^j:ddlmZddlZddlmZddlmZmZmZddl Z ddl Z ddl mZ ddlmZddlmZmZddlmZej*eZddZ dd Z dd Zdd Z dd Zdd Z ddZ ddZy)) annotationsN)chain)AnyUnioncast)CLASS_NAME_DATA_FIELD)polygon_to_mask rle_to_mask)Vectorch|jsy|j}t|jjjdd}d}||k7r@t |d|dz |d|dz }|d|d|zz dz |d|d|zz dz f}t |dt |d}}t |d|dz t |d|dz }}g} |jjjj} t| jdD]P} | | } | ||||f} | j|k7rtj| |d|df} | j| Rttjt j"t!j$| t&S)N)rrrdtype)masks orig_shapetupledatashapeminintcpunumpyrangecv2resizeappendrnptNDArraynpbool_asarraybool) yolov8_resultsrinference_shapepadgaintopleftbottomright mask_mapsrimasks o/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/supervision/detection/utils/internal.pyextract_ultralytics_masksr0s   **JN0055;;AB?@O C*$ A A . A A .  Q *Q-$"6 6! ; Q *Q-$"6 6! ;  CF SQ[C*SV34c/!:LsSTv:U6VEFI  % % ) ) + 1 1 3E 5;;q> "QxCJU *+ :: #::dZ]JqM$BCD  BHH%rzz)4'H IIc  |dstjdtjtjdtjtjdtjddttjdt ifSg}g}g}g}g}g}t |dd}t |dd}|dD]} | d } | d } | d} | d} | | d z z }| | d z z }|| z}|| z}| jd xs| jd }t|trddhj|sd}|{ |d\}}t|d||f}||f||fk7rXtj|jtj||ftj jt"}|~|j1||||g|j1| d|j1| d|j1| d|j1d| vsb|j1| dxd| vrm|j1||||g|j1| d|j1| d|j1| dd| vs|j1| dt3| ddk\stj4| dDcgc] }|d |d gc}t }t7|||fjt"}|j1||||g|j1| d|j1| d|j1| d|j1|d| vs|j1| dt3|dkDr%tj4|tjntjd}t3|dkDr%tj4|tjntjd}t3|dkDr%tj4|tjn$tjdtj}t3|dkDrtj4|ntjdt }t3|dkDrtj4|t"nd}t3|dkDr%tj4|tjnd}t|i}||||||fS#t$t&t(t*f$r#}t,j/d|d}Yd}~d}~wwxYwcc}w)aParse a Roboflow API or Inference package result into detection arrays. The returned ``data`` dict always contains ``CLASS_NAME_DATA_FIELD`` as a string-dtype NumPy array. When ``predictions`` is empty, the array has shape ``(0,)`` with ``dtype=str``, preserving dtype contracts for callers that mix empty and non-empty results. Args: roboflow_result: Raw dict from the Roboflow REST API or the Inference package (after ``.dict()`` serialisation). Returns: A 6-tuple of ``(xyxy, confidence, class_id, masks, tracker_ids, data)`` where each array is aligned with the others. ``masks`` and ``tracker_ids`` are ``None`` when absent from the predictions. Examples: >>> from supervision.detection.utils.internal import process_roboflow_result >>> result = {"predictions": [], "image": {"width": 100, "height": 100}} >>> _, _, _, _, _, data = process_roboflow_result(result) >>> data["class_name"].dtype.kind 'U' predictions)rrrNimagewidthheightxyrrlerle_masksizecounts) interpolationzQFailed to decode RLE mask payload; falling back to box-only detection. Reason: %sclass_idclass confidence tracker_idpoints) resolution_wh)r emptyfloat64int64rstrrget isinstancedictissubsetr rrastypeuint8 INTER_NEARESTr# ValueErrorAssertionErrorKeyError TypeErrorloggerwarningrlenarrayr ) roboflow_resultxyxyrAr? class_namer tracker_ids image_width image_height predictionr8r9r6r7x_miny_minx_maxy_maxrle_datahwr.excpointpolygonxyxy_arrconfidence_arr class_id_arrclass_name_arr masks_arrtracker_id_arrrs r/process_roboflow_resultrp6sB = ) HHV2:: . HHQbjj ) HHQbhh '   "BHHQc$: ;   !D JHJ)+EKog.w78Kw/9:L%m4== sO sO7#H%EAI FQJ >>%(FJNN:,F(D)  2  (8 2H   '1"8H#51v>q6lK88:: BHH-$l3&)&7&7fTl    KKue4 5 OOJz2 3   j1 2   j6 7 LL z)"":l#;< Z ' KKue4 5 OOJz2 3   j1 2   j6 7z)"":l#;< H% &! +hh7A(7KLe%*eCj)LTWG# \'BfTl  KKue4 5 OOJz2 3   j1 2   j6 7 LL z)"":l#;<{==@-0IMRZZ(rxx?O 36j/A2E2::.288TU; x=1  * XXarxx ( !$J! 3!39O(+5zA~d#425[1AA1EBHH-41F~/VD   w)D ,    0MsA:T0U/ 0U, U''U,ctjtjk(xrtfdDS)z Compares the data payloads of two Detections instances. Args: data_a, data_b: The data payloads of the instances. Returns: True if the data payloads are equal, False otherwise. c3VK|] }tj||"ywN)r array_equal).0keydata_adata_bs r/ z is_data_equal..s)<58vc{F3K0<s&)setkeysall)rwrxs``r/ is_data_equalr~sA v{{} V[[]!3 3 <.smD  z# 3:c?BJJ7 z# 38 _ 3 /  0DsA+A.rz)rrs``r/is_metadata_equalrsH z !S):%; ; DDAr1c|siS|Dcgc]}t|jc}tfdDs td|D]J}|j Dcgc] }t |}}t t|dkDsAtddDcic]}|g}}|D] }|D]}||j ||"|D]}td||Dr%ttj||||<=td||Drc||dj}|dk(rtj||||<|dkDrtj||||<td|d td |d ttt t"t$j&tj(tt*ff|Scc}wcc}wcc}w) a Merges the data payloads of a list of Detections instances. Warning: Assumes that empty detections were filtered-out before passing data to this function. Args: data_list: The data payloads of the Detections instances. Each data payload is a dictionary with the same keys, and the values are either lists or npt.NDArray[np.generic]. Returns: A single data payload containing the merged data, preserving the original data types (list or npt.NDArray[np.generic]). Raises: ValueError: If data values within a single object have different lengths or if dictionaries have different keys. c3.K|] }|dk(ywrNrukeys_set all_keys_setss r/ryzmerge_data.. Jx=++Jz7All data dictionaries must have the same keys to merge.r z>All data values within a single object must have equal length.rc3<K|]}t|tywrs)rKlistruitems r/ryzmerge_data..sC$z$%Csc3PK|]}t|tj ywrs)rKr rrs r/ryzmerge_data..sK$D"**-Ks$&z$Unexpected array dimension for key ''.z!Inconsistent data types for key 'z.'. Only np.ndarray and list types are allowed.)r{r|r}rQvaluesrWrrr from_iterablendimr hstackvstackrrLrIrrrgenericr) data_listrvaluelengthsrv merged_datarrs @r/ merge_datars,  2;<$S% C #%99[-=#> C  #GuB!OPP3C59%& " S% BJJ 7c BCCDk RRC= : #Hs G&#G+" G0ct|siS|Dcgc]}t|jc}tfdDs tdi}|D]}|j D]\}}||vr|||<||}t |t jrCt |t jr)t j|||rctd|dt |t jst |t jrtd|d|||k7std|d|Scc}w)aS Merge metadata from a list of metadata dictionaries. This function combines the metadata dictionaries. If a key appears in more than one dictionary, the values must be identical for the merge to succeed. Warning: Assumes that empty detections were filtered-out before passing metadata to this function. Args: metadata_list: A list of metadata dictionaries to merge. Returns: A single merged metadata dictionary. Raises: ValueError: If there are conflicting values for the same key or if dictionaries have different keys. c3.K|] }|dk(ywrrrs r/ryz!merge_metadata..Frrz;All metadata dictionaries must have the same keys to merge.zConflicting metadata for key: 'z&': {type(value)}, {type(other_value)}.r) r{r|r}rQitemsrKr rrt) metadata_listmetadatamerged_metadatarvr other_valuers @r/merge_metadatar.sL(  :GHhS)HM JMJ JVWW&(O!P"..* PJC/)',$)#.K%,K1T~~oc&:EB$9#?>>E2::.*["**2U 5cU;:: #3'50$'Fse2%NOO) PP. 9Is D5c i}|jD]/\}}t|tjr ||||<*t|trt|t r ||||<St|tr|Dcgc]}|| c}||<zt|tjrR|j tk(r(t|Dcgc] \}}|s ||c}}||<|Dcgc]}|| c}||<t|tr ||g||<tdt|td|dt||Scc}wcc}}wcc}w)a6 Retrieve a subset of the data dictionary based on the given index. Args: data: The data dictionary of the Detections object. index: The index or indices specifying the subset to retrieve. Returns: A subset of the data dictionary corresponding to the specified index. zUnsupported index type: zUnsupported data type for key 'z': ) rrKr rrslicerr# enumeraterrTtype)rindex subset_datarvrr- index_values r/ get_data_itemrdsLCEKjjlU U eRZZ ($U|K  t $%'#(< C E4(6;#<E!H#< C E2::.;;$&7@7G(%3Q ;a(K$;@'@Qa'@K$E3'$)%L> C ":4;- HII=cU#d5k]ST T)U, $=((As: E E E & Ectj|jj|jjz |jj |jj z g}tj|jj|jj g}t tjtjtj|||z S)a) Get array of cross products of each anchor with a vector. Args: anchors: Array of anchors of shape (number of anchors, detections, 2) vector: Vector to calculate cross product with Returns: Array of cross products of shape (number of anchors, detections) ) r rXendr8startr9rrrnumbercross)anchorsvectorvector_at_zero vector_starts r/ cross_productrsXX JJLL6<<>> ) JJLL6<<>> ) N 88V\\^^V\\^^<=L  BII<9O P r1)r$rreturnznpt.NDArray[np.bool_] | None)rYdict[str, Any]rztuple[npt.NDArray[np.floating], npt.NDArray[np.floating], npt.NDArray[np.integer], npt.NDArray[np.bool_] | None, npt.NDArray[np.integer] | None, dict[str, npt.NDArray[np.generic]]])rw.dict[str, npt.NDArray[np.generic] | list[Any]]rxrrr#)rrrrrr#)rz4list[dict[str, npt.NDArray[np.generic] | list[Any]]]rr)rzlist[dict[str, Any]]rr)rrrzrs"## 4O,   8 $!JHQ#QQh : : $*:SC:S3:Sz3l% 8% G%4%P #-3r1