This is the command line tool from das-element for classification of image, sequence and movie files.

You can deploy it on your render farm to use it in a post-render process for tagging of elements

Each version will be shipped with the model inside. Use the --info flag to get the version number


Save the software to your preferred location. That’s all!

On Linux make sure to run this command to make the file executable:

chmod +x das-element-cli_{version}_lin

How To

Simple usage

das-element-cli.exe {file}
# Linux & Mac
das-element-cli /path/to/file.#.exr

# Windows
C:\das-element-cli.exe C:\path\to\file.#.exr

# result:
{"/path/to/file.#.exr": [{"tag": "fire", "description": "rapid oxidation of a material", "value": "Q3196"}]}

Valid file paths are …

  • single file (single image or movie file):

    • /path/to/file.exr

    • /path/to/

  • sequence of files

    • /path/to/sequence.#.exr

    • /path/to/sequence.%04d.exr

  • directory

    • the software will crawl the folder structure to find any media files or sequences

Multiple files

You can pass multiple file paths to the software.

das-element-cli.exe {file1} {file2} {file3}
das-element-cli.exe /path/to/files.#.exr /path/to/another/

# result:
{"/path/to/files.#.exr": [{"tag": "fire", "description": "rapid oxidation of a material", "value": "Q3196"}],
"/path/to/another/": [{"tag": "torch", "description": "stick with a flaming end used as a source of light", "value": "Q327954"}]}

Multiple results

Get the top X predicted categories by using the flag: --top {number}

das-element-cli.exe -top 3 /path/to/

# result:
{"/path/to/": [
      {"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"}

Python Example

Here is an example code snippet that you could use in your python code.

# print the top 3 tag predictions for a given file path

import json
import subprocess

path = '/path/to/'
command = ['./das-element-cli.exe', '--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))
    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/" predicted the tags: torch, flame, fire

Software info

Get information about the current software version and the categories that can be classified.

das-element-cli.exe --info




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.

The result is in JSON format. The default string format is Unicode.
File path gets returned as PosixPath with forwards slash, even for Windows.

{'/path/to/': [{
                          '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'}]




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


These are the flags that can be set




Shows information of the software.
List all categories that this version of the model can classify.

--top {number}

Get the top X predictions of tags.

The first two predictions are probably the most significant ones.


File path to another model file (.wit)
Each version will be shipped with a model file inside the executable


Set the number of frames of a filmstrip for a sequence of images or movie files.
default value: 36

higher value: takes longer, but this might give you more different tags
lower value: faster, but might return less tags

Example: for a sequence of 1000 frames only a number of frames get validated. This helps to speed up the process and still gets you a good result.


debugging mode




MacOS shows unidentified developer for 'ffprobe'

For MacOS you should add the ffprobe to your trusted applications if you want to use the software.

We use the ffmpeg and ffprobe build from MacOS from the following source:

Windows startup is quite slow

Unfortunately that is an issue with Window that can not be fixed in the current moment.