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Jun 15 13:46 refactor: implement _summary_list_field function to streamline handling of summary fields in coach summary; enhance payload processing and validation for string and list types 13:15 refactor: add functions for JSON payload extraction and validation in coach summary; streamline summary key handling and improve error reporting 13:07 refactor: introduce compact representation functions for metrics, issues, and knowledge cards; enhance summary evidence generation and improve error handling in JSON extraction 12:56 refactor: enhance JSON response handling in coach summary generation; update response format instructions and improve error reporting for invalid JSON outputs 08:15 refactor: enhance _encode_bt709_output and _encode_bt709_command for improved audio stream handling and code clarity 08:07 refactor: remove sample_pose_cache module and streamline pose processing in pipeline Jun 14 23:24 refactor: change default delegate to CPU in MediaPipePoseBackend and update tests accordingly NLag
23:05 refactor: update artifact URLs and improve router device handling for better classification performance NLag
22:40 refactor(mediapipe): simplify GPU delegate preference logic and remove unused CUDA visibility check NLag
21:58 refactor(mediapipe): enhance MediaPipePoseBackend to prefer tasks on GPU and improve delegate handling NLag
09:39 feat: load external coach knowledge packs Jun 11 21:36 fix(hf-spaces): install mediapipe native libraries 21:23 fix(hf-spaces): avoid pickling analysis progress callbacks 21:07 feat(pose)!: use coco17 3d router features BREAKING CHANGE: exercise router artifacts must be regenerated with the coco17_3d_v1 feature schema. 18:51 Implement grounded coach summary with HF SLM 15:47 feat(hf): use ZeroGPU for analysis 14:55 perf(pose): read dense video frames sequentially 14:26 Merge branch 'main' into NLag/issue4 14:24 refactor(mediapipe): improve code readability and add CPU delegate option 14:03 Avoid OpenCV H264 writer fallback errors NLag
13:37 feat(report): add annotated issue clips 12:44 Merge branch 'main' into NLag/issue4 12:36 fix(renderer): preserve video colors in annotations 12:21 refactor(exercises): route pipeline through exercise objects 11:42 Implement frame-level issue markers 09:39 Merge branch 'main' into NLag/issue4 08:39 refactor(exercises): introduce exercise strategies 08:14 Merge branch 'main' into NLag/issue4 08:11 fix(rep-analysis): split exercise analyzers 08:01 Merge branch 'main' into NLag/issue4 01:42 Merge main into issue 4 branch NLag
# Conflicts:
# app.py
# uv.lock 00:58 Implement exercise classifier router NLag
Jun 10 22:28 Merge branch 'main' into issue-6-rep-analysis-variation 22:04 Detect exercise variations from rep metrics Daphne
22:04 Implement pose-derived rep metrics Daphne
22:03 feat(rep_counter): implement exercise-specific rep counters for push-ups, shoulder presses, and squats; add dependency on fastapi 16:20 feat(pose): add pluggable pose backends 20:31 fix(rep): ignore noisy extrema in squat cycle segmentation 20:14 refactor(ui): clarify mocked downstream analysis 20:13 fix(renderer): prefer web-friendly video codecs 20:13 feat(pose): use dense frames for real pose extraction 20:13 fix(classifier): default auto routing to squat 19:54 feat(renderer): generate annotated pose videos 19:54 fix(rep): clamp mock analysis scores for long sets 19:34 feat(pipeline): persist rep debug artifacts 19:34 feat(rep): implement deterministic exercise rep segmentation 19:34 feat(rep): add shared signal and state machine utilities 19:09 refactor(exercises): centralize exercise definitions 16:20 feat(pose): add pluggable pose backends 13:48 feat(video): add intake quality gate Closes #2 
