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Lr#chtjd}|d|d<|d|d<d|z}tjd}||z |d<||z |d<||d |z dzz|d<||d |z dzz|d <|rtj|}tj||dd }|j S) aGenerate and affine transformation matrix. Given a set of points, a center, a scale and a targer resolution, the function generates and affine transformation matrix. If invert is ``True`` it will produce the inverse transformation. Arguments: point {torch.tensor} -- the input 2D point center {torch.tensor or numpy.array} -- the center around which to perform the transformations scale {float} -- the scale of the face/object resolution {float} -- the output resolution Keyword Arguments: invert {bool} -- define wherever the function should produce the direct or the inverse transformation matrix (default: {False}) r%rrgi@)rr)rrr)rr )rr r )torchoneseyeinversematmulr)) r-centerscale resolutioninvert_ptht new_points r! transformrD8s" **Q-C 1XCF 1XCF  A ! A1nAdG1nAdGVAYJNS01AdGVAYJNS01AdG MM! a%q+I ==?r#cb tddg|||d}t||g|||d}|jdkDrmtj|d|dz |d|dz |jdgtj }tj |tj}n^tj|d|dz |d|dz gtj}tj |tj}|jd}|jd} tjtd|d dzt|d| |dz gtj } tjtd|d dzt|d||dz gtj } tjtd|ddzt|d| gtj } tjtd|ddzt|d|gtj } || ddz | d| ddz | dddf|| ddz | d| ddz | df<tj|t|t|ftj}|S)aCenter crops an image or set of heatmaps Arguments: image {numpy.array} -- an rgb image center {numpy.array} -- the center of the object, usually the same as of the bounding box scale {float} -- scale of the face Keyword Arguments: resolution {float} -- the size of the output cropped image (default: {256.0}) Returns: [type] -- [description] rTr rrN)dsize interpolation)rDndimr arrayr(int32zerosuint8r)r*r+cv2resize INTER_LINEAR)r,r<r=r>r.r/newDimnewImghtwdnewXnewYoldXoldYs r!croprX\skU Aq665*d ;B J +VUJ MB zzA~2a52a5="Q%"Q%- ;;q>+24((<&12a52a5="Q%"Q%-8G&1 QB QB 88 QA SA^be34BHH FD 88 QA SA^be34BHH FD 88SBqEAI&BqE27rxx HD 88SBqEAI&BqE27rxx HDT!Wq[a($q'A+d1g*=q@A 47Q;tAw Q! DG 3 3 ZZs:J&H&)&6&68F Mr#c tjjjdjdjdjdzd\}}|dz }|j|jd|jddj dddj }|dj fd|djdjjdjjdt|jdD]}t|jdD]}||d d f}t|||dfdz t|||dfdz } } | dkDs;| d ksA| dkDsG| d ksMtj|| | dzf|| | dz fz || dz| f|| dz | fz g} |||fj| jjd |jd tj|j} |h|ftjdD]I}tjdD]*}t!|||f||jdd | ||f<,K|| fS)aObtain (x,y) coordinates given a set of N heatmaps. If the center and the scale is provided the function will return the points also in the original coordinate frame. Arguments: hm {torch.tensor} -- the predicted heatmaps, of shape [B, N, W, H] Keyword Arguments: center {torch.tensor} -- the center of the bounding box (default: {None}) scale {float} -- face scale (default: {None}) rrr r%.rc8|dz jdzdzSNrr%rxhms r!z"get_preds_fromhm..AERWWQZ#7!#;r#.rN??Tr7r*viewrrepeatfloatapply_add_div_floor_r r) FloatTensorsign_mul_rKrD) r`r<r=r*idxpredsrr hm_pXpYdiff preds_origs ` r!get_preds_fromhmrzsyyy  BGGAJ RWWQZ(?@!EHC1HC HHSXXa[#((1+q 1 8 8Aq A G G IE &M;< &Mr +22499!< 5::a= !uzz!}%AQ1W+Cq!Qw(1,c%1a..AA.EBAv"r'b1fb((R!V_s2rAv:6a_s262:689ad   !2!23!78&" JJsOUZZ\*J e/rwwqz"A2771:&#,!Q$K D$B 1a4 '# * r#c tjjjdjdjdjdzd\}}|dz }|j|jd|jddj dddj }|dj fd|djdjjdjjdt|jdD]}t|jdD]}||d d f}t|||dfdz t|||dfdz } } | dkDs;| d ksA| dkDsG| d ksMtj|| | dzf|| | dz fz || dz| f|| dz | fz g} |||fj| jjd |jd tj|j} |n|ltjdD]O}tjdD]0}t!|||f||||jdd | ||f<2Q|| fS)aObtain (x,y) coordinates given a set of N heatmaps. If the centers and the scales is provided the function will return the points also in the original coordinate frame. Arguments: hm {torch.tensor} -- the predicted heatmaps, of shape [B, N, W, H] Keyword Arguments: centers {torch.tensor} -- the centers of the bounding box (default: {None}) scales {float} -- face scales (default: {None}) rrr r%rZc8|dz jdzdzSr\r]r^s r!raz(get_preds_fromhm_batch..rbr#rcrdNrerfrgTrh) r`centersscalesr*rsrtrr rurvrwrxrys ` r!get_preds_fromhm_batchrsyy  BGGAJ RWWQZ(?@!EHC1HC HHSXXa[#((1+q 1 8 8Aq A G G IE &M;< &Mr +22499!< 5::a= !uzz!}%AQ1W+Cq!Qw(1,c%1a..AA.EBAv"r'b1fb((R!V_s2rAv:6a_s262:689ad   !2!23!78&" JJsOUZZ\*Jv1rwwqz"A2771:&#,!Q$KVAY D$J 1a4 '# * r#c^|gd}|jdk(r ||df}|S|dd|df}|S)a&Shuffle the points left-right according to the axis of symmetry of the object. Arguments: parts {torch.tensor} -- a 3D or 4D object containing the heatmaps. Keyword Arguments: pairs {list of integers} -- [order of the flipped points] (default: {None}) N)D r&r%r rr#"! -,+*/.'&%$)(6543210;:987@re>=<CBAr%.) ndimension)partspairss r! shuffle_lrrsO })  QeSj! Lam$ Lr#ctj|stj|}|r-t|j |j dz }|S|j |j dz }|S)aFlip an image or a set of heatmaps left-right Arguments: tensor {numpy.array or torch.tensor} -- [the input image or heatmaps] Keyword Arguments: is_label {bool} -- [denote wherever the input is an image or a set of heatmaps ] (default: {False}) r)r7 is_tensor from_numpyrflipr)tensoris_labels r!rrsp ??6 "!!&)F#(():):)rs[%  AEAD4&!H%P&P&P2,6r#