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# PyAnnote REST API

## Installation

$ pip install pyannote.server

## Running the server

$ python -m pyannote.server.run

## Using the API

### Parsers

* `/parser/` returns list of supported file formats

$ curl -X GET http://localhost:5000/parser/
["mdtm", "uem"]

* `/parser/<format>` parses `POST`ed file and returns its content in PyAnnote JSON format.


### Evaluation metrics

* `/metric/` returns list of available evaluation metrics

$ curl -X GET http://localhost:5000/metric/
["detection", "diarization", "identification"]


* `/metric/<name>` compares `POST`ed reference and hypothesis annotations in JSON format and returns the corresponding evaluation metric.

**Input format (JSON)**

{
"reference": [
...
],
"hypothesis": [
...
]
}

**Output format (JSON)**

{
METRIC: {
METRIC: value,
COMPONENT_1: value_1,
COMPONENT_2: value_2,
... # components are values from
... # which the final value is computed
},
... # one call to /parser/<metric> may
... # return more than one sub-metrics
}


### Error analysis

* `/error/diff` compares `POST`ed reference and hypothesis and returns their differences.

**Input format (JSON)**

# same format as for metric/<name>
{
"reference": [
...
],
"hypothesis": [
...
]
}


* `/error/regression` compares `POST`ed reference with two hypotheses and returns regressions and/or improvements brought by the second one (`after`) over the first one (`before`).

**Input format (JSON)**

{
"reference": [
...
],
"before": [
...
],
"after": [
...
]
}

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