h$VSSKrSSKJr SSKrSSKJrJrJr SSKJ r "SS\5r g)N)Any) BaseSolutionSolutionAnnotatorSolutionResults)colorsc h^\rSrSrSrS\SS4U4SjjrS\S\S \S \S \SS4 S jrS\ 4S jr Sr U=r $)DistanceCalculation a A class to calculate distance between two objects in a real-time video stream based on their tracks. This class extends BaseSolution to provide functionality for selecting objects and calculating the distance between them in a video stream using YOLO object detection and tracking. Attributes: left_mouse_count (int): Counter for left mouse button clicks. selected_boxes (dict[int, list[float]]): Dictionary to store selected bounding boxes and their track IDs. centroids (list[list[int]]): List to store centroids of selected bounding boxes. Methods: mouse_event_for_distance: Handle mouse events for selecting objects in the video stream. process: Process video frames and calculate the distance between selected objects. Examples: >>> distance_calc = DistanceCalculation() >>> frame = cv2.imread("frame.jpg") >>> results = distance_calc.process(frame) >>> cv2.imshow("Distance Calculation", results.plot_im) >>> cv2.waitKey(0) kwargsreturnNc P>[TU]"S0UD6 SUl0Ul/Ulg)zYInitialize the DistanceCalculation class for measuring object distances in video streams.rN)super__init__left_mouse_countselected_boxes centroids)selfr __class__s d/home/james-whalen/.local/lib/python3.13/site-packages/ultralytics/solutions/distance_calculation.pyrDistanceCalculation.__init__$s, "6"!"68*,eventxyflagsparamcU[R:XaU=RS- slURS::a{[URUR 5HVupgUSUs=:a US:dMO MUSUs=:a US:dM3O M7XpR ;dMHX`R U'MX ggU[R:Xa0UlSUlgg)aX Handle mouse events to select regions in a real-time video stream for distance calculation. Args: event (int): Type of mouse event (e.g., cv2.EVENT_MOUSEMOVE, cv2.EVENT_LBUTTONDOWN). x (int): X-coordinate of the mouse pointer. y (int): Y-coordinate of the mouse pointer. flags (int): Flags associated with the event (e.g., cv2.EVENT_FLAG_CTRLKEY, cv2.EVENT_FLAG_SHIFTKEY). param (Any): Additional parameters passed to the function. Examples: >>> # Assuming 'dc' is an instance of DistanceCalculation >>> cv2.setMouseCallback("window_name", dc.mouse_event_for_distance) rN)cv2EVENT_LBUTTONDOWNrzipboxes track_idsrEVENT_RBUTTONDOWN)rrrrrrboxtrack_ids rmouse_event_for_distance,DistanceCalculation.mouse_event_for_distance-s C)) )  ! !Q & !$$)%(T^^%DMC1v*CF**s1v/BCF/B/BxWjWjGj8;++H5&E* c++ +"$D $%D !,rc "URU5 [XRS9nSn[URUR UR UR5HupEpgURU[[U5S5URXgU5S9 [UR5S:XdMUURR5HnX:XdM X@RU'M M [UR5S:XaURR!URR#5Vs/sH1n[USUS-S-5[USUS-S-5/PM3 sn5 [$R&"URSSURSS- S-URSSURSS- S--5nUR)X0R5 /UlUR+5n UR-U 5 UR.R1S5(a2UR2(a![4R6"S UR85 [;X[UR 5S 9$s snf) ah Process a video frame and calculate the distance between two selected bounding boxes. This method extracts tracks from the input frame, annotates bounding boxes, and calculates the distance between two user-selected objects if they have been chosen. Args: im0 (np.ndarray): The input image frame to process. Returns: (SolutionResults): Contains processed image `plot_im`, `total_tracks` (int) representing the total number of tracked objects, and `pixels_distance` (float) representing the distance between selected objects in pixels. Examples: >>> import numpy as np >>> from ultralytics.solutions import DistanceCalculation >>> dc = DistanceCalculation() >>> frame = np.random.randint(0, 255, (480, 640, 3), dtype=np.uint8) >>> results = dc.process(frame) >>> print(f"Distance: {results.pixels_distance:.2f} pixels") ) line_widthrT)colorlabelr rr!showzUltralytics Solutions)plot_impixels_distance total_tracks)extract_tracksrr-r$r%r&clssconfs box_labelrintadjust_box_labellenrkeysrextendvaluesmathsqrtplot_distance_and_lineresultdisplay_outputCFGget env_checkr"setMouseCallbackr*r) rim0 annotatorr2r(r)clsconftrk_idr1s rprocessDistanceCalculation.processGs5. C %cooF (+DJJ SWS]S](^ $C3   6#c(D+AI^I^_bjrIs  t4&&'1,"11668F)8;++H59 )_ t"" #q ( NN ! !W[WjWjWqWqWstWsPS#s1vA1,-sCFSVO3I/JKWst #ii"1%q(9!(<<BdnnUVFWXYFZ]a]k]klm]nop]qFqvwEwwO  , ,_nn M""$ G$ 88<<  DNN  !8$:W:W Xw^abfbpbp^qrrus68J )rrr) __name__ __module__ __qualname____firstlineno____doc__rrr8r*rrL__static_attributes__ __classcell__)rs@rr r s`.---&c&c&c&#&VY&^b&47so7s7srr ) r>typingrr"ultralytics.solutions.solutionsrrrultralytics.utils.plottingrr rrrrXs)  \\-rs,rsr