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nx_pose_estimate.nx

buildroot/runtime/nx_pose_estimate.nx

3249 B75 linesdepth 2pulls 2 transitivereach 2 importersview sourcekind librarytopic pose
docsdependenciesstructsconstsfunctions

about

nx_pose_estimate.nx -- LEARNED pose localization from an image (roadmap R2 v0, the video->POSE keystone gap). Sovereign + deterministic, the text2motion playbook: a silhouette (z-buffer occupancy grid) -> a PERCEPTRON that classifies WHERE a keypoint is (a coarse region). Trained on rendered rig poses (we generate the data), proven by HELD-OUT generalization. Honest ceiling: coarse region-classification of ONE joint on OUR-render silhouettes; SOTA = precise full-body keypoints from real video via a trained CNN (OpenPose/MoveNet). The architecture (image feature -> learned classifier -> keypoint) is the real thing at small scale. ORIGINAL

dependencies 1 imports · 2 importers

nx_syscalls.nx nx_pose_estimate.nx nx_pose_estimate_min.nx nx_poseest_gate.nx

imports: nx_syscalls.nx

imported by: nx_pose_estimate_min.nxnx_poseest_gate.nx

structs

none

consts

8const K_MAGIC_1900000000: i64 = 1900000000

functions

11func pe_occupancy(zb: *i64, w: i64, h: i64, gw: i64, gh: i64, occ: *i64) -> i64
called by 1: pe_sample
35func pe_score(W: *i64, r: i64, occ: *i64, nfeat: i64) -> i64
called by 1: pe_predict
40func pe_predict(W: *i64, occ: *i64, nfeat: i64, nr: i64) -> i64
called by 2: pe_trainmain calls 1: pe_score
48func pe_train(W: *i64, occs: *i64, labels: *i64, nsamp: i64, nfeat: i64, nr: i64, epochs: i64) -> i64
called by 2: mainmain calls 1: pe_predict