tdddl}|j|jdjStdddl}|j ddi5}|j|d }dddtjd gD]d}|jd xsdd k\xs|jdxsddk\}|s8|ddk7sA|ddk(sJ|ddk(sS|jdcSy#1swYxYw)aE Retrieves the URL of the best quality MP4 video stream from a given YouTube video. This function uses the pafy or yt_dlp library to extract the video info from YouTube. It then finds the highest quality MP4 format that has video codec but no audio codec, and returns the URL of this video stream. Args: url (str): The URL of the YouTube video. use_pafy (bool): Use the pafy package, default=True, otherwise use yt_dlp package. Returns: (str): The URL of the best quality MP4 video stream, or None if no suitable stream is found. )pafyzyoutube_dl==2020.12.2rNmp4)preftypezyt-dlpquietTF)downloadformatsriri8vcodecnoneacodecexturl) rrnew getbestvideoryt_dlp YoutubeDL extract_inforeversedrO)ruse_pafyrrydl info_dictrv good_sizes rrFrFs<=xx}))5)9===8$   wo .#((u(=I/)-- 267Aw,15W!%%/:NQSW9WIQx[F2q{f7LQRSXQY]bQbuuU|# 8/ .s C>>D)F)&rrVr6rs dataclassesrpathlibr threadingr urllib.parserrJnumpyrnrr-PILrultralytics.data.utilsrr ultralytics.utilsr r r r ultralytics.utils.checksrrrrrrrrLOADERSrFrrrr's !!  ;>>7  P!P!f?2?2Dood88v99x   O C$r