This is the command line tool from das-element for .
It contains the API (supporting Python 2 & 3) and the classification of image, sequence and movie files.
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You can deploy it on your render farm to use it in a post-render process for tagging of elements |
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Each version will be shipped with the model inside. Use the |
Versions
There are two command line tool (CLI) versions with a different range of features and file size.
cli
This version is optimized to receive data from the database or update an element.
Smaller in file size and fast to use, but has a reduced set of features.
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get-categories Get all categories of the library
get-category Get category entity
get-element-by-id Get element entity from element ID
get-element-by-name Get element entity from element name
get-element-by-uuid Get element entity from element UUID
get-elements Get all elements of the library
get-libraries Get all libraries data for current config
get-library-template-mappings Get all library template mappings
get-tag Get tag entity
get-tags Get all tags of the library
license Show license
update Updates database entity |
cli_full
Includes all features of the CLI, like ingesting files, rendering proxies or running a machine learning model.
This version has larger in file size and is slower.
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delete-element Delete element
get-categories Get all categories of the library
get-category Get category entity
get-element-by-id Get element entity from element ID
get-element-by-name Get element entity from element name
get-element-by-uuid Get element entity from element UUID
get-elements Get all elements of the library
get-libraries Get all libraries data for current config
get-library-template-mappings Get all library template mappings
get-meaningful-frame Validate meaningful thumbnail frame number
get-paths-from-disk Get all file paths from a given folder.
get-tag Get tag entity
get-tags Get all tags of the library
info Show machine learning model info
ingest Ingest new element
license Show license
predict Predict the category for a give file path.
render-element-proxies Render the proxy files for an element...
update Updates database entity |
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Installation
Save the software to your preferred location. That’s all!
On Linux make sure to run this command to make the file executable:
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chmod +x das-element-cli_{version}_lin |
API
To learn more about the application programming interface (API) follow this link here.
Documentation
Python API
https://github.com/das-element/python-api
How To machine learning prediction
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Each version will be shipped with the model inside. Use the |
Simple usage
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das-element-cli.exe {file} |
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# Linux & Mac das-element-cli predict /path/to/file.#.exr # Windows C:\das-element-cli.exe predict C:\path\to\file.#.exr # result: {"/path/to/file.#.exr": [{"tag": "fire", "description": "rapid oxidation of a material", "value": "Q3196"}]} |
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das-element-cli.exe predict {file1} {file2} {file3} |
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das-element-cli.exe predict /path/to/files.#.exr /path/to/another/file.mov
# result:
{"/path/to/files.#.exr": [{"tag": "fire", "description": "rapid oxidation of a material", "value": "Q3196"}],
"/path/to/another/file.mov": [{"tag": "torch", "description": "stick with a flaming end used as a source of light", "value": "Q327954"}]} |
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das-element-cli.exe predict --top 3 /path/to/file.mov # result: {"/path/to/file.mov": [ {"tag": "torch", "description": "stick with a flaming end used as a source of light", "value": "Q327954"}, {"tag": "fire", "description": "rapid oxidation of a material", "value": "Q3196"}, {"tag": "flame", "description": "visible, gaseous part of a fire", "value": "Q235544"} ]} |
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# print the top 3 tag predictions for a given file path
import json
import subprocess
path = '/path/to/file.mov'
command = ['./das-element-cli.exe', 'predict', '--top', '3', path]
process = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
output, error = process.communicate()
if process.returncode != 0:
print('Something went wrong: {} - Error: {}'.format(path, error))
else:
result = json.loads(output)
for path, predictions in result.items():
wikidata_ids = [item['value'] for item in predictions] # list of IDs from wikidata
readable_tags = [item['tag'] for item in predictions] # list of human readable tags
print('For path: "{}" predicted the tags {}'.format(path, ', '.join(readable_tags)))
# result:
# For path: "/path/to/file.mov" predicted the tags: torch, flame, fire |
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das-element-cli.exe --info |
key | description |
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| the identifier for the class from Wikidata |
| meaningful readable tag |
| a list of different words for this class |
Result Format
For each file path you get a list of predictions for tags.
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{'/path/to/file.mov': [{ 'value': 'Q327954', 'tag': 'torch', 'description': 'stick with a flaming end used as a source of light' 'parents': "parents": [{'id': 'Q3196', 'name': 'fire'}, {'id': 'Q235544', 'name': 'flame'}] }]} |
key | description |
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| identifier value - see here for more details |
| human readable text of this category |
| description text for this category |
| the parent tags based on the category hierarchy structure |
Flags for prediction
These are the flags that can be set for the prediction.
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| Shows information of the software. | ||
| Get the top X predictions of tags.
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| File path to another model file (.wit) | ||
| Set the number of frames of a filmstrip for a sequence of images or movie files.
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--debug
debugging mode
Troubleshooting
issue | solution |
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MacOS shows unidentified developer for 'ffprobe' | For MacOS you should add the ffprobe to your trusted applications if you want to use the software. |
Windows startup is quite slow | Unfortunately that is an issue with Window that can not be fixed |
at the |
moment. |