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Merge pull request #262 from alan-turing-institute/add-nb-deepforest-…
…livestock Notebook - Livestock detection using DeepForest
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Submodule 95199651-9e81-4cae-a3a7-66398a9a5f62
added at
f83443
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|---|---|---|
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@@ -10,27 +10,27 @@ | |
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| # metadata | ||
| metadata_contribution = { | ||
| 'environment': 'polar', | ||
| 'environment': 'farming', | ||
| 'topic': 'modelling', | ||
| 'reponame': '67a1e320-7c47-4ea9-8df8-e868326bc90b', | ||
| 'title': "Sea ice forecasting using the IceNet library", | ||
| 'inputs': {'input1':{'name':'Codebase of the IceNet library', | ||
| 'url':'https://github.com/icenet-ai/icenet/'}, | ||
| 'reponame': '95199651-9e81-4cae-a3a7-66398a9a5f62', | ||
| 'title': "Livestock detection using DeepForest", | ||
| 'inputs': {'input1':{'name':'Input dataset for the fine-tuned model', | ||
| 'url':'https://doi.org/10.7910/DVN/N7GJYU'}, | ||
| }, | ||
| 'outputs': {'content': 'results', | ||
| 'url': "https://doi.org/10.5281/zenodo.12612126"}, | ||
| 'url': "https://doi.org/10.5281/zenodo.14279111"}, | ||
| 'author_GHuser': 'eds-book-gallery', | ||
| 'references':{'ref1':{'name':'Seasonal Arctic sea ice forecasting with probabilistic deep learning', | ||
| 'url':"https://doi.org/10.1038/s41467-021-25257-4"}}, | ||
| 'sketch': {'title':'Image showing an example of the forecasted sea ice', | ||
| 'path':'_temp/rohub/67a1e320-7c47-4ea9-8df8-e868326bc90b/plot.png'} | ||
| 'references':{'ref1':{'name':'Deepforest: a python package for rgb deep learning tree crown delineation', | ||
| 'url':"https://doi.org/https://doi.org/10.1111/2041-210X.13472"}}, | ||
| 'sketch': {'title':'Image showing an example of the finetuned model predictions to detect livestock', | ||
| 'path':'_temp/rohub/95199651-9e81-4cae-a3a7-66398a9a5f62/plot.png'} | ||
| } | ||
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| title_nb = metadata_contribution['title'] | ||
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| metadata_rohub = { | ||
| 'title': f'{title_nb} (Jupyter Notebook) published in the Environmental Data Science book', | ||
| 'research_areas': ['Environmental research', 'Oceanography', 'Deep learning'], | ||
| 'research_areas': ['Environmental research', 'Agriculture', 'Deep learning'], | ||
| 'description': f'The research object refers to the {title_nb} notebook published in the Environmental Data Science book.', | ||
| 'ros_type': 'Executable Research Object', | ||
| 'ros_template': 'Executable Research Object folders structure', | ||
|
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@@ -48,34 +48,27 @@ | |
| # edition | ||
| authors=[ | ||
| {"agent_type": "user", | ||
| "display_name": "Bryn Noel Ubald", | ||
| "name": "Bryn Noel Ubald", | ||
| "email": "[email protected]", | ||
| "orcid_id": "0000-0002-0206-7140", | ||
| "affiliation": "British Antarctic Survey"}, | ||
| {"agent_type": "user", | ||
| "display_name": "James Byrne", | ||
| "name": "James Byrne", | ||
| "email": "[email protected]", | ||
| "orcid_id": "0000-0003-3731-2377", | ||
| "affiliation": "British Antarctic Survey"}, | ||
| "display_name": "Cameron Appel", | ||
| "name": "Cameron Appel", | ||
| "email": "[email protected]", | ||
| "affiliation": "Queen Mary University London"}, | ||
| ] | ||
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| ro.set_authors(agents=authors) | ||
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| reviewers=[ | ||
| {"agent_type": "user", | ||
| "display_name": "Wei Ji", | ||
| "name": "Wei Ji", | ||
| "email": "[email protected]", | ||
| "orcid_id": "0000-0003-2354-1988", | ||
| "affiliation": "Development Seed"}, | ||
| "display_name": "Ethan P. White", | ||
| "name": "Ethan P. White", | ||
| "email": "[email protected]", | ||
| "orcid_id": "0000-0001-6728-7745", | ||
| "affiliation": "University of Florida"}, | ||
| {"agent_type": "user", | ||
| "display_name": "William Gregory", | ||
| "name": "William Gregory", | ||
| "email": "[email protected]", | ||
| "orcid_id": "0000-0001-8176-1642", | ||
| "affiliation": "Princeton University"}, | ||
| "display_name": "Louisa Van Zeeland", | ||
| "name": "Louisa Van Zeeland", | ||
| "email": "[email protected]", | ||
| "orcid_id": "0009-0005-0392-4377", | ||
| "affiliation": "The Alan Turing Institute"}, | ||
| ] | ||
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| ro.set_contributors(agents=reviewers) | ||
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