FreeSkills
Commits, branches and sync with the but CLI
- 361361 downloads
- 198198 likes
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Works with
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Train an OCRNet text recognition model v1.0.0
Use this resource to train a model that reads text from cropped regions of images
New
- 442 downloads
- 131 likes
- 145 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install scene-text-recognition-trainingWith no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.
First time: connect the CLI with
npx --yes palatekit@latest loginThe agent prepares the dataset and spec, chooses the decoder, runs training then evaluation, export or quantization. It relies on the supplied spec templates.
Mostly picked by
Updated November 2, 2026
Previews
Details
- Install guides
- Generates with
- Your agent's model
- Licence
- Apache-2.0
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What you get
- SKILL.md : actions, requirements and checkpoint selection
- references/spec_template_dataset_convert.yaml : dataset conversion
- references/spec_template_quantize.yaml : quantization template
Good fit for
- You read plates or labels from regions that are already detected
- You want to compare CTC and attention decoders
Not for
Tags
- ocrnet
- text recognition
- ctc
- tao
- ocr
About
You say
“Train OCRNet on my cropped text regions with a CTC decoder.”
Skill published by nvidia under the Apache-2.0 license, delivered in its original version.
Show moreShow less
How to use it
- Install the skill in your agent's skills folder
- Ask your agent to train a model that reads text from cropped regions of images
- Review and adjust the result
Content preview
Files
- BENCHMARK.md7.1 KB
- config/skillspector-baseline.yaml0.8 KB
- evals/evals.json0.8 KB
- LICENSE11.3 KB
- NOTICE-PALATEKIT.md0.5 KB
- references/skill_info.yaml8.5 KB
- references/spec_template_dataset_convert.yaml1.9 KB
- references/spec_template_deploy_experiment.yaml3 KB
- references/spec_template_evaluate.yaml2 KB
- references/spec_template_export.yaml1.9 KB
- references/spec_template_gen_trt_engine.yaml2.2 KB
- references/spec_template_inference.yaml2 KB
- references/spec_template_prune.yaml2 KB
- references/spec_template_quantize.yaml1.8 KB
- references/spec_template_retrain.yaml1.8 KB
- references/spec_template_train.yaml1.8 KB
- references/tao-deploy-ocrnet.md5.6 KB
- references/tao-deploy-ocrnet.skill_info.yaml4.1 KB
- schemas/dataset_convert.schema.json29.9 KB
- schemas/evaluate.schema.json32.4 KB
- schemas/export.schema.json30 KB
- schemas/gen_trt_engine.schema.json37.5 KB
- schemas/inference.schema.json32.2 KB
- schemas/manifest.json20.6 KB
- schemas/prune.schema.json32 KB
- schemas/quantize.schema.json29 KB
- schemas/retrain.schema.json29 KB
- schemas/train.schema.json29 KB
- skill-card.md4.8 KB
- SKILL.md17.4 KB
- skill.oms.sig10.3 KB
Origin and licence
Listed unmodified
- Author
- nvidia
- Source
- github.com/nvidia/skills/tree/ca116d60beafe1b4459f0ab790b7b450912c56b0/skills/tao-train-ocrnet
- Licence
- Apache-2.0
Notice
« tao-train-ocrnet » (nvidia, Apache-2.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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