nothing but datacenters the record

treatment record

glitch-06

The whole published pass so far - 6,251 frames, 4.3 minutes - with BOTH readings in one overlay: all-COCO segmentation contours and id boxes, plus pose skeletons and face mesh on the figures the prompts say should not be there. Composited 'under', so the HUD is drawn onto the plate before displacement and the blockouts cut and carry it.

status
preferred
upstream
pass-02 frames 1–6,251
evidence
Video only. No frame sequence was written, so the encode is the record.
frame 1 · 0:0021,600 · 15:0043,200 · 30:00
glitch-061–6,251

Its window on pass 2's full 43,200-frame axis.

what it looks like · 12 frames

This treatment kept no sampled frames of its own, so these are the source frames it consumed — pass-02 1–6,251, before the treatment was applied.

departs from the baseline

Two detections files merged into one overlay, which no single detect.py run produces: --draw-mask needs masks and --draw-skeleton needs keypoints, and one model gives one or the other. The merge is a union with pose ids namespaced 'p<id>' because the two runs use independent trackers - see cv.merged_from.

Upstream

pass
pass-02
frames
1–6,251
source
regenerable: hstack of passes/pass-02/{frames,text} 1-6251 (image left, text right)
source sha256
41d8807682ce

Regenerating the source

ffmpeg -framerate 24 -start_number 1 -i frames/frame_%06d.png -framerate 24 -start_number 1 -i text/frame_%06d.png -frames:v 6251 -filter_complex '[0:v][1:v]hstack=inputs=2' -c:v prores_ks -profile:v 4 -pix_fmt yuv444p10le source.mov

Render

composite
under
device
cpu
frames
6,251
clip length
4 m 20 s
time to render it
42 m 21 s
chunking
160-frame windows, 40 of them, 124-frame lead-in discarded
overlay draws
box, mask, skeleton, face_mesh
overlay hold
1 frame
stroke / bracket / label floor
5 / 56 / 4,800 px²

Displacement layers

gridmax offsetanglesparsityjitterholdstaggerseedenvelope
4×33290°0.50.880.65none
8×7220.80.860.59none
20×18140.930.840.813none

What the detector found

model
yolo11n-seg.pt + yolo11n-pose.pt
confidence floor
0.15
detections
2,738
per frame
0.438
labeldetections
person748
train321
bench288
clock171
refrigerator137
suitcase102
truck102
car96
airplane60
kite49

Outputs

fileframesgeometryruntimebytessha256
previews/glitch-06.under-contours-skeletons.f000001-006251.mp41–6,2511536x13444 m 20 s1.3 GB8060d8ab14d5

Named and hashed, not hosted. Nothing in this repository is a master.

Provenance

no task id

This treatment was run as a local process rather than dispatched through the mesh, so it has no task id, no lease and no event trail. That is a gap in the record, and it is recorded as one.

Note

No frame sequence on this run, deliberately: writing 6,251 full-resolution PNGs measured 2.3 frames/s, ~45 minutes on top of a ~42 minute gather, for an output a look is not judged on. This is look development and the video is the deliverable. Re-render with --frames-dir once the look is locked; the source and detections are recorded, so it reproduces exactly.