Command Line Tool (cli)

This is the command line tool from das-element.

It contains the API (supporting Python 2 & 3) and the 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

Installation

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

API

To learn more about the application programming interface (API) follow this link here.
docu.api.das-element.com

How To machine learning prediction

Simple usage

das-element-cli.exe {file}

# 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"}]}

Valid file paths are …

single file (single image or movie file):
- /path/to/file.exr
- /path/to/file.mov
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 predict {file1} {file2} {file3}

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"}]}

Multiple results

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

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"}
]}

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/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

Software info

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

das-element-cli.exe info

key	description
`id`	the identifier for the class from Wikidata
`human-readable`	meaningful readable tag
`synonym`	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/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
`value`	identifier value - see here for more details
`tag`	human readable text of this category
`description`	description text for this category
`parents`	the parent tags based on the category hierarchy structure

Flags for prediction

These are the flags that can be set for the prediction.

flag	description
`info`	Shows information of the software. List all categories that this version of the model can classify.
`predict --top {number}`	Get the top X predictions of tags. The first two predictions are probably the most significant ones.
`predict --model`	File path to another model file (.wit) Each version will be shipped with a model file inside the executable
`predict --filmstrip_frames`	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.

Troubleshooting

issue	solution
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: https://evermeet.cx/ffmpeg/
Windows startup is quite slow	Unfortunately that is an issue with Window that can not be fixed in the current moment.