This demonstrates a neural network that can capture 486 locations on each face in a costume.data:image/png;base64,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 demonstrates a neural network that can capture 486 locations on each face in a costume.

Reports the value of the 'key' in a table that is a list of pairs of keys and values.

Reports six locations on the face along with the coordinates of the smallest box that encloses the entire face.

stage costume percentagefalsehand

Converts costume coordinates to stage or percentage

x ystage costume percentage

Reports the 3D locations of 468 facial "landmarks" as well as the bounding box of the face. For full documentation including options click the following help: https://github.com/tensorflow/tfjs-models/tree/master/face-landmarks-detection/src/tfjs

stagestage costume percentagefalseIs a textual error messagekeypointlandmark

This is the workhorse behind the reporters for the body and hand poses and face landmarks.

MoveNet PoseNet BlazePose MediaPipeFaceDetector MediaPipeFaceMesh MediaPipeHands ARPortraitDepth

poses_and_landmarksmodel name

Computes brightness values between 33 and 100 depending upon how close the point is the "camera".

Reports a costume using the camera.

truecostume

Creates a costume from the video camera and passes it the 'process costume' blocks.

rotation1

Copied from https://snap.berkeley.edu/snapsource/snap.html#present:Username=jens&ProjectName=3D%20cube

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uWjpdANwoogLtxVNWnjhDw8xyI4WXuc1xolvN8RzS6iUb6eQ42hrmZKt83t/NMJc97Qnh2PFtANlGtDpVAxwgogDtmqLqnoXYBLw16WGHh59ki7263nlUKFKzlQFPjiswS7pis9vUXeK+B+e4qzpiK5TP78ywysIlXYufJ6pPKlYAEGhdQADdupSNbKBDfur2BcKILMthXsU0lzXE25Davj2vqNXEwXLfLrOYas4wXRju+kmdhDQ5MGa7IFLm9XplT/b3fy844/MYaLs8WOb3R+u3ubEQN06qw7y9whrE875X4eqNt0HESkMD/CyiANRs6WsC+mm39GscZw21ekavrdcbPcTKG17k1TjZL+Ge94xv53s9zEobvOiHvzZT5SSPnTOSY6KnwSpYdMw7PmCKPTqSs0c6N9huuzOQgE/Jgpsyiscr383zIGlZli1w0dIwFp5LnXx1YOfTQW/QQ3UCON1qHbWpV/pi9nQdb3WaVJ4FOFFAAd+Koqc0SmEQBuxtb+B7nGLjJK/G9ZqqyOdKB4ZcW7sqWOC06N/qDIZhBH4Y5Bj6l15WaEdWx3SygAO7m0Z2mfYuuwgCjTeGn6QRQtyXQIQIK4A4ZqOnUzP4CPwbS2SJHjafffp7/xfAmN2QTU+bZ8ZQxdE5/jjON4XGvxNkTKWe6nmshFV0ET/S3/unqp353t4ACuLvHtyN7Vy3w+oEQJ1vmj5PdgSDHJ63D57G8zSvxu5H1+Xk+4sBTmRIXj9aW+IGoFAc5ITdlyvRNdnuTLN/PcwKGt2A5xSuxvF5bovANCgTWcnO2xD71jtf3EphuAgrg6Tbi6u86AvEV2vakeZDKWFdpdmdctqVmbmBgJF9lAa8KezjGhvx6PH8wVBaQD1N82YGLMyUuafXwBDl2Bd5qQq7LLKG0vvKjla/8mfwFyx+zJY4ceWxQ4JW2xg5uyM3Re71r7xLkecIYHvaKzB+r/P6F7GBCrgKu9Ep8stX9VHkS6EQBBXAnjto0brNdwNZVw1bpVdzTzOIV0XlBKn5N6XdeiU+MJBx8nek1doCl3u3cO/S9n2dHYJmBy9wSxw4/z8/zRgN7Zmr82Czhb+MZlsEN6xcA93sl7h9PGes7J+hlnnU4MgW/qbcUZ/S0MgW2wCcwd/J0VG70b0GOHd2Q/rGeGo//QMlgzTIqY7Vl7ZPb8Kwp80ir+6nyJNCJAgrgThy1adzmaOF/DO9z4IOZEosbpYiezq0YdsmkeMYs4qEXXcn28prQ4RQMP/GK/KaRcv0c+1vDngzw46l8tSZaexnDx1Lw+nSRWxppa71jogfX/DyXOvBXt8QXho63OWYEhqXWsGjoN/n41nKeDxjLw26ZK9b5o6QQvzd9v1fkbWvLiALaY0NcnjdlVtdri76XwHQRUABPl5FWP9cRiJdJhN0zAecOXe21isjP81ELz2ZLXLj2SjrH163DXl7IARN9MCx+ynsfnNFuia/3arjAp6MNLUZ7tSi60q3kOTw0PJEtct36yokWUQle4GwM93pFzlkngBfycluhMvwPkiDPW0PD+cDp2SIXtMpZ5Uig0wUUwJ0+gmo/0XurQZZHsVzhlTi0EZIgzztCmO+t5lv1Voay2+OxASmzlFWNlN2f4wvG8PTwJ6f9PLs4IRulN6DUbHA2UmcjxwR5TrXwnAm50Tp8wVh+6Za5rJFzxzomXlY0xUeM4Sa3yP8MPy66vV6tsm3a8rfhvxlPpD6dK4FuElAAd9Noqi/rCARrrviONCFHuX0sreQ52loGxgoduwuzBzagtxbykFfmvrVXr3muBxZ6JWYN/VtQ4HBrOcKBMzIllnQSvV3AZhWH12JZ7vZxd9T2IMfu1rK1O8DNQ39oxLf7HQ42IR91y/x1tD7aAlsGliMs3J4tcYPNMYcBZtHD4xWHt1n4NJZTvVL8AJY+EpDAMAEFsKbDlAkEOQ6xhv0IOcfrY8VkV2xzbFUxbJJJc5+5lX6/wDesJciW+MxodQcLmBumONfA5V6J766vfYNPF++aqXKLWcrjk92XyS7fz/MfGPZzHY4b+o086OUVNsVL3ZBbh26b+/k4SPdwS2w6fKETP8+3gB2jIMZwXMryr532h8lkG6t8CYwUUABrTkyZQDXPa2uwwK3yK3MHD09ZxeupqD/PxRje6K3ilfVuRddrb5BnNwu/MoZL3CJn1Ds+qe+jPZID+DAmXmryymbaEa0TTYYeUmzgO7zfWG6J3p+u5tirZthAV7rNaOrY6S6gAJ7uM2Ca9D8Ox5BtTI2HnAyb1uA/LezgVdmdNB5FHjPxWzfj/0Sv4wQb8BLX8Iwps3J4SX6BC6xl12yJvaN/9/P8C4aPA+c2+tT1UHnRK1NBmlluiRVjLbcZ5HmXhYVuhS8HGQ5xLMHQRhHRnYHA4SgbUh7Pu8tRO2yBl1RC3htd9RrDH0dbqMTP82YLpzrwDbfEr8cvqzMl0J0CCuDuHNeO6lW0mIXtYcAt8pfJarhfiMPujcZyfQgH9gzw+Z4Md5rFPDlZdUY7NVVC5mRWcW/V5RXGYXa6zM1xgEUhmmF3N2SZKfP3teG6ZjOD3wN3eiVOHq1tfp7zgDe4lr2GB3204X20jaIhXtnrpRjmugE/8V0+7kC/W+JLrezr4KtLP3YMbwktT/UY3pcu8qe1fZnH5gNpXt7jsGIydm1qZV9UlgSSEFAAJ6GuOtcR8PPxkpNPeiXe0Qqawd13vonlXq/Mt1tR5njK8HN8HYc3u/BmU+QfjZQxGGqvS8Gzzf6GWsmzwMIuGcsfRl6BDz4p/hCWX7fKOf5DYs2DawtNjRkpw7LA0OM+zz+bWSSlERcdI4FuFFAAd+OoTpM+Rb9HDswkV6vyz+GrVw1uiXeCCXnY7eNXY3EMBuQpKdhn+JVbq/jifXALvK5mOcIY/uwW+Wmrym6mnGi5S1LMS1v+RJkHWrExQnQF72e43LFcPbRwR/SUeQinAh8b+Vuwn+dXGA5x+9nS3MVjzbRfx0qgWwUUwN06sl3Ur6DAuy1cYEM+nC3zw6GuRe/WWjjfWK70yvFTuHU/0bupFcu/mJB7h2+e4OfYCRP/+63RK0t1C1rPAdFvn8DBDvygBuc70W/Lhm/ZkLw1vNeJbh+XuGsidTRyrj+fl9ETP9X9iDXsjyFjapwQ/W6beZazzQqCRsoZfkz0ClNg6DXwdyfF5rbGC2nDUlOmOvy46HZ4aPgYhk8Zy4YOPDoZf+Q0234dL4F2ElAAt9NoqC2jCgzbMKE60T1+o92LrMMXMVyTLXLRUIWDmyIcx5pXkP4QLb5R3Yhd0iEr6z2x7ffyFmPIumV+GZVXydEbRg9AwVXR77uDr0MtzMB9WB6lzNMT7UcjUyW6PRzM5tUpS60H7ova0l/gGGPZxV3J582D+JUC86M/D9Z3uzv235keVlCt5smHhjMM/BTL1qHhE9Q4LNsXvyu99hMFdbWHbdLwqG8524E7W/0bdCMGOkYC7SygAG7n0VHbEhOIrq4x/DxeLWrYw0vRMpPAgXaA9w8tt+jn+RowxyvFV5cv+lQXskct5JMGLhr+NHBQ4HRrmeeu5D1RGLaqs/2F+PWgXnc1n4lereovcCtr3n9+0ZaA8a1hyHglDor/eChQCC1Hpgy/HFpn2i9wCjb+o+WdzT6x3ao+qRwJdKOAArgbR1V9alhg8N3k6P3VF+0FPFoh8eIUDtu4FW5d39KU0QNRNcO5xnLpWIt6VHvZO3TYIlPiV628Io52acKyk/sClw5/GCpaiATLhl6J6Ep/1E+0GIlNsb+xXOeWuXO0g6LlJ6uwYdqJn+Be59Zzw/A6UAISQAGsSdC1AvEWeDN5WWaAp8faSs/Pc1b0m6hX4q0TgYj2u/UM1aFVpOyr2aBaZW7a8M/hrxmNEerzwhTXGMvFje6VG+3dG8xgM3c1D5tlvDBU7uD2g5cauMQtxVfmaz9+ngONwYvWbI43dHgVW1Glv9kFSAYfXnujG7B/N6wCNpFx17kSmIiAAngiejq3rQXiTeAtv7GWK7IlTmu0sYO/nV5soDTyd8v+HMcZh4xX5NwR4XYH8LBX4sD11eMX+AWWx70SHxo6LtpdiFVsisNqs4jnGmnn4G3mj2M52SvH7w3HH7sH2UqVnTKGlZWQva3hMMfwpUwx3iZw7Sf6jdbvidew/kO2GC+oEX+CAkcBVbfIL4b+zc/zEWAnt8S/j/UEdX+eRcAW2RLbN9J+HSMBCUQbcOsjAQmsIzC4efyBxvJopo/bhn8Z7SgUWtxsmc81whYFHWnCoQU//AIHpGB1usiNjZzfX+DLBo7A8CZvMfesN9yj9ZgNb3Cjp7kX82R0O5kUczM+N1FlNXPIsJin1rfi1+AdgcAr8alhofy2eKOGEt8b69zojxZm4Ux0q8VGTHSMBLpFQAHcLSPZAf2IbptWZrJVxuEfjV7ptbpb0XKRbEttqrYE9Asst/BUtsge4+lL9NqUX2G2l+Lher+3Rlf8Kcuc9EzuGtm/wTWvD/QC5uq28XhGQudIoPUCCuDWm6rEMQQG3+eNrqxO8Ypc3SooO4+ZPEet3pPEfp4dgWUGLnNLHNuq+qNyot98gwE2c/t5bPhvsqPVMXiL+wwLd2ZLXNjKdgwvy89zvDW8JFvk9JF1xFes0S7Hz/JkPbex2he9XuU79Bn4rVfk/bHD4HvCONzrlbh/svqmciXQDQIK4G4YxWneBz8fP4S02Cuxb1IU8R8Xls8b+Hi9jQdsjhmB4XgM9w1/rSf6XRc4vsdwcnoxt463L0GBV1rL2dbwsBOywi3zxZFl+TlOtg6fAP4tW+S68dQVP8hVYHOq+OZ2nonKqORZOPiecMFC0StywHjK1jkSmA4CCuDpMMpt3Ec7nw2pYcydPJ1kM/2FvBzLfxj4XfSU8Ghtid7bDUN6Gv39t9n+2AVsXYWt0xnumcgteptjTmAoMMDfhi/R2Uh74j2Re3gPIb8fuVOSn+NE67Bdtsin65UVrT3NDAYmc7OLem3Q9xJodwEFcLuPUJe3z8/Th2GmV2SXJLsa306Fg1IOd2SKFEdrS3+eYzGkskUuaKatfp4S8NjQYhfNnNuqY/0C52DZ13XYZ32hGC1fadK83YEbhxbiGGpDtLykNWzjFvlKM+2KVh8jxVlYfuuVOL+Zc3WsBLpZQAHczaPbJX3z83wXw2vdVexd7/fVduxydHVtoZpdzAND7YtfPXqIFCuojHcf4igsbZpjoy0WvRLXjtb3aGMKnsVhDltUDBtkZvHXqXoAbag9QZ4LLexpLO8ca3GPdhw3tUkCky2gAJ5sYZU/YYHo4SnHsEG6yJ2tXDFqwg0bUUD02yshNbfMX+uVPfi6z4mOZc/hm0KMGqK7MLs6i7cZuG9oP+HouOipZ8dyuFPjz+k+bor+rdJLzqbYNWO4OrrS9QtciWV/12Gb4Ve+dnc2GnCZ25Pib0OLh9Rr83i/j25rmyj8R7zSNd7ydJ4EukVAAdwtI6l+rCMQ3XKNrrq8Vbxhqq6a432NDc97RQ5u5XDYeWzuu3zNWG7xSvxgfWVHD4OFcIAJ+ZxX5r6xjq0W2HPA8rUU/CBT4uJWtDfIcYh1OMvCGcM3umhF2SpDAt0ooADuxlFVn4huzzqGOeklLGnnq+ZuGqrodTDfYTPP5amJPETWTSbqiwTWJ6AA1vyQQAMC0S3bissHsfzFLXNFA6esPWTw/eOPGsMfx3rCeuhgP8dBOHzAWr6ZLXFDM/WMPLY/z0+MYZVX5IPRd36e84D7vRJfX1+5a5eenMVHp/r34on0V+dKoNMEFMCdNmJqb8sE/AIX2JAnsmVOrVdotIqXP4OPOYalw9dJrnde9H30hHVgeHvKcvvw33BHO7d/Ptsbh93cGkvq7UNcr24/z5ujdZ2j/Y3jAM7xAWN5zO2LtyAc8xMUGFp68ryx7h74eb5vDTmvh9eZW+mv1xZ9LwEJvFhAAaxZMW0FggKH2xqrvD5+O20RxtnxaL9kp8bs9JJ4JaxwnMXoNAlMawEF8LQefnW+lQK4gxzkAAAbzElEQVR+jp2MQz6ssih7Ow/WKzvIsWu0KWDG4c/jfRI5vjXuEW0ccW+mxOLR6ow2gDCwiVvk0uHfBwUOs7CVV+Scem3V9xKQQOsFFMCtN1WJ01TAz/MvFo7rMZyXLvKnegx+noMtHJmynJUpx9v5rfcTX7Fb9nKrfGXo9rTNsZ3vcCZw3dCTx9GKXYPBGv/221/gjGjP42yRdw+vIP6t17C9V4y3G9RHAhKYYgEF8BSDT/fqbIEt6ceau3hsuls02//+PPsY2M21/MyUWTnW+UEvh4Yp5mSL/LjZOiZyfPT7tZNmZqbI3botPRFJnTtdBBTA02Wk26Sffp6lFp7Nlti7TZrUds2wr2KbSprX2AGWNruW88jO9Peyb8rwkvSz/MysIJjMzgYFLrJQcHso6MGsyZRW2d0ioADulpFUPyZVYKJX7n6Bf7VwqoEzh++ANFqjK728JnQ4BcNP6h1br9PRbWZrmO+t4kP+TN7V6G5L0atTxrCHrbHI62NFvXrG+j5ahjMVslnPSsrj3fZwvHXrPAm0u4ACuN1HqMvbV8nx6tDwRWO5yC1zWbt2N9o0whqCbJE9xtPGaJ/cqmGntOU+s4QnxlPGRM9pZrelai97D6Q4gRoXZvu4frx19+f4MoY3eFXePtHXqsbbBp0ngXYVUAC368hMk3bZHJsGhvl2gBXre3J47RPGhsXDNzXoZKZ4P93d2AwX35R5djL7Er2LXHHYOPME903llahf4A8W5meLbDqZ/VPZEuhEAQVwJ47aNGzz0BPGWM4fuU9tp3JEV8V+D3c6a/YgPmYy+zH4ZPThWN7ulVg+mXWpbAlIoDEBBXBjTjpKAg0J2Pls6Kf5pGO5wy3xs4ZOauKgaMclM0BPZgl3DJ0WbTnoGy52DMvcIv8Z/Xu0LvNAhvk1eMQrcf/IKuxCNgksX7GwuNn9jZtorg6VgATWI6AA1vSQQAsFbI45FYcTrWWZV+LK4UUHOT4ZOjw1kcDz81wObOKVeMPaAAankuewMOTxod9ro5WqLPzIwH97Jc4aOtbPczyWl7nP81V/NocA93XLHYUWDqOKksCUCCiAp4RZlUgAgjyfs5anvDLfWZ9HtcDrapYvGMN5za47PVa5fp6vRtszpiw/DB02c5/mO614LSl6sCtIMdudxX3auEGzXALNCSiAm/PS0R0sUF3IHrWQeW6FX5mlPN6uXYl/G07xSs9wnynyj1a0M1jAXMdh457Z3NbKoIz2XcbyJrfKfnrKuRUjpTKmk4ACeDqN9jTva5Djndawn3X4atJPUlsw1V56wx6e9xZzz1QOTbXA62shrlfm91NZr+qSgATWFVAAa0ZIoEmBaAOEwONo1vzOe22Tp8eH27lkghncApS9EieMp4zxnhPtC2xho2yJI0aW4ec4GcOhOJww1X8YjLc/Ok8CnSqgAO7UkVO7ExOw89g8cDnVhCxu58VD6gHZ3diCLMYUeXToWH8+L7M9bOM9T9ks5/l6Zeh7CUhg/AIK4PHb6UwJNCQQ5NjdGm7B8KN22nmoP89NBuZ4JeY11BEdJAEJtFRAAdxSThUmgRcLxCtezWUGFaqNPnlsd2F2VNLIq1C7Dz08hctSfAO14bVZSAGhARv9e/Q7MzuTYVtq0YNX0brMTo2N0tBHOT7XjCxjPOMX3U6nhzRLWT1U93jK0TkSmG4CCuDpNuJt0N+1IbIxQSufyG2Drq1tgp9jf+vE7+Eux9LnlfjEyPbZPcgGA3wbuMsrcs7w7/0Cf4n+t1fklev8+5rfaM80lne7Za4Y+s7PcyCGK43ls24p3h+Y6Mlnm6IPuMgrcaJf4BvRfsLpGmfWUlxqDTNtyGXZ8rr7BDfr6Of5PvBuE1Jw+7jb7owbbMiVWFZ4ZU5qtjwdL4HpIqAAni4j3Ub97M/zPgPnGMMJbpFL46u1BWwNVNe3UUG0uIRrWN2qV3Mmk8Ruj8cWbFqrsH8tRX8m4Opqhpen4e+mzCNxn+eS8bMcbSz/8Pq4ZjLbs86V8i7MrszmpcawX2jZyrWca8r8vVX1RwHsb8QfnZB73DLvbVW5KkcC3SagAO62Ee3Q/vj5eMu7+7wSbxqtC9Ht1SDPX6yhnC1yVKd1M1pcY8DytRR8L1PikqTab+eyMT30RO9Bx1fNcKAJ+V505ZpUm1SvBKargAJ4uo68+j2qQLQPrlNjdnoJdxoIp4qpP8/FUV3ZEkdPRp3R3QPHsmHocKaFXXoMR4dVNs9kuMos4rl6dQa9HGpT8XaRp3lFvlnveH0vAQnUF1AA1zfSEdNIIP490/Aat4c9zK30t6Lr/QW+bOAjKcO+oWVHCz/F8qH4ISjLhm6ZL/bn2ccxbG4tpxPtjlTi0wM5XleDkw1c5pb55XjaEq2qFfTwGSzHW1jpwD8sPGlhlgMFDCdmZvIznmcmz+KP9ZBY/CDZ9mR4kGorHtwaT190jgS6TUAB3G0jqv5MuUB/jjON4VDrcOBoK2zFD509GP8XBHn+18CjIVyM4RIHbnWLHBY1OvpNuDKDl2dSPFOpsaE13AjcbAb4lLuEZfExuzA72IBjgeVekauHOmsX8FIc7NBvudFqV6FlHyfk+prhSAfuCA3zgaOsiX/v3ThbZKvofD/PwUTtgc97Jc5uFjDo5RXWYV8Tcr1uZTerp+Ons4ACeDqPfpf2PX4tJrq8XEZlKroYb3YPczL93F+vzmove9sUfjrknoEUr6nV+ABwjVeOnyQe9RO/TjSPGQxQBWYFM/msY+nLlNbcto4+/QVuxRJkS+wT7cgUpHgfNbbH8m13gOcCl2uocYM7wGkEOMzCMWWebYXP4BrbR6UcLk0v5tZWlKkyJDAdBBTA02GUp1kfo1d4LMzJFtm2Xboe3wo29GJYgeEX1rC5F7JbxfBmY3kgU2ZRfy/7GodDHctFmXL8+tCacM3xA2M4xhBvRfizzAB/MrfzzGh9szm2qxiuDg0bG8tNwEr3GT5S3YhX1OCbWF6bguOHh3e7GKkdEphuAgrg6Tbi6m8iApU8C0PDGQZ+mgn5H6oYs5RVwxtTKTA/hNc7ITel+7lr6Gra7+UtqRS71dY8sZzB8DsMB1v4vDtAuZLiixjuMTW2CJ04qP8GLMXy3xa2dMucP7RARvQuMBbXK/HhRCBUqQQksFZAAazJIIE2EggKvM1aLsTyaa/MeUNNi37j9R3e2BPyQK2H71nLEgfus/AeLFdhONBarjWG5W7INYHDhcBuXgmvjbqnpkhAAsMEFMCaDhJoM4Fqjr0GDCcZy0WjbRkY7xfcw8fSIX+t1viT9wKPDH96OX4ozGGOV5zaVaj8fFzfOwx82C1xV5uxqjkSaDsBBXDbDYka1M4C0dPF1vJcpsSSyWpndLVbSbGHHaDs3c69I+uJFtOozOR4G3KnV+Z/R34fvbOLITvenZr68ywysNIrcdBofYxWuhpaX3r4934vO1uHbT3LklY94DVZxipXAu0goABuh1FQGxoSiJawxPB5YznJK3FlQye18KBoNS4/z3XGsMwr8sEWFt1WRcVbEmYYGPWVqt3YIvD4W7TutDf4+lTU+Ghd60qV/U3IQ5loqwd9JCCBugIK4LpEOqBdBOxcZjGbDXF4ciKLZERXaqQ4C8tvvRLnt0v/Orkd8R7JGX6A4SatlNXJI6m2T6WAAngqtVVXQwJ+L2/CYEf7/bOhAuocFL8na9nbpHjALa7ZdUgfCUhAAlMtoACeanHVV1cgKHCRtdS8EsfVPXgaHhDk2N0xbNBT4pYk9t+1OWYEhrKBW9wS75uGQ6AuS6AlAgrgljCqEAm0RiD+/TXNscZyvVfi2tFK9Qucay3zvNXsO3Llrf75bG96uAC4yitxVmtatW4p0cpclRy7ZBxWdcLWkJNhoDIl0AoBBXArFFXGhAX6C9xoLM+P9eTthCtIoID+hezg1DjMsdyS7otXpar7ic+xHO7U+HOj5wwv1M5jZpBhDxPy8FjrMvt5TsDwgRSclC5yS91G6QAJSGBSBBTAk8KqQpsVCHLsamvURnvtptmy2uV4fyEvJ+RYoqvZMr9vl3bZAltWYcv0c9xnlvP8WO2Kd0CK1tQeY1vGoJd5NsUbsFztlVjeLv1TOyTQKQIK4E4ZKbVzSgXsQjYJamzoPsnD5kH8Ka28TSrzC9yFZVuvxIajNSlaMKTm8A6nxiV69ahNBk3N6CgBBXBHDZcaO5qAzbFpxfBaLMvdMn9thVJQ4FPWcpxjOSraKKEVZbZjGfFWhJa9bY3vZW/nwXZso9okgW4VUAB368hOo37Ft0IdzjCWX4x39aeJcvl5no92OvKKLJhoWVN5fn+ONxiHnFvhv8wdPDyVdasuCUx3AQXwdJ8B6n9LBKJVsqKCDNRaUqAKkYAEul5AAdz1Q6wOSkACEpBAOwoogNtxVNQmCUyxQLzMp8smBDxplvFCvertq9im2sO2afirNl6op6XvJTC6gAJYM0MCTQhEq1BZw55Y/uCVua+JUxs+1OZI8yzO8C0GGzk5KPDKELb0eril2bWygwJHhZYvOYZPukV+Xq++/hzHYTguFfKRTB+31Tte30tAAi8WUABrVkigCYH+XvY1Doc5NX6YWUKpiVMbPtTPcxWwr1thE7OUVY2eGOT5jDW8wR3gaLOEf0bnRVsHVucwP7Q86fWxotGydJwEJDD5AgrgyTdWDS0U6M/xBeOwlVfk+BYWO2VFRVep1vKBwaUif9dsxZU8C0K4GMOPG9l1yL6abf0al2O4Nlvk9GbrG368n+crwEmOYd9MkeJEytK5EpBA/NCmPhLoHIHovVUH5mRKXNI5rf7/lg6u1fwWBxZnSixutg/RRggVw44Zw0pT5NFmzvfzvBE40MCP3BJ31Ts33rYRdnJ9itUZvKVmeZPncCZF7h5rdax6Zep7CUjg/wUUwJoNXS/g5/kP4NjBRTX6pqLDdgEvDXq4AcuvvBIfa6bOSoFCGLK5C783ZaqNnBv9hmtD5rsVzjR38rSdS6Yyk5dlKjwz9H5vJc/CEPY0lgetpd/dgOvMDQwMlW9fzQasIstdrIxep6rkOTo0HOnAp4C0hV0yq7jKLOOpRtqkYyQggfULKIA1Q9peYLwPJa0NlgVsVnHYJJPhb6M9nBSFVTCDOywszpb4t+Eg0RVrymGT9HPcNdZDUVFwBSE/t1Aaus1r96HHf4ZtPZcZAzU26qlxj1nCE0NlBwVOt5aNvRIfHTkA8W12Q85NcaRZxHPDvw/yfC40HOBVeMfwhTP8Xt5Cil1dhx9E59gCLwngd9Zys2N52BoOS1l+E936rjm8E9jFDXj78N+Y/TzftYZ3UOU1WhWr7f9voQZ2gYACuAsGsdu7sPahJMsWk/HKy9rt9WC1KfP3dQK4EK+wdaCb4hCziIdGs44CuBJygbFsEhoe6Klx5YDDFy1s7RhOCC0fc+BaDNtj+WZ0+zcocJgJ2TQd8N+4PNXola6fYyfHsln6OZZEfxBEGyZUCrwiM8ALQYqXG8PmFrYylveEhi2N5efWsjCVohrWyOGQxnKLsfzDws1eme93+/xR/yTQrgIK4HYdGbWr7QX8PE9jeD6EGSlLxhpuIOQqDCcDO2L5jlfmP6rz2afWE+/tu9StcnB05WpzzKkYnrJQdeB1w38P7s+z3MBLhz8FHa20VcnxaQxHhfD1bIkLB18FOtbAFhiuN8R/POxmLY8beBLDGy1sFt0+Zk37VjiWm6JbycbET1f/rpFXjtp+INRACXSogAK4QwdOzU5eIHrFhznMpgePJ3misiFvs/B6oGAtS0yKrzFAaFJ8xli2T8P7TIn7o5ZXcrw6NHzJhFzk9nHp2tvlc9l4IBs/4T2QLvONtf++PV6wKT934JG05QumzCO2l50rDsfYkNu8Pn4zuBdwtJ7zDe4s3lF5gXda+CpwJYbfGsvpGHYFPph5jqvWtxVh8rpqgQS6X0AB3P1jrB5OskCQ4xBr+HcD11pDxa3yQ3M7z0TV+jn2t4ZjeyzfTZe5Ofq36JY3C9gqSLO7rbB8+O+tQS+H2hSfM5YvuiUuXxvAObYLHJZbyy+zJY6Oy5nLLH8m3zWW270SZ8f/lmNO4PBeYLlb5Nqglx2Mw3wLq70SV/k5TrSG13s1Pjb0rnAjPP15FhnDY16Rgxs5XsdIQAL1BRTA9Y10hATWKxAty+ineZnnc7e5i8eGDvYL/CK69euVOGR4AcEC5toUfRgu8Yq8vxHeOLS3jxeLrA3/vTi+Ct+YWTzFC/Fvwjk2DRxOcyx9mRIXx38ErHm4aqNskaPWaceaB8H2dX2OiNptc2zn13BGewAr6OUVNmTAu517G2mvjpGABOoLKIDrG+kICawViBajsIb9vICDzFIeXx9NZQF5UjjNvO/r5zk/XgXLsocps3J4+dEDWO4A/vCnn4M8R4SG76ZCPp4p85O1V8xrdmcKTXzBHYdwtIjGDK8U/z4df6I/BMIUm3sruc08iO8XuM7C7GyRhRpyCUhg8gUUwJNvrBqmUMDPc7c1bJgtstVEqu0v8J/Rk8JeiR+sE4J5dnRqbJx2uGOsJ5ej27w4fNuxvG/oKnSojP6F7OCEHB1absyW+ePINtocWwWWmW4fD4zc2tDPx0tJLvFK8WtEY34qC3hV2EMZON8rclIctgXeFl2NuyV+NhEXnSsBCbROQAHcOkuV1AYCrdqXN8hxWujwULbIj5vtVny7eB9S3EBt6Ap0qAw/z44Wjibkxmwf1zdb9lQc319gPxNyqmP4bW2AX+md4KlQVx3TUUABPB1HXX1uS4HoyWhrOADD5W6RvzTayP48fzbwz+FXxnYBWwcpZrslVgxdSfsF/gfLbK8UL0k55scW2LJSYz/r8ElruCJb5LONtkXHSUACjQsogBu30pFdJhA9RVyZyUEm5MFMmUXj7d7gspPfJ+Rar8y3xipn7VrMNS5wl7Bs5HGVXl5TczjAgctHrtUcPegVZLgZy2+G/44blTG4RWLFK7F82JX2d4F/cS17Df2WHOTZzdRIZZZwx3j7qvMkIIHWCSiAW2epkhISGFyJ6iUZw6NmMU822gy7G1v4HucYuMkr8b1Gzxt5XBTkwUz2MiEPu2XuHKucobWYrcOvs4t5oJn61i5taVg1fEnLZsoYOjZe2jPFBjzOqujhq/GUoXMkIIGJCyiAJ26oEhIWiK8sDWdZ+MZ4frNNuPlx9XZ3NgpcNndX87BZxguNtikK04rhE1gecMtc1sh5fp43W8MlJuQMr8y3h58TLW3JQjbCx29mL+JG6tUxEpDAugIKYM0ICTQhUM2xV2jYImO5stH1mxspvr/AMcbySSwne2V+P/KcwR2d9nQdjht+lR9tJOHP4LMYVgz/46M/z0+MYWOvyL82Uv/QMdEWhDbFbcbyX16JDzdzro6VgASaE1AAN+elo6e5QFDgs9Yyz7Ucbcqsrsfh5/m2hXeZkD28vvg1onF9oi0Kbcg2mSe5upHbxtHtbmPJDK2+Na5KdZIEJDCpAgrgSeVV4e0mYOexecVls0zIA40E6ETbH/0+TBaPMk+PfK93omVP9PxKjn+rOXyoB05JF/nTRMvT+RKQQHMCCuDmvHR0hwv4eT6C4TgHjskUKSbdnegWMlmyrNkKsdpMewbf1z3AWC50+7i7mXOjY6PXjaoDbJu2rBhau7rZMnS8BCQwfgEF8PjtdOY0EIgW5CDaYKHE1yaju4O//Z5lLB8c7SGq/gLvNXCeDflwtswPh7chem0pTLEXlv/xBndZGv79YNnfMvBBt8R/TUb7VaYEJDB+AQXw+O105jQQ8HPx2slVr8x5jXQ3yPPW0JD34HumyKONnLO+Y+KVvbYnzYNUm72FHV9dZ5hBhdVmGZWx6glyHGkdvmQsp7gl/nuibdb5EpBAYwIK4MacdJQEGhLwcxxkYEEm4ILhOyM1dPIUHxS9B13NsG16gMd8hx6vwspmXoGa4uaqOgl0nYACuOuGVB2SQGMC0UNYoeHDNuQT7boudWM90VES6EwBBXBnjptaPQ6BaHvAMMVFwI+GNrAfRzFtdUr8frBhXzfkWFPmkdEaZ3PMYICN6OHpqXjyu62A1BgJtLGAAriNB0dNa62AncfMSoYdMj5PjHV7OPrNtZLnUwb+MXIrwVa2xs/zawz7uyFbmjLPjlV2f57LMKSyRQ4f7Zigl3k2xdZuyI1jhWuQ452hw1kOfMot8tNW9kNlSUAC4xdQAI/fTmd2oUC85vILfB7D37JFLqjXxWgpyAD2dxweb+a1png95idJ1VtUI1p5C4tJ93FTvbboewlIoLMEFMCdNV5qbZsJRBtBBDUus5Zytszn2qx5L2pOtFdxkGNHN6TfLOGf7d5etU8C3SygAO7m0VXfJDBCIHo1KZjBMgulbIkjBCQBCSQnoABOzl41S2BKBKKrXuYxg9UMmBUEU1KpKpGABOoKKIDrEumA6SQQFHiltexjLNe5Zf7aCX23OTYNDJ9xoC9T4pKRbY7Wvw4y3G/hN9kS7+qEPqmNEpgOAgrg6TDK6mPDAtFDTzXDEY7lkkyZRQ2f2MCB/QvZwVhONfAHt8jP651i9yDLajbG8sz69ua1OeYEhmOA5V6J39UrV99LQALtIaAAbo9xUCs6TCDI8xlrOA3LwV6Jaxtpvl3AZr7DW1OWuzJ93FbvnKCXQ8MU38HyuWyJH9U7Xt9LQAKdJaAA7qzxUmvbRCB6XYkH4/8qBsI2aZaaIQEJdJCAAriDBktNlUAzAv05jjMO3zHwfi3A0YycjpXA1AgogKfGWbVIYNIEoqvx4AXeh+Uhr8z/DlU0kZ2UJq2xKlgCElgroADWZJDAOAT8AncBD3lFDqh3erxYR5U9DPzd7ePuesc3+73dGTfYkHMw3O0VOafZ83W8BCSQjIACOBl31drhAjbHdoQMNLKalD+fl5HmO8CVXpFzG+l6vMazwzEWfp0tcUMj5+gYCUigswQUwJ01XmrtNBHwe9kZh7c4lhszZfrG6n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