U ±PÓhç”ã@s ddlmZddlZddlZddlZddlZddlmZmZm Z m Z ddl Z ddl Z ddlmZddlmZddlmZddlmZmZmZddlmZmZed d eƒ\ZZe e¡Zed d d \Z ZGdd„deƒZ!Gdd„deƒZ"Gdd„deƒZ#Gdd„deƒZ$Gdd„deƒZ%Gdd„deeƒZ&Gdd„deƒZ'Gdd„deeƒZ(Gdd„deƒZ)Gd d!„d!eƒZ*Gd"d#„d#eƒZ+Gd$d%„d%eeƒZ,Gd&d'„d'eƒZ-dS)(é)Ú annotationsN)ÚHashableÚMappingÚSequenceÚSized)ÚKeysCollection)Ú MetaTensor)ÚGaussianFilter)Ú MapTransformÚ RandomizableÚ Transform)Ú min_versionÚoptional_importzskimage.measurez0.14.2zscipy.ndimage.morphologyÚdistance_transform_cdt)ÚnamecsDeZdZdddddd d œ‡fd d „ Zd d„Zdddœdd„Z‡ZS)ÚDiscardAddGuidancedéçð?NFrÚintÚfloatz Sized | NoneÚbool)ÚkeysÚnumber_intensity_chÚ probabilityÚ label_namesÚallow_missing_keyscs(tƒ ||¡||_||_|p g|_dS)aE Discard positive and negative points according to discard probability Args: keys: The ``keys`` parameter will be used to get and set the actual data item to transform number_intensity_ch: number of intensity channels probability: probability of discarding clicks N)ÚsuperÚ__init__rÚdiscard_probabilityr)Úselfrrrrr©Ú __class__©úS/home/dell461/cl/sdc2/HISourceFinder-master-l/src/monai/apps/deepedit/transforms.pyr&szDiscardAddGuidanced.__init__cCsž|jdks*tjjddg|jd|jgdrštjt|jƒ|jd|jd|jdftjd }|jd |j t|jƒkrˆ|||j d…d f<ntj ||gd d }|S) NrTFr©Úpéýÿÿÿéþÿÿÿéÿÿÿÿ©Údtyper.©Úaxis) rÚnpÚrandomÚchoiceÚzerosÚlenrÚshapeÚfloat32rÚ concatenate)rÚimageÚsignalr"r"r#Ú_apply<sÿ"ÿzDiscardAddGuidanced._applyúMapping[Hashable, np.ndarray]údict[Hashable, np.ndarray]©ÚdataÚreturncCs^t|ƒ}| |¡D]F}|dkrP| ||¡}t||tƒrF|||_qX|||<qtdƒq|S)Nr5z(This transform only applies to the image)ÚdictÚ key_iteratorr7Ú isinstancerÚarrayÚprint)rr;ÚdÚkeyÚ tmp_imager"r"r#Ú__call__Is   zDiscardAddGuidanced.__call__)rrNF)Ú__name__Ú __module__Ú __qualname__rr7rEÚ __classcell__r"r"r r#r$sú rcs8eZdZdddddœ‡fdd„ Zd d d œd d „Z‡ZS)ÚNormalizeLabelsInDatasetdNFrzdict[str, int] | Noner©rrrcstƒ ||¡|pi|_dS)zë Normalize label values according to label names dictionary Args: keys: The ``keys`` parameter will be used to get and set the actual data item to transform label_names: all label names N)rrr©rrrrr r"r#rYs z"NormalizeLabelsInDatasetd.__init__r8r9r:c Csªt|ƒ}| |¡D]’}i}t ||j¡}t|j ¡ddD]<\}\}}|dkrh|||<|||||k<|dkrr-r0r2Ú enumeraterÚitemsr?rr@) rr;rBrCZnew_label_namesÚlabelÚidxÚ key_labelÚ val_labelr"r"r#rEgs   z"NormalizeLabelsInDatasetd.__call__)NF©rFrGrHrrErIr"r"r r#rJWsÿrJcs8eZdZdddddœ‡fdd„ Zd d d œd d „Z‡ZS)ÚSingleLabelSelectiondNFrzSequence[str] | NonerrKcs@tƒ ||¡|pg|_ddddddddd d d d d ddœ|_dS)zâ Selects one label at a time to train the DeepEdit Args: keys: The ``keys`` parameter will be used to get and set the actual data item to transform label_names: all label names réééééééé é é é é é)Zspleenz right kidneyz left kidneyZ gallbladderZ esophagusZliverZstomachZaortazinferior vena cavaZ portal_veinZ splenic_veinZpancreaszright adrenal glandzleft adrenal glandN)rrrÚall_label_valuesrLr r"r#rs"  òzSingleLabelSelectiond.__init__r8r9r:cCs t|ƒ}| |¡D]ˆ}|dkrtj |j¡}||d<d|||||j|k<|j |¡d}|||||dk<td|›d||  ¡›ƒqt   d¡q|S) NrQZ current_labelgrrz Using label z with number: z(This transform only applies to the label) r=r>r-r.r/rrdÚindexrAÚmaxÚwarningsÚwarn)rr;rBrCZt_labelZ max_label_valr"r"r#rEs zSingleLabelSelectiond.__call__)NFrUr"r"r r#rV}sÿrVcsHeZdZdZdddddd d œ‡fd d „ Zd d„Zdddœdd„Z‡ZS)ÚAddGuidanceSignalDeepEditdaB Add Guidance signal for input image. Multilabel DeepEdit Based on the "guidance" points, apply Gaussian to them and add them as new channel for input image. Args: guidance: key to store guidance. sigma: standard deviation for Gaussian kernel. number_intensity_ch: channel index. ÚguidancerXrFrÚstrrr)rrjÚsigmarrcs$tƒ ||¡||_||_||_dS©N)rrrjrlr)rrrjrlrrr r"r#rºsz#AddGuidanceSignalDeepEditd.__init__c Cs¦t|jƒdkrdnd}t|tjƒr*| ¡n|}t|tƒrBt |¡n|}t|ƒrF|dkr„tj d|jd|jd|jdftj d}n"tj d|jd|jdftj d}|j}|D]ì}t  t  |¡dk¡rÊq°|dkrJt dtt|dƒ|ddƒƒ}t dtt|dƒ|ddƒƒ}t dtt|dƒ|ddƒƒ} d |dd…||| f<q°t dtt|dƒ|ddƒƒ}t dtt|dƒ|ddƒƒ}d |dd…||f<q°t  |d¡dkrBt |d¡} tt| jƒ|jd } | |  d¡ d¡ƒ} |  d¡ d¡} |  ¡ ¡ ¡|d<|dt |d¡t  |d¡t |d¡|d<|S|dkr|tj d|jd|jd|jdftj d}n"tj d|jd|jdftj d}|SdS) NrXrWrr&r'r(r)rr)rl)r1r2r?r-ÚndarrayÚtolistrkÚjsonÚloadsr0r3ÚanyÚasarrayrfÚminrÚtorchÚtensorr rlÚ unsqueezeÚsqueezeÚdetachÚcpuÚnumpy) rr5rjÚ dimensionsr6ÚsshapeÚpointÚp1Úp2Úp3Z signal_tensorZ pt_gaussianr"r"r#Ú _get_signalÇs> ,"      6 ,"z&AddGuidanceSignalDeepEditd._get_signalr8r9r:c Cs®t|ƒ}| |¡D]–}|dkr ||}|dd|j…df}||j}| ¡D]H}| |||¡}tj||gdd}t||t ƒrŽ|||_ qN|||<qN|St dƒq|S)Nr5r.r+z(This transform only applies to image key) r=r>rrjrr‚r-r4r?rr@rA) rr;rBrCr5rDrjrSr6r"r"r#rEôs     z#AddGuidanceSignalDeepEditd.__call__)rjrXrF)rFrGrHÚ__doc__rr‚rErIr"r"r r#ri®sú -ricsDeZdZdZdddddœ‡fdd „ Zd d „Zd d dœdd„Z‡ZS)ÚFindAllValidSlicesDeepEditdzà Find/List all valid slices in the labels. Label is assumed to be a 4D Volume with shape CHWD, where C=1. Args: sids: key to store slices indices having valid label map. ÚsidsFrrr©rr…rcstƒ ||¡||_dSrm©rrr…©rrr…rr r"r#rsz$FindAllValidSlicesDeepEditd.__init__cCs`i}|d ¡D]J}g}t|jdƒD]*}|d||dd|fkr&| |¡q&|||<q|S)Nrr(r.©rÚranger2Úappend©rrQrBr…rSZl_idsÚsidr"r"r#r7s  z"FindAllValidSlicesDeepEditd._applyr8r9r:cCs’t|ƒ}| |¡D]z}|dkr„||}|jddkrr2Ú ValueErrorr1r7rr…rA©rr;rBrCrQr…r"r"r#rE s   z$FindAllValidSlicesDeepEditd.__call__)r…F©rFrGrHrƒrr7rErIr"r"r r#r„ s r„csReZdZdZdddddd d d œ‡fd d „ Zdd„Zdd„Zdddœdd„Z‡ZS)ÚAddInitialSeedPointDeepEditdai Add random guidance as initial seed point for a given label. Note that the label is of size (C, D, H, W) or (C, H, W) The guidance is of size (2, N, # of dims) where N is number of guidance added. # of dims = 4 when C, D, H, W; # of dims = 3 when (C, H, W) Args: guidance: key to store guidance. sids: key that represents lists of valid slice indices for the given label. sid: key that represents the slice to add initial seed point. If not present, random sid will be chosen. connected_regions: maximum connected regions to use for adding initial points. rjr…rrZFrrkrr©rrjr…rÚconnected_regionsrcs2tƒ ||¡||_||_tƒ|_||_||_dSrm©rrÚsids_keyÚsid_keyr=rrjr–©rrrjr…rr–rr r"r#rDs z%AddInitialSeedPointDeepEditd.__init__c CsÌt|jƒdkrdnd}dg|d|_|}|dk rT|dkrTd}|dd|ftj}|dk tj¡}|dkr€tj| t ¡ddn|}t  |¡dkr t d |›ƒ‚g}t d|dkr´dn|j dƒD]þ}|dkrø||k tj¡}t |¡dkrø| |j¡qÀt|ƒ ¡} t | ¡d } t | ¡dk¡d} |jj| d| | t | | ¡d } | | } t t | |j¡¡ ¡ ¡d}| d|d<|dks”|dkr | |¡qÀ| |d|d |d|g¡qÀt |g¡S) NrXrWr(rr.çà?©rNzSLICES NOT FOUND FOR LABEL: r©Úsizer%r')r1r2Údefault_guidancer-ÚnewaxisÚastyper3ÚmeasurerQrrfÚAssertionErrorrŠr–Úsumr‹rÚflattenÚexpÚwhereÚRr/rsÚ unravel_indexÚ transposero)rrQrrSr|ÚdimsÚ blobs_labelsZ pos_guidanceÚridxÚdistancerrRÚseedÚdstÚgr"r"r#r7Ts8    $    z#AddInitialSeedPointDeepEditd._applycCsœ| |j¡dk r"| |j¡ |¡nd}| |j¡dk rH| |j¡ |¡nd}|dk rz|rz|dksh||krŽ|jj|dd}nt d|›¡d}||j|<dS©NF)ÚreplacezNot slice IDs for label: ©Úgetr˜r™r¨r/ÚloggerÚinfor©rrBrSr…rr"r"r#Ú _randomizes&& z'AddInitialSeedPointDeepEditd._randomizer8r9r:c CsÚt|ƒ}| |¡D]Â}|dkrÌi}|d ¡D]Š}| ||¡t ||¡}|dkrnd||t|d|ƒk<n d||t|d|ƒk<d|}t |  ||j   |¡|¡  t ¡ ¡¡||<q.|||j<|Stdƒq|S©NrQr…rNrrrr©r=r>rr¹r-ÚcopyrrpÚdumpsr7rrµr¡rrorjrA©rr;rBrCZlabel_guidancesrSÚ tmp_labelr"r"r#rEŒs$ ÿ   z%AddInitialSeedPointDeepEditd.__call__)rjr…rrZF© rFrGrHrƒrr7r¹rErIr"r"r r#r”4sù- r”csReZdZdZddddddœ‡fd d „ Zed d „ƒZd d„Zdddœdd„Z‡Z S)ÚFindDiscrepancyRegionsDeepEditdzê Find discrepancy between prediction and actual during click interactions during training. Args: pred: key to prediction source. discrepancy: key to store discrepancies found between label and prediction. ÚpredÚ discrepancyFrrkr)rrÂrÃrcstƒ ||¡||_||_dSrm)rrrÂrÃ)rrrÂrÃrr r"r#r¯sz(FindDiscrepancyRegionsDeepEditd.__init__cCs0||}|dk tj¡}|dk tj¡}||gS)Nr)r¡r-r3)rQrÂÚ disparityZ pos_disparityZ neg_disparityr"r"r#rĺsz)FindDiscrepancyRegionsDeepEditd.disparitycCs | ||¡Srm)rÄ)rrQrÂr"r"r#r7Ãsz&FindDiscrepancyRegionsDeepEditd._applyr8r9r:c Cs:t|ƒ}| |¡D] }|dkr,i}t|d ¡ƒD]â\}\}}|dkr¢t ||¡}d|||k<|dk tj¡}t ||j¡} d| | |k<| dk tj¡} nft ||¡}d|||k<d|}|dk tj¡}t ||j¡} d| | |k<d| } | dk tj¡} |  || ¡||<q6|||j <|St dƒq|S)NrQrrNrr›rz*This transform only applies to 'label' key) r=r>rOrPr-r¼r¡r3rÂr7rÃrA) rr;rBrCZall_discrepanciesÚ_rSrTrQrÂr"r"r#rEÆs2       z(FindDiscrepancyRegionsDeepEditd.__call__)rÂrÃF) rFrGrHrƒrÚ staticmethodrÄr7rErIr"r"r r#rÁ¦s û  rÁcsZeZdZdZddddddd œ‡fd d „ Zdd d„Zdd„Zdd„Zdddœdd„Z‡Z S)ÚAddRandomGuidanceDeepEditdab Add random guidance based on discrepancies that were found between label and prediction. Args: guidance: key to guidance source, shape (2, N, # of dim) discrepancy: key to discrepancy map between label and prediction shape (2, C, H, W, D) or (2, C, H, W) probability: key to click/interaction probability, shape (1) rjrÃrFrrkr)rrjrÃrrcsBtƒ ||¡||_||_||_d|_d|_d|_d|_i|_ dSrm) rrÚ guidance_keyrÃrÚ_will_interactÚis_posÚis_otherrŸrj)rrrjrÃrrr r"r#rösz#AddRandomGuidanceDeepEditd.__init__NcCs,||j}|jjddg|d|gd|_dS)NTFrr$)rr¨r/rÉ)rr;rr"r"r#Ú randomizes z$AddRandomGuidanceDeepEditd.randomizecCs¦t|ƒ ¡}t | ¡¡d}t | ¡dk¡d}t |dk¡dkr¢|jj|d||t ||¡d}||}t t  ||j ¡¡  ¡  ¡d}|d|d<|SdS)Nrrrr) rr¥r-r¦r§r¤r¨r/rsr©r2rªro)rrÃr®rrRr¯r°r±r"r"r#Ú find_guidance s $  z(AddRandomGuidanceDeepEditd.find_guidancec Cs||d}i}t| ¡ƒD]†\}\}} |dkrjt |¡} d| | | k<| dk tj¡} t |d| ¡||<qt |¡} d| | | k<d| } t |d| ¡||<qt |¡dkrÄ| | |¡¡d|_ |  ¡D]ª}||dkrÌd|_ |dkr6t |¡} d| | ||k<| dk tj¡} |j | | |d| ¡¡qÌt |¡} d| | ||k<d| } |j | | |d| ¡¡qÌdS)NrrNr›rTé2) rOrPr-r¼r¡r3r¤r‹rÍrÊrrËrj) rrjrÃrÚlabelsZ pos_discrZother_discrepancy_areasrÅrSrTr¿r"r"r#Ú add_guidances6          z'AddRandomGuidanceDeepEditd.add_guidancer8r9r:c Cs”t|ƒ}||j}||j}| |¡|jr„|d ¡D]P}||}t|tjƒrZ|  ¡n|}t|t ƒrrt   |¡n|}dd„|Dƒ|j |<q:|d ¡D]&}| |j ||||d|d¡q˜t dd¡}d}g} t t|d ¡ƒ¡} | | krônb|  | ¡|t|j | ƒ}||krV|d ¡D]}|| kr&g|j |<q&t d|›¡q„t| ƒt|d ¡ƒkrÔt d|›¡q„qÔ|j ||j<|S) NrcSsg|]}d|kr|‘qS)r(r")Ú.0Újr"r"r#Ú Lsz7AddRandomGuidanceDeepEditd.__call__..rQrr_rzNumber of simulated clicks: )r=rÈrÃrÌrÉrr?r-rnrorkrprqrjrÐr.Úrandintr/Úlistr‹r1r¶r·) rr;rBrjrÃrSZtmp_guiZ num_clicksÚcounterZ keep_guidanceZ aux_labelr"r"r#rEAs>   $     z#AddRandomGuidanceDeepEditd.__call__)rjrÃrF)N) rFrGrHrƒrrÌrÍrÐrErIr"r"r r#rÇìs ú 'rÇc@s<eZdZdZdddddddœd d „Zed d „ƒZd d„ZdS)ÚAddGuidanceFromPointsDeepEditdaC Add guidance based on user clicks. ONLY WORKS FOR 3D We assume the input is loaded by LoadImaged and has the shape of (H, W, D) originally. Clicks always specify the coordinates in (H, W, D) Args: ref_image: key to reference image to fetch current and original image details. guidance: output key to store guidance. meta_keys: explicitly indicate the key of the metadata dictionary of `ref_image`. for example, for data with key `image`, the metadata by default is in `image_meta_dict`. the metadata is a dictionary object which contains: filename, original_shape, etc. if None, will try to construct meta_keys by `{ref_image}_{meta_key_postfix}`. meta_key_postfix: if meta_key is None, use `{ref_image}_{meta_key_postfix}` to fetch the metadata according to the key data, default is `meta_dict`, the metadata is a dictionary object. For example, to handle key `image`, read/write affine matrices from the metadata `image_meta_dict` dictionary's `affine` field. rjNÚ meta_dictrkz dict | Nonez str | None©Ú ref_imagerjrÚ meta_keysÚmeta_key_postfixcCs&||_||_|pi|_||_||_dSrmrÙ)rrÚrjrrÛrÜr"r"r#rƒs  z'AddGuidanceFromPointsDeepEditd.__init__cCs*t|ƒr"t ||¡ t¡ ¡}|SgSdSrm)r1r-Úmultiplyr¡rro)ÚclicksÚfactorrjr"r"r#r7‘sz%AddGuidanceFromPointsDeepEditd._applyc Csît|ƒ}|jp|j›d|j›}t||jtƒr>||jj}n ||krP||}nt|›dƒ‚d|krntdƒ‚|d}t ||jj ƒdd…}t   |¡|}i}|j  ¡D]4} | | g¡} t t   | ¡ t¡ƒ} | | |¡|| <qª|||j<|S)NrÅúI is not found. Please check whether it is the correct the image meta key.Ú spatial_shapez%Missing "spatial_shape" in meta_dict!r)r=rÛrÚrÜr?rÚmetar‘Ú RuntimeErrorrÕr2r-r@rrrµr¡rr7rj) rr;rBÚ meta_dict_keyrØÚoriginal_shapeÚ current_shaperßÚ all_guidancesrSrÞr"r"r#rE™s* ÿ  z'AddGuidanceFromPointsDeepEditd.__call__)rjNNrØ)rFrGrHrƒrrÆr7rEr"r"r"r#r×nsú r×c@s*eZdZdZddddœdd„Zdd„Zd S) Ú$ResizeGuidanceMultipleLabelDeepEditdzA Resize the guidance based on cropped vs resized image. rkÚNone)rjrÚr<cCs||_||_dSrm)rjrÚ)rrjrÚr"r"r#rÀsz-ResizeGuidanceMultipleLabelDeepEditd.__init__c CsÖt|ƒ}||jjdd…}d}t||jtƒr>||jj}n ||krP||}nt|›dƒ‚|d}t ||¡}i}||j   ¡D]B} t ||j | ƒrºt  ||j | |¡  t¡ ¡ng} | || <q„|||j <|S)NrÚimage_meta_dictràrá)r=rÚr2r?rrâr‘r-Údividerjrr1rÝr¡rro) rr;rBrærärØrårßrçrSrjr"r"r#rEÄs* ÿ ÿ"ý  z-ResizeGuidanceMultipleLabelDeepEditd.__call__N)rFrGrHrƒrrEr"r"r"r#rèºsrèc@s eZdZdZdddœdd„ZdS)ÚSplitPredsLabeldz; Split preds and labels for individual evaluation r8r9r:cCs¢t|ƒ}| |¡D]Š}|dkrŠt|d ¡ƒD]X\}\}}|dkr.|||ddfd|d|›<|d|ddfd|d|›<q.q|dkrt d ¡q|S) NrÂrrNr.Úpred_rQÚlabel_zThis is only for pred key)r=r>rOrPr¶r·)rr;rBrCrRrSrÅr"r"r#rEês"& zSplitPredsLabeld.__call__N)rFrGrHrƒrEr"r"r"r#rìäsrìcsReZdZdZdddddd d d œ‡fd d „ Zdd„Zdd„Zdddœdd„Z‡ZS)Ú!AddInitialSeedPointMissingLabelsdaf Add random guidance as initial seed point for a given label. Note that the label is of size (C, D, H, W) or (C, H, W) The guidance is of size (2, N, # of dims) where N is number of guidance added. # of dims = 4 when C, D, H, W; # of dims = 3 when (C, H, W) Args: guidance: key to store guidance. sids: key that represents lists of valid slice indices for the given label. sid: key that represents the slice to add initial seed point. If not present, random sid will be chosen. connected_regions: maximum connected regions to use for adding initial points. rjr…rrZFrrkrrr•cs2tƒ ||¡||_||_tƒ|_||_||_dSrmr—ršr r"r#rs z*AddInitialSeedPointMissingLabelsd.__init__c CsÌt|jƒdkrdnd}dg|d|_|}|dk rT|dkrTd}|dd|ftj}|dk tj¡}|dkr€tj| t ¡ddn|}g}t  |¡dkr¦|  |j¡nt d|dkr¶dn|j dƒD]þ}|dkrú||k tj¡}t |¡dkrú|  |j¡qÂt|ƒ ¡}t |¡d } t | ¡dk¡d} |jj| d| | t | | ¡d } || } t t | |j¡¡ ¡ ¡d} | d| d<|dks–|dkr¢|  | ¡qÂ|  | d| d | d|g¡qÂt |¡S) NrXrWr(rr.r›rœrrr')r1r2rŸr-r r¡r3r¢rQrrfr‹rŠr–r¤rr¥r¦r§r¨r/rsr©rªro)rrQrr|r«r¬Zlabel_guidancer­r®rrRr¯r°r±r"r"r#r7s8    $    z(AddInitialSeedPointMissingLabelsd._applycCsœ| |j¡dk r"| |j¡ |¡nd}| |j¡dk rH| |j¡ |¡nd}|dk rz|rz|dksh||krŽ|jj|dd}nt d|›¡d}||j|<dSr²r´r¸r"r"r#r¹Ds&& z,AddInitialSeedPointMissingLabelsd._randomizer8r9r:c CsØt|ƒ}| |¡D]À}|dkrÊi}|d ¡D]ˆ}| ||¡t ||¡}|dkrnd||t|d|ƒk<n d||t|d|ƒk<d|}t |  ||j   |¡¡  t ¡ ¡¡||<q.|||j<|Stdƒq|Srºr»r¾r"r"r#rEOs$ ÿ   z*AddInitialSeedPointMissingLabelsd.__call__)rjr…rrZFrÀr"r"r r#rï÷sù0 rïcsDeZdZdZdddddœ‡fdd „ Zd d „Zd d dœdd„Z‡ZS)Ú FindAllValidSlicesMissingLabelsdz Find/List all valid slices in the labels. Label is assumed to be a 4D Volume with shape CHWD, where C=1. Args: sids: key to store slices indices having valid label map. r…Frrrr†cstƒ ||¡||_dSrmr‡rˆr r"r#rqsz)FindAllValidSlicesMissingLabelsd.__init__cCsri}|d ¡D]\}g}t|jdƒD]*}|d||dd|fkr&| |¡q&|gkrddgd}|||<q|S)Nrr(r.r_r‰rŒr"r"r#r7us   z'FindAllValidSlicesMissingLabelsd._applyr8r9r:cCs’t|ƒ}| |¡D]z}|dkr„||}|jddkr s:     3&1[+rFL*r