# zamba Command Line Interface¶

This section goes into a bit more detail concerning the available options for the zamba command line interface tool. If you are new to zamba and just want to classify some videos as soon as possible, see the [Quickstart] (quickstart.html) guide.

## zamba’s Optional Flags¶

### zamba predict¶

As discussed in the Quickstart, the --help flag provides more information about options for zamba:

\$ zamba predict --help
Usage: zamba predict [OPTIONS] [DATA_PATH] [PRED_PATH]

Identify species in a video.

This is a command line interface for prediction on camera trap footage.
Given a path to camera trap footage, the predict function use a deep
learning model to predict the presence or absense of a variety of species
of common interest to wildlife researchers working with camera trap data.

Options:
--tempdir PATH                 Path to temporary directory. If not
specified, OS temporary directory is used.
--proba_threshold FLOAT        Probability threshold for classification. if
specified binary predictions are returned
with 1 being greater than the threshold, 0
being less than or equal to. If not
specified, probabilities between 0 and 1 are
returned.
--output_class_names           If True, we just return a video and the name
of the most likely class. If False, we return
a probability or indicator (depending on
--proba_threshold) for every possible class.
--model_profile TEXT           Defaults to 'full' which is slow and
accurate; can be 'fast' which is faster and
less accurate.
during processing.
--help                         Show this message and exit.


Let’s go through these one by one.

#### –tempdir PATH¶

This option specifies the PATH to be used for temporary storage during prediction. The model that is shipped with zamba is able to process within memory (assuming reasonably large modern memory of ~16 GB). If a custom model is being used, it may be necessary to point zamba to a mounted drive or some other large-capacity directory. By default this uses the operating system’s temporary directory.

#### –proba_threshold FLOAT¶

For advanced uses, you may want the algorithm to be more or less sensitive to if a species is present. This parameter is a FLOAT number, e.g., 0.64 corresponding to the probability threshold beyond which an animal is considered to be present in the video being analyzed.

By default no threshold is passed, proba_threshold=None. This will return a probability from 0-1 for each species that could occur in each video. If a threshold is passed, then the final prediction value returned for each class is probability >= proba_threshold, so that all class values become 0 (False, the species does not appear) or 1 (True, the species does appear).

#### –output_class_names¶

Setting this option to True yields the most concise output zamba is capable of. The highest species probability in a video is taken to be the only species in that video, and the output returned is simply the video name and the name of the species (or blank) with the highest class probability. See the Quickstart for example usage.

#### –model_profile TEXT¶

There are two versions of the algorithm that ship with zamba. If you pass fast there is a faster algorithm that can be less accurate that is used. If you pass full (the default) a slower algorithm that has 4 sub-models instead of 1 is used.

Because zamba needs to download pretrained weights for the neural network architecture, we make these weights available in different regions. ‘us’ is the default, but if you are not in the US you should use either eu for the European Union or asia for Asia Pacific to make sure that these download as quickly as possible for you.

#### –verbose BOOLEAN¶

This option currently controls only whether or not the command line shows additional information during processing.