^j}ddlmZddlZddlZddlZddlZddlmZddlm Z ddl m Z m Z m Z ddlZddlZddlm ZddlmZmZddlmZddlmZdd lmZmZdd lmZmZdd l m!Z!dd l"m#Z#m$Z$m%Z%dd l&m'Z'm(Z(e dZ)dZ*e$ d3dZ+e$d4dZ,e$ d5 d6dZ-e$ej\f d7dZ/eej`dd d8dZ1e$ej\df d9dZ2e$d:dZ3d;dZ4GddZ5eej`dddddejldd ejld!d"ddejld#dd$d ejnejldd%f dd(Z:e e:ejv)e e:ejx)e e:ejz)d*Z> d?d+Z? d@d,Z@dAd-ZA dBd.ZB dCd/ZC dDd0ZD dEd1ZE dFd2ZFy)G) annotationsN)Callable)partial)AnyLiteralcast) TargetMode deprecated)Image) ImageType)Color unify_to_bgr)calculate_optimal_text_scale draw_text)Point) cv2_to_pillow(ensure_cv2_image_for_standalone_function images_to_cv2)create_batchesfill)topbottomct|ttfrtj|}tj |j t}|j\}}}}t|tjr |||||fSt|tjr|j||||fStdt|)a( Crop image based on bounding box coordinates. Args: image: The image to crop. xyxy: Bounding box coordinates in `(x_min, y_min, x_max, y_max)` format. Returns: Cropped image matching input type. Examples: ```pycon >>> import numpy as np >>> import supervision as sv >>> image = np.zeros((1080, 1920, 3), dtype=np.uint8) >>> image.shape (1080, 1920, 3) >>> xyxy = (400, 400, 800, 800) >>> cropped_image = sv.crop_image(image=image, xyxy=xyxy) >>> cropped_image.shape (400, 400, 3) ``` ```pycon >>> image = np.zeros((1920, 1080), dtype=np.uint8) >>> image.shape (1920, 1080) >>> xyxy = (400, 400, 800, 800) >>> cropped_image = sv.crop_image(image=image, xyxy=xyxy) >>> cropped_image.shape (400, 400) ``` ![crop-image](https://media.roboflow.com/supervision-docs/supervision-docs-crop-image-2.png){ align=center width="1000" } z=`image` must be a numpy.ndarray or PIL.Image.Image. Received ) isinstancelisttuplenparrayroundastypeintflattenndarrayr crop TypeErrortype)imagexyxyx_miny_minx_maxy_maxs b/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/supervision/utils/image.py crop_imager/!sX$u &xx~ 88D>  %D!%E5%%$U5[%+-..%%zz5%677  GU }U ct|tjsJ|dkr td|jd|jd}}t ||z}t ||z}t j|||ft jS)a" Scale image by given factor. Scale factor > 1.0 zooms in, < 1.0 zooms out. Args: image: The image to scale. scale_factor: Factor by which to scale the image. Returns: Scaled image matching input type. Raises: ValueError: If scale factor is non-positive. Examples: ```pycon >>> import numpy as np >>> import supervision as sv >>> image = np.zeros((1080, 1920, 3), dtype=np.uint8) >>> image.shape (1080, 1920, 3) >>> scaled_image = sv.scale_image(image=image, scale_factor=0.5) >>> scaled_image.shape (540, 960, 3) ``` ```pycon >>> image = np.zeros((1920, 1080), dtype=np.uint8) >>> image.shape (1920, 1080) >>> scaled_image = sv.scale_image(image=image, scale_factor=0.5) >>> scaled_image.shape (960, 540) ``` ![scale-image](https://media.roboflow.com/supervision-docs/supervision-docs-scale-image-2.png){ align=center width="1000" } rzScale factor must be positive. interpolation) rrr$ ValueErrorshaper"cv2resize INTER_LINEAR)r( scale_factor width_old height_old width_new height_news r. scale_imager?^sR eRZZ (( (q9::!KKNEKKNzII ,-IZ,./J ::ei4CDTDT UUr0cRt|tjsJ|r]|jd|jdz }|d|dz }||k\r|d}t |d|z }n|d}t |d|z}n|\}}t j |||ft jS)a Resize image to specified resolution. Can optionally maintain aspect ratio. Args: image: The image to resize. resolution_wh: Target resolution as `(width, height)`. keep_aspect_ratio: Flag to maintain original aspect ratio. Defaults to `False`. Returns: Resized image matching input type. Examples: ```pycon >>> import numpy as np >>> import supervision as sv >>> image = np.zeros((1080, 1920, 3), dtype=np.uint8) >>> image.shape (1080, 1920, 3) >>> resized_image = sv.resize_image( ... image=image, resolution_wh=(1000, 1000), keep_aspect_ratio=True ... ) >>> resized_image.shape (562, 1000, 3) ``` ```pycon >>> image = np.zeros((1920, 1080), dtype=np.uint8) >>> image.shape (1920, 1080) >>> resized_image = sv.resize_image( ... image=image, resolution_wh=(1000, 1000), keep_aspect_ratio=True ... ) >>> resized_image.shape (1000, 562) ``` ![resize-image](https://media.roboflow.com/supervision-docs/supervision-docs-resize-image-2.png){ align=center width="1000" } r2rr3)rrr$r6r"r7r8r9)r( resolution_whkeep_aspect_ratio image_ratio target_ratior=r>s r. resize_imagerEs` eRZZ (( (kk!nu{{1~5 $Q'-*:: , &%a(I]1- ;>> import numpy as np >>> import supervision as sv >>> image = np.zeros((1080, 1920, 3), dtype=np.uint8) >>> image.shape (1080, 1920, 3) >>> letterboxed_image = sv.letterbox_image( ... image=image, resolution_wh=(1000, 1000) ... ) >>> letterboxed_image.shape (1000, 1000, 3) >>> gray = np.zeros((4, 6), dtype=np.uint8) >>> sv.letterbox_image(image=gray, resolution_wh=(10, 10)).shape (10, 10) ``` ![letterbox-image](https://media.roboflow.com/supervision-docs/supervision-docs-letterbox-image-2.png){ align=center width="1000" } colorT)r(rArBNr2r)value) rrr$rrEr6r7copyMakeBorderBORDER_CONSTANT) r(rArH resized_imager>r= padding_toppadding_bottom padding_left padding_rightimage_with_borderss r.letterbox_imagerSs\ eRZZ (( ( u %E =DM*//3J  #j0Q6K"1% 2[@N!!$y0Q6L!!$y0<?M++  r0z0.27.0z0.31.0)target deprecated_in remove_inc|jdd\}}|jdd\}}|\}}||zdkxs||k\} ||zdkxs||k\} | s| r|St|d} t|d} t|||z} t|||z}t| d}t| d}|t||z|z dz }|t||z|z dz }|jddk(rstj|||||f\}}}}|dddddfdz }tj |||f}|| || | f}|d|z z||zz|dd||| || | f<|S|||||f|| || | f<|S)a Overlay image onto scene at specified anchor point. Handles cases where overlay position is partially or completely outside scene bounds. Args: image: Background scene with shape `(height, width, 3)`. overlay: Image to overlay with shape `(height, width, 3)` or `(height, width, 4)`. anchor: Coordinates `(x, y)` where top-left corner of overlay will be placed. Returns: Scene with overlay applied, shape `(height, width, 3)`. Examples: ```pycon >>> import numpy as np >>> import supervision as sv >>> image = np.zeros((1000, 1000, 3), dtype=np.uint8) >>> overlay = np.zeros((400, 400, 3), dtype=np.uint8) >>> overlay[:] = (0, 255, 0) # Green overlay >>> result_image = sv.overlay_image( ... image=image, overlay=overlay, anchor=(200, 400) ... ) >>> result_image.shape (1000, 1000, 3) ``` NrIrgo@r2)r6maxminr7splitmerge)r(overlayanchor scene_height scene_width image_height image_widthanchor_xanchor_yis_out_horizontallyis_out_verticallyr*r+r,r- crop_x_min crop_y_min crop_x_max crop_y_maxbgralpha overlay_colorrois r. overlay_imagerqsN!& BQL+ ' bq 1L+Hh"[0A5P[9P </14PL8P/ ! E ! E  X 3 4E  h5 6EhY"JhY"JsH{$:k#I1MMJX %< $La PPJ}}Q1 Jz):j+@@ A 1aaDj!E) 1a), E%Ku,-E "]U%::A*-eEk5;&' L +2 z !:j#8 8+ eEk5;&' Lr0g?ct|tjsJd|cxkrdkstdtdtj||j |j }tj|||d|z d||S)aw Tint image with solid color overlay at specified opacity. Args: image: The image to tint. color: Overlay tint color. Defaults to `Color.BLACK`. opacity: Blend ratio between overlay and image (0.0-1.0). Defaults to `0.5`. Returns: Tinted image matching input type. Raises: ValueError: If opacity is outside range [0.0, 1.0]. Examples: ```pycon >>> import numpy as np >>> import supervision as sv >>> image = np.zeros((100, 100, 3), dtype=np.uint8) >>> tinted_image = sv.tint_image( ... image=image, color=sv.Color.ROBOFLOW, opacity=0.5 ... ) >>> tinted_image.shape (100, 100, 3) ``` ![tint-image](https://media.roboflow.com/supervision-docs/supervision-docs-tint-image-2.png){ align=center width="1000" } gg?z#opacity must be between 0.0 and 1.0) fill_valuedtyper2r)src1rnsrc2betagammadst) rrr$r5 full_likeas_bgrrtr7 addWeighted)r(rHopacityr]s r. tint_imager~csJ eRZZ (( ( ' S >?? !>??ll5U\\^5;;OGOO G%a'kPU Lr0ctj|tj}tj|tjS)a Convert image to 3-channel grayscale. Luminance channel is broadcast to all three channels for compatibility with color-based drawing helpers. Args: image: The image to convert to grayscale. Returns: 3-channel grayscale image matching input type. Examples: ```pycon >>> import numpy as np >>> import supervision as sv >>> image = np.ones((100, 100, 3), dtype=np.uint8) * 128 >>> grayscale_image = sv.grayscale_image(image=image) >>> grayscale_image.shape (100, 100, 3) ``` ![grayscale-image](https://media.roboflow.com/supervision-docs/supervision-docs-grayscale-image-2.png){ align=center width="1000" } )r7cvtColorCOLOR_BGR2GRAYCOLOR_GRAY2BGR)r( grayscaleds r.grayscale_imagers16eS%7%78J << C$6$6 77r0ct|tjrO|jdkrt d|j |j dd\}}t |t |fSt|tjr%|j\}}t |t |fStdt|)a Get image width and height as a tuple `(width, height)` for various image formats. Supports both `numpy.ndarray` images (with shape `(H, W, ...)`) and `PIL.Image.Image` inputs. Args: image: Input image. Returns: Image resolution as `(width, height)`. Raises: ValueError: If a `numpy.ndarray` image has fewer than 2 dimensions. TypeError: If `image` is not a supported type (`numpy.ndarray` or `PIL.Image.Image`). Examples: ```pycon >>> import numpy as np >>> import supervision as sv >>> image = np.zeros((1080, 1920, 3), dtype=np.uint8) >>> sv.get_image_resolution_wh(image) (1920, 1080) ``` rIzINumPy image must have at least 2 dimensions (H, W, ...). Received shape: NzC`image` must be a numpy.ndarray or PIL.Image.Image. Received type: ) rrr$ndimr5r6r"r sizer&r')r(heightwidths r.get_image_resolution_whrs8%$ ::>##(;;-1  BQ 5z3v;&&%% v5z3v;&&  u+ ( r0cZeZdZ d ddZddZ d d dZ d dZy) ImageSinkc<||_||_||_d|_y)a Initialize context manager for saving images to directory. Args: target_dir_path: Target directory path where images will be saved. overwrite: Whether to overwrite existing directory. Defaults to `False`. image_name_pattern: File name pattern for saved images. Defaults to `"image_{:05d}.png"`. Examples: ```pycon >>> import numpy as np >>> import supervision as sv >>> import tempfile >>> import os >>> with tempfile.TemporaryDirectory() as tmpdir: ... image = np.zeros((100, 100, 3), dtype=np.uint8) ... with sv.ImageSink(target_dir_path=tmpdir, overwrite=True) as sink: ... sink.save_image(image=image) ... sink.save_image(image=image) ... files = sorted(os.listdir(tmpdir)) ... len(files) 2 ``` rN)target_dir_path overwriteimage_name_pattern image_count)selfrrrs r.__init__zImageSink.__init__s$D /""4r0c.tjj|jrL|jr>t j |jtj|j|Stj|j|SN)ospathexistsrrshutilrmtreemakedirs)rs r. __enter__zImageSink.__enter__ sc 77>>$.. /~~ d223 D001  KK,, - r0Nc|%|jj|j}tjj |j |}tj|||xjdz c_y)aa Save image to target directory with optional custom filename. Args: image: Image to save with shape `(height, width, 3)` in BGR format. image_name: Custom filename for saved image. If `None`, generates name using `image_name_pattern`. Defaults to `None`. Nr2) rformatrrrjoinrr7imwrite)rr( image_name image_paths r. save_imagezImageSink.save_images_  00778H8HIJWW\\$"6"6 C  J& Ar0cyr)rexc_type exc_value exc_tracebacks r.__exit__zImageSink.__exit__'s r0)Fzimage_{:05d}.png)rstrrboolrr)returnrr)r(npt.NDArray[np.uint8]rz str | NonerNone)rztype[BaseException] | NonerzBaseException | Nonerrrr)__name__ __module__ __qualname__rrrrrr0r.rrs "4 %%% %NFJ*8B ( , (     r0ravgz#D9D9D9 z#BFBEBDautoz#262523r2rct|dk(r td|dk(r t|}t|}t|}t |}| t ||}|Dcgc]}t |||}}t|| }t||d|d zkDrtd t|d |d |t|t|d}t| tr| }n| g}t|t|d} t| } t|}t|||||||| | | | | |||}|dk(r t|}tt|Scc}w)a Creates tiles mosaic from input images, automating grid placement and converting images to common resolution maintaining aspect ratio. It is also possible to render text titles on tiles, using optional set of parameters specifying text drawing (see parameters description). Automated grid placement will try to maintain square shape of grid (with size being the nearest integer square root of #images), up to two exceptions: * if there are up to 3 images - images will be displayed in single row * if square-grid placement causes last row to be empty - number of rows is trimmed until last row has at least one image Args: images: Images to create tiles. Elements can be either np.ndarray or PIL.Image, and a common representation will be agreed by the function. grid_size: Expected grid size in format (n_rows, n_cols). If not given, automated grid placement will be applied. One may also provide only one out of two elements of the tuple - then grid will be created with either n_rows or n_cols fixed, leaving the other dimension to be adjusted by the number of images. single_tile_size: Size of a single tile element provided in (width, height) format. If not given, size of tile will be automatically calculated based on `tile_scaling`. tile_scaling: Strategy used to calculate tile size when `single_tile_size` is not given, using the min / max / avg size of images provided in `images`. tile_padding_color: Color to be used in the image letterbox procedure while standardizing tile sizes. If a tuple is provided, it should be in BGR order. tile_margin: Size of margin between tiles, in pixels. tile_margin_color: Color of the tile margin. If a tuple is provided, it should be in BGR order. return_type: Format of the returned image. One may choose a specific format ("cv2" or "pillow") to enforce conversion. "auto" mode takes a majority vote between types of elements in `images`, resolving draws in favour of OpenCV format. "auto" can be safely used when all input images are of the same type. titles: Optional titles to be added to tiles. Elements of that list may be empty - then a specific tile, in the order presented in `images`, will not be filled with a title. It is possible to provide a list of titles shorter than `images` - then remaining titles will be assumed empty. titles_anchors: Anchor points for titles. It is possible to specify an anchor either globally or for specific tiles, following the order of `images`. If not given, either globally or for a specific element of the list, it will be calculated automatically based on `default_title_placement`. titles_color: Color of the title text. If a tuple is provided, it should be in BGR order. titles_scale: Scale of titles. If not provided, the value will be calculated using `calculate_optimal_text_scale(...)`. titles_thickness: Thickness of title text. titles_padding: Size of title padding. titles_text_font: Font used to render titles. Must be an integer constant representing an OpenCV font. (See docs: https://docs.opencv.org/4.x/d6/d6e/group__imgproc__draw.html) titles_background_color: Color of the title text padding. default_title_placement: Title anchor placement used when an explicit anchor is not provided. Returns: ImageType: Image with all input images located in tiles grid. The output type is determined by `return_type` parameter. Raises: ValueError: In case when input images list is empty, provided `grid_size` is too small to fit all images, `tile_scaling` mode is invalid. rz7Could not create image tiles from empty list of images.rimagesrGNrmode)r(rArH)r grid_sizer2zCould not place z in grid with size: .)sequence desired_sizecontent)rrsingle_tile_sizetile_padding_color tile_margintile_margin_colortitlestitles_anchors titles_color titles_scaletitles_thicknesstitles_paddingtitles_text_fonttitles_background_colordefault_title_placementpillow)r()lenr5_negotiate_tiles_formatrr_aggregate_images_shaperS_establish_grid_sizerrr_generate_tilesrrr )rrr tile_scalingrrr return_typerrrrrrrrriresized_imagestitles_anchors_sequencetiless r. create_tilesr0sz 6{aRSSf-V< %,>?$+<= & )F2&|T    #3;M N %FiHI 6{Yq\IaL00s6{m+? {! L  vCKN.$'"0#1"2(s6{DN l3L*1HI )-+%!!)%) 7 7 E"hE*  5 !!Ss"EcLtd|D}|dzt|k\ryy)Nc3bK|]'}tt|tj)ywr) issubclassr'rr$).0rs r. z*_negotiate_tiles_format..sN!ja"**=Ns-/rIr7r)sumr)rnumber_of_np_arrayss r.rrs*NvNNQ#f+- r0c t||Dcgc]}|jdc}}t||Dcgc]}|jdc}}||fScc}wcc}w)Nrr2)r r6)r aggregatorrrrs r."_calculate_aggregated_images_shapersZ:6:aqwwqz:; .s=aT =srrr2)all_negotiate_grid_sizemathceilrrrr")rrcolumnsrowss r.rrsC=9==#622|A,"""yyVw./88||TYYs6{T1222 c3h ++r0ct|tkr dt|fStjt j t|}|}|}||dz zt|k\r|dz}||dz zt|k\r||fS)Nr2)rMAX_COLUMNS_FOR_SINGLE_ROW_GRIDrrrsqrt)r nearest_sqrtproposed_columns proposed_rowss r.rrs 6{55#f+~99RWWS[12L# M ma/ 0CK ?  ma/ 0CK ? * **r0c t||||| | | | | | }|\}}tt||}t|d|kr1|dj t ||t|d|kr1t||kr/|j t ||g|zt||kr/t |||||S)N) rrrrrrrrrr)r batch_sizer6rH)tiles_elementsrrrr) _draw_textsrrrappend_generate_color_image_merge_tiles_elements)rrrrrrrrrrrrrrrrrrs r.rrs"%!!)%) 7 7 FMD'.&WMNN nR !G +r!! !(8@R S  nR !G + n  $ ")9AS T U   n  $ !%)+  r0c b||St||| } |#|djdd\} } t| | f}g} t||| D]e\}}}|| j |t |||t j|||||t j| }| j |g| S)N)rrrrrI)rA) scenetext text_anchor text_color text_scaletext_thickness text_padding text_fontbackground_color)_prepare_default_titles_anchorsr6rziprrr from_bgr_tuple)rrrrrrrrrrprepared_titles_anchorsrarbresultr(rr^processed_images r.rr0s~ =% 7 $*1IOOBQ$7! k3& 5 F"663JK'tV < MM% #++L9#+'&"112IJ    o&' Mr0cg}t||D]h\}}||j||jdd\}}|dk(rt|dz |dz}nt|dz |dz}|j|j|S)NrIrg?)xyg?)r rr6r) rrrr r(r^rarbdefault_anchors r.rr\s FV^4 & v   MM& ! $)KKO! k "e +"[1_ s8JKN"[1_ s8JKN n% & Mr0ctj|d|dftj|z}|Dcgc]S}tjt t j jt||g|dzdddU}}|djd}tj||dftj|z} g} |D]$}| j|| j| &ttjtjtj| dddjtjScc}w)Nr2rrtr)axisr)ronesuint8 concatenater itertoolschain from_iterabler r6rrnptNDArrayr!) rrrrrvertical_paddingrow merged_rows row_widthhorizontal_paddingrows_with_paddingss r.rrosW !!$k15RXXF  "    --./)A,>? r      K A$$Q'I i+288rCsm" $%% ,+6J+ =?+"#*9 9 B99*9x*/V*/Vd*$<V <V"<V<V <V*<V~*+0++A A"A (A A*AH    E E "E E E  EP*;;, , ,, ,*,^*8*8<,^L L ^   7;/3167Eu~~i7P6DennY6O4:&*8<1? 1J!%44