punch/ | Punches in a round: start/end time + type per hand | The main tool. Its labels are the training corpus for the punch classifier |
unusable/ | Stretches of a video where the BlazePose skeleton can't be used (with a reason), a reviewed mark per video, and the whole-video retirement into Skeleton Problems | The unusable-footage pass, made AFTER extraction (the skeleton doesn't exist while rounds and punches are labeled); feeds the roll detector's exclusion mask and the skeleton-usability model |
impact/ | The exact impact frame of each labeled punch | Trained the impact-frame spotter |
punch_directions/ | 16-way (22.5°) direction of straight punches | Trained the axiality (punch-direction) model that three rules gate on |
bodyshot/ | Head vs body, one short clip per punch | Refines punch-type labels where head/body was ambiguous |
callout/ | Called-out combos in guided rounds vs what was actually thrown | Measures how well users follow the app's callouts |
rules/ | Form-rule spot checks on rounds | Ground truth for rules-engine tuning |
chin_tuck_1.0/ | Three chin-vs-shoulder questions per sampled frame | Current chin labeling. Repeated samples measure each labeler's self-agreement ceiling |
chin_tuck_0.0/ | One verdict (tucked/level/air) per sampled frame | The original chin labeler, frozen for reference. Has no data of its own — reads 1.0's chin_frames.json/frames/ by relative path |
uppercut_drop/ | How far the punching hand drops before each uppercut: Great / Good / Bad / Very bad / Can't tell, one looping clip per labeled uppercut, ~10 % blind repeats | The coach's ratings set the cut-offs of the "keep your hand up before the uppercut" score |
roll_eyes/ | Do the eyes stay up through each roll: Good / Mid / Bad / Can't tell (with a reason) + a comment, one looping clip per labeled roll, ~10 % blind repeats; the name admin shows the model's head angle and every rater's answers | The coach's ratings set the cut-off of the "keep your eyes up when you roll" rule |
roll_legs/ | Does the boxer use the legs to get under the punch in each roll — Uses the legs / Doesn't / Can't tell (with a reason) + a comment, on the roll eyes clips; the scale is one PASS block in roll_legs.js, an example per rating, ~10 % blind repeats; admin shows the skeleton's knee bend and lean | The coach's ratings set the cut-off on the knee bend |
roll_shoulders/ | Do the shoulders rotate through the roll — Good / Bad / Can't tell (with a reason) + a comment, on the roll eyes clips, frontal rolls only; the scale is one PASS block in roll_shoulders.js, an example per rating, ~10 % blind repeats; admin shows the skeleton's shoulder turn | The coach's ratings set the cut-off on the shoulder turn |
bag_bite/ | Does each punch on the heavy bag snap or push — two buttons, Snapping / Pushing, + a comment, one looping clip per punch cropped to the boxer, the skeleton on it and beside it with the facing angle; 200 punches, each once; admin shows every rater's answers | The coach's ratings say what rule 41 (punches stuck in the bag) should measure |
guard_drop/ | Hands-down moments in a round | Ground truth for the guard-drop rule |
hip_rotation/ | Rotation-quality rubric per punch | Ground truth behind the hip-rotation rule |
bladedness/ | Pairwise "which stance is more squared?" (shoulder pairs + hip pairs), plus the coach review where the coach scores curated frontal frames | The too-squared/too-bladed research — pair judgements calibrate the candidate metrics; the coach review is the expert reference |
axiality/ | Review of ground truth vs model direction predictions | QA pass on the axiality model |
