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13
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1.03
1.03
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int64
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af_alloy
1.03
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[ { "scene": 1, "speech_start": 0, "speech_end": 13.3, "scene_end": 13.75, "duration": 13.75, "text": "Train Cellpose fine-tunes a CPSAM segmentation model from paired microscopy images and instance-label masks. The console reports the selected data, training progress, checkpoint path, and rep...
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af_aoede
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en
af_bella
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[ { "scene": 1, "speech_start": 0, "speech_end": 15.85, "scene_end": 16.3, "duration": 16.3, "text": "Train Cellpose fine-tunes a CPSAM segmentation model from paired microscopy images and instance-label masks. The console reports the selected data, training progress, checkpoint path, and repr...
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af_heart
1.03
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[ { "scene": 1, "speech_start": 0, "speech_end": 14.925, "scene_end": 15.375, "duration": 15.375, "text": "Train Cellpose fine-tunes a CPSAM segmentation model from paired microscopy images and instance-label masks. The console reports the selected data, training progress, checkpoint path, and...
1
en
af_jessica
1.03
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[ { "scene": 1, "speech_start": 0, "speech_end": 12.775, "scene_end": 13.225, "duration": 13.225, "text": "Train Cellpose fine-tunes a CPSAM segmentation model from paired microscopy images and instance-label masks. The console reports the selected data, training progress, checkpoint path, and...
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af_kore
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[ { "scene": 1, "speech_start": 0, "speech_end": 15.325, "scene_end": 15.774999999999999, "duration": 15.774999999999999, "text": "Train Cellpose fine-tunes a CPSAM segmentation model from paired microscopy images and instance-label masks. The console reports the selected data, training progre...
1
en
af_nicole
1.03
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[ { "scene": 1, "speech_start": 0, "speech_end": 22.55, "scene_end": 23, "duration": 23, "text": "Train Cellpose fine-tunes a CPSAM segmentation model from paired microscopy images and instance-label masks. The console reports the selected data, training progress, checkpoint path, and reproduc...
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af_nova
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[ { "scene": 1, "speech_start": 0, "speech_end": 13.425, "scene_end": 13.875, "duration": 13.875, "text": "Train Cellpose fine-tunes a CPSAM segmentation model from paired microscopy images and instance-label masks. The console reports the selected data, training progress, checkpoint path, and...
1
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af_river
1.03
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[ { "scene": 1, "speech_start": 0, "speech_end": 12.575, "scene_end": 13.024999999999999, "duration": 13.024999999999999, "text": "Train Cellpose fine-tunes a CPSAM segmentation model from paired microscopy images and instance-label masks. The console reports the selected data, training progre...
1
en
af_sarah
1.03
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251.5
[ { "scene": 1, "speech_start": 0, "speech_end": 14.85, "scene_end": 15.299999999999999, "duration": 15.299999999999999, "text": "Train Cellpose fine-tunes a CPSAM segmentation model from paired microscopy images and instance-label masks. The console reports the selected data, training progres...
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en
af_sky
1.03
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[ { "scene": 1, "speech_start": 0, "speech_end": 13.975, "scene_end": 14.424999999999999, "duration": 14.424999999999999, "text": "Train Cellpose fine-tunes a CPSAM segmentation model from paired microscopy images and instance-label masks. The console reports the selected data, training progre...
1
en
am_adam
1.03
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242.65
[ { "scene": 1, "speech_start": 0, "speech_end": 14.55, "scene_end": 15, "duration": 15, "text": "Train Cellpose fine-tunes a CPSAM segmentation model from paired microscopy images and instance-label masks. The console reports the selected data, training progress, checkpoint path, and reproduc...
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spaCR tutorial media

Narration and 4K video for the spaCR interactive tutorial library, served directly to https://einarolafsson.github.io/spacr/tutorials/.

spaCR is a toolkit for microscopy and single-cell analysis of pooled CRISPR screens. This repository holds the media its 40-lesson tutorial player streams; it is not a training dataset.

Why it lives here

GitHub Pages caps a published site at 1 GB. The full narration set is 2,662 MiB across 54 voices, so the site could only ever publish one voice per language — 27 of the 28 English voices were unreachable. Hosting the audio here removes the cap rather than rationing it, and leaves room for the 4K video too.

Layout

Paths mirror the tutorial player's own, so a single base URL resolves both:

<lesson_id>/audio/<language>/<voice>.m4a    narration
<lesson_id>/audio/<language>/<voice>.json   word timings for captions and sync
<lesson_id>/video/<lesson_id>_silent.mp4    4K silent master (3840x2160)

For example:

07_mask/audio/en/af_heart.m4a
07_mask/audio/ja/jf_alpha.m4a
07_mask/video/07_mask_silent.mp4

Contents

Lessons 40
Narrated languages 8 (en, es, fr, hi, it, pt-BR, ja, zh-CN)
Voices 54
Narration files 2,160 (~2,662 MiB)
4K silent masters 40 (~681 MiB)

How the player uses it

The video carries no audio track. The player plays a silent master and overlays whichever narration voice the visitor picks, mapping the two timelines onto each other so any voice fits any lesson. The site offers 1440p by default and the 4K cut from here as a quality option; both are the same cut on the same timeline, so switching quality does not interrupt narration.

Narration was rendered with Kokoro-82M.

Author

Einar Birnir Ólafsson — ORCID 0000-0002-3388-061X Uppsala University & University of Michigan–Ann Arbor

Citing

If spaCR contributes to your research, cite the software via its CITATION.cff.

Licence

MIT, matching spaCR itself.

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