o W hF@sddlmZddlmZddlmZddlmZddlZ ddl m Z m Z m Z mZmZmZmZdd Zed Zed Zgd Zd ZGdddZGdddZdS))abc)repeat)Number)ListN) ltwh2xywh ltwh2xyxyresample_segments xywh2ltwh xywh2xyxy xyxy2ltwh xyxy2xywhcsfdd}|S)zFrom PyTorch internals.cst|tjr|Stt|S)zDParse input to return n-tuple by repeating singleton values n times.) isinstancerIterabletupler)xnN/var/www/vscode/kcb/lib/python3.10/site-packages/ultralytics/utils/instance.pyparsesz_ntuple..parser)rrrrr_ntuple s r)xyxyxywhltwh)Bboxes Instancesc@sjeZdZdZddddZddZd d Zd d Zd dZddZ e dde dddfddZ dddZ dS)ra A class for handling bounding boxes. The class supports various bounding box formats like 'xyxy', 'xywh', and 'ltwh'. Bounding box data should be provided in numpy arrays. Attributes: bboxes (np.ndarray): The bounding boxes stored in a 2D numpy array with shape (N, 4). format (str): The format of the bounding boxes ('xyxy', 'xywh', or 'ltwh'). Note: This class does not handle normalization or denormalization of bounding boxes. rreturnNcCsj|tvsJd|dt|jdkr|dddfn|}|jdks$J|jddks-J||_||_dS)a Initialize the Bboxes class with bounding box data in a specified format. Args: bboxes (np.ndarray): Array of bounding boxes with shape (N, 4) or (4,). format (str): Format of the bounding boxes, one of 'xyxy', 'xywh', or 'ltwh'. Invalid bounding box format: , format must be one of rNrr)_formatsndimshapebboxesformat)selfr%r&rrr__init__1s  zBboxes.__init__cCs|tvsJd|dt|j|krdS|jdkr#|dkr tnt}n|jdkr1|dkr.tnt}n|dkr7tnt}||j|_||_dS)z Convert bounding box format from one type to another. Args: format (str): Target format for conversion, one of 'xyxy', 'xywh', or 'ltwh'. r r!Nrr) r"r&r r r r rrr%)r'r&funcrrrconvertAs     zBboxes.convertcCsv|jdkr)|jdddf|jdddf|jdddf|jdddfS|jdddf|jdddfS)zReturn box areas.rNrrr)r&r%r'rrrareasTs F"z Bboxes.areascCst|tr t|}t|ttfsJt|dksJ|jdddf|d9<|jdddf|d9<|jdddf|d9<|jdddf|d9<dS)z Multiply bounding box coordinates by scale factor(s). Args: scale (int | tuple | list): Scale factor(s) for four coordinates. If int, the same scale is applied to all coordinates. rNrrrr+rr to_4tuplerlistlenr%)r'scalerrrmull "z Bboxes.mulcCst|tr t|}t|ttfsJt|dksJ|jdddf|d7<|jdddf|d7<|jdddf|d7<|jdddf|d7<dS)z Add offset to bounding box coordinates. Args: offset (int | tuple | list): Offset(s) for four coordinates. If int, the same offset is applied to all coordinates. rNrrrr+r.)r'offsetrrradd}r4z Bboxes.addcC t|jS)zReturn the number of boxes.r1r%r,rrr__len__ zBboxes.__len__r boxes_listcCsjt|ttfs J|s|tdStdd|DsJt|dkr'|dS|tjdd|D|dS)a Concatenate a list of Bboxes objects into a single Bboxes object. Args: boxes_list (List[Bboxes]): A list of Bboxes objects to concatenate. axis (int, optional): The axis along which to concatenate the bounding boxes. Returns: (Bboxes): A new Bboxes object containing the concatenated bounding boxes. Note: The input should be a list or tuple of Bboxes objects. rcs|]}t|tVqdSN)rr).0boxrrr z%Bboxes.concatenate..rcSg|]}|jqSrr%r>brrr z&Bboxes.concatenate..axis)rr0rnpemptyallr1 concatenate)clsr;rIrrrrMs zBboxes.concatenatecCsLt|trt|j|ddS|j|}|jdks"Jd|dt|S)a Retrieve a specific bounding box or a set of bounding boxes using indexing. Args: index (int | slice | np.ndarray): The index, slice, or boolean array to select the desired bounding boxes. Returns: (Bboxes): A new Bboxes object containing the selected bounding boxes. Raises: AssertionError: If the indexed bounding boxes do not form a 2-dimensional matrix. Note: When using boolean indexing, make sure to provide a boolean array with the same length as the number of bounding boxes. rrzIndexing on Bboxes with z failed to return a matrix!)rintrr%reshaper#)r'indexrErrr __getitem__s  zBboxes.__getitem__)rrNr)rr)__name__ __module__ __qualname____doc__r(r*r-r3r6r9 classmethodrrMrSrrrrr"s rc@seZdZdZd)d*ddZdd Zed d Zd+d dZddZ ddZ ddZ d,ddZ ddZ ddZddZddZd-dd Zd!d"Zed.d$edddfd%d&Zed'd(ZdS)/ra Container for bounding boxes, segments, and keypoints of detected objects in an image. Attributes: _bboxes (Bboxes): Internal object for handling bounding box operations. keypoints (np.ndarray): Keypoints with shape (N, 17, 3) in format (x, y, visible). normalized (bool): Flag indicating whether the bounding box coordinates are normalized. segments (np.ndarray): Segments array with shape (N, M, 2) after resampling. Methods: convert_bbox: Convert bounding box format. scale: Scale coordinates by given factors. denormalize: Convert normalized coordinates to absolute coordinates. normalize: Convert absolute coordinates to normalized coordinates. add_padding: Add padding to coordinates. flipud: Flip coordinates vertically. fliplr: Flip coordinates horizontally. clip: Clip coordinates to stay within image boundaries. remove_zero_area_boxes: Remove boxes with zero area. update: Update instance variables. concatenate: Concatenate multiple Instances objects. Examples: >>> instances = Instances( ... bboxes=np.array([[10, 10, 30, 30], [20, 20, 40, 40]]), ... segments=[np.array([[5, 5], [10, 10]]), np.array([[15, 15], [20, 20]])], ... keypoints=np.array([[[5, 5, 1], [10, 10, 1]], [[15, 15, 1], [20, 20, 1]]]), ... ) NrTrcCs$t||d|_||_||_||_dS)a Initialize the object with bounding boxes, segments, and keypoints. Args: bboxes (np.ndarray): Bounding boxes, shape (N, 4). segments (List | np.ndarray, optional): Segmentation masks. keypoints (np.ndarray, optional): Keypoints, shape (N, 17, 3) in format (x, y, visible). bbox_format (str, optional): Format of bboxes. normalized (bool, optional): Whether the coordinates are normalized. )r%r&N)r_bboxes keypoints normalizedsegments)r'r%r^r\ bbox_formatr]rrrr(s  zInstances.__init__cCs|jj|ddS)z Convert bounding box format. Args: format (str): Target format for conversion, one of 'xyxy', 'xywh', or 'ltwh'. r&N)r[r*)r'r&rrr convert_bboxszInstances.convert_bboxcCs |jS)z%Calculate the area of bounding boxes.)r[r-r,rrr bbox_areass zInstances.bbox_areasFcCsx|jj||||fd|rdS|jd|9<|jd|9<|jdur:|jd|9<|jd|9<dSdS)z Scale coordinates by given factors. Args: scale_w (float): Scale factor for width. scale_h (float): Scale factor for height. bbox_only (bool, optional): Whether to scale only bounding boxes. r2N.r.r)r[r3r^r\)r'scale_wscale_h bbox_onlyrrrr2s  zInstances.scalecCs||jsdS|jj||||fd|jd|9<|jd|9<|jdur9|jd|9<|jd|9<d|_dS)z Convert normalized coordinates to absolute coordinates. Args: w (int): Image width. h (int): Image height. NrcrdreFr]r[r3r^r\r'whrrr denormalizes  zInstances.denormalizecCs|jrdS|jjd|d|d|d|fd|jd|<|jd|<|jdurA|jd|<|jd|<d|_dS)z Convert absolute coordinates to normalized coordinates. Args: w (int): Image width. h (int): Image height. NrrcrdreTrirjrrr normalize$s&  zInstances.normalizecCs~|jrJd|jj||||fd|jd|7<|jd|7<|jdur=|jd|7<|jd|7<dSdS)z Add padding to coordinates. Args: padw (int): Padding width. padh (int): Padding height. z1you should add padding with absolute coordinates.)r5rdreN)r]r[r6r^r\)r'padwpadhrrr add_padding6s zInstances.add_paddingcCsXt|jr |j|n|j}|jdur|j|nd}|j|}|jj}t|||||jdS)a Retrieve a specific instance or a set of instances using indexing. Args: index (int | slice | np.ndarray): The index, slice, or boolean array to select the desired instances. Returns: (Instances): A new Instances object containing the selected boxes, segments, and keypoints if present. Note: When using boolean indexing, make sure to provide a boolean array with the same length as the number of instances. N)r%r^r\r_r])r1r^r\r%r[r&rr])r'rRr^r\r%r_rrrrSFs zInstances.__getitem__cC|jjdkr3|jdddf}|jdddf}|||jdddf<|||jdddf<n||jdddf|jdddf<||jd|jd<|jdur`||jd|jd<dSdS)z` Flip coordinates vertically. Args: h (int): Image height. rNrr+rer[r&r%copyr^r\)r'rly1y2rrrflipud` $ zInstances.flipudcCrr)za Flip coordinates horizontally. Args: w (int): Image width. rNrrrdrs)r'rkx1x2rrrfliplrrrxzInstances.fliplrcCs |jj}|jdd|jddddgfd||jddddgf<|jddddgfd||jddddgf<|dkrD|j|d|jdd||jd<|jd d||jd <|jdurd |jd |jddk|jd|kB|jd dkB|jd |kB<dSdS) z Clip coordinates to stay within image boundaries. Args: w (int): Image width. h (int): Image height. rr`Nrrrr+rdreg).r)r[r&rar%clipr^r\)r'rkrl ori_formatrrrr|s( 00      zInstances.clipcCsN|jdk}t|s%|j||_t|jr|j||_|jdur%|j||_|S)z Remove zero-area boxes, i.e. after clipping some boxes may have zero width or height. Returns: (np.ndarray): Boolean array indicating which boxes were kept. rN)rbrLr[r1r^r\)r'goodrrrremove_zero_area_boxess      z Instances.remove_zero_area_boxescCs6t||jjd|_|dur||_|dur||_dSdS)z Update instance variables. Args: bboxes (np.ndarray): New bounding boxes. segments (np.ndarray, optional): New segments. keypoints (np.ndarray, optional): New keypoints. r`N)rr[r&r^r\)r'r%r^r\rrrupdates   zInstances.updatecCr7)z'Return the length of the instance list.r8r,rrrr9r:zInstances.__len__rinstances_listc st|ttfs J|s|tdStdd|DsJt|dkr'|dS|djdu}|djj }|dj }tj dd|D|d}d d|D}tt |dkrgt |tj fd d|D|d}n tj d d|D|d}|rtj d d|D|dnd} |||| ||S) a Concatenate a list of Instances objects into a single Instances object. Args: instances_list (List[Instances]): A list of Instances objects to concatenate. axis (int, optional): The axis along which the arrays will be concatenated. Returns: (Instances): A new Instances object containing the concatenated bounding boxes, segments, and keypoints if present. Note: The `Instances` objects in the list should have the same properties, such as the format of the bounding boxes, whether keypoints are present, and if the coordinates are normalized. rcsr<r=)rr)r>instancerrrr@rAz(Instances.concatenate..rNcSrBrrC)r>insrrrrFrGz)Instances.concatenate..rHcSsg|]}|jjdqS)r)r^r$rDrrrrFscs<g|]}t|jrtt|jn tjddftjdqS)rr)dtype)r1r^r r0rJzerosfloat32rDmax_lenrrrFs cSrBr)r^rDrrrrFrGcSrBr)r\rDrrrrFrG)rr0rrJrKrLr1r\r[r&r]rM frozensetmax) rNrrI use_keypointr_r] cat_boxesseg_len cat_segments cat_keypointsrrrrMs,     zInstances.concatenatecCs|jjS)zReturn bounding boxes.)r[r%r,rrrr%szInstances.bboxes)NNrTrT)F)rr)NNrU)rVrWrXrYr(rapropertyrbr2rmrnrqrSrwr{r|rrr9rZrrMr%rrrrrs*     /r) collectionsr itertoolsrnumbersrtypingrnumpyrJopsrrr r r r r r to_2tupler/r"__all__rrrrrrs    $ "