PySDK 0.10.1

Release Date: 11/2/2023

New Features and Modifications

The HTTP+WebSocket AI server protocol is initially supported for DeGirum AI Server.

Starting from PySDK version 0.10.0, AI server supports two protocols: asio and http. The asio protocol is DeGirum custom socket-based AI server protocol, supported by all previous PySDK versions. The http protocol is a new protocol, which is based on REST HTTP requests and WebSockets streaming. The http protocol allows to use AI server from any programming language, which supports HTTP requests and WebSockets, such as browser-based JavaScript, which does not support native sockets, thus precluding the use of asio protocol.

When you start AI server by executing degirum server start command, you specify the protocol using --protocol parameter, which can be asio, http, or both.

If you omit this parameter, asio protocol will be used by default to provide compatible behavior with previous PySDK verisions.

You select the http protocol by specifying --protocol http.

You may select both protocols by specifying --protocol both. In this case, AI server will listen to both protocols on two consecutive TCP ports: the first port is used for asio protocol, the second port is used for http protocol.

For example: start AI server to serve models from ./my-zoo directory, use asio protocol on port 12345, and use http protocol on port 12346:
```
degirum server start --zoo ./my-zoo --port 12345 --protocol both
```
On a client side, when you connect to AI server with http protocol, you have to prefix AI server hostname with http:// prefix, for example:
```
zoo = dg.connect("http://localhost")
```
To connect to AI server with asio protocol you simply omit the protocol prefix.
Now you may pass arbitrary model properties (properties of degirum.model.Model`` class) as keyword arguments todegirum.zoo_manager.ZooManager.load_model` method. In this case these properties will be assigned to the model object.

For example:
```
model = zoo.load_model(model_name, output_confidence_threshold=0.5, input_pad_method="letterbox")
```
Multi-classifier (or multi-label) classification models are initially supported. The post-processor type string, which is assigned to OutputPostprocessType model parameter, is "MultiLabelClassification". Each inference result dictionary contains the following keys:
- classifier: object class string.
- results: list of class labels and its scores. Scores are optional.
The results list element is a dictionary with the following keys:
- label: class label string.
- score: optional class label probability.
Example:
```
[
    {
        'classifier': 'vehicle color',
        'results': [
            {'label': 'red', 'score': 0.99},
            {'label': 'blue', 'score': 0.01}
        ]
    },
    {
        'classifier': 'vehicle type',
        'results': [
            {'label': 'car', 'score': 0.99},
            {'label': 'truck', 'score': 0.01}   
        ]
    }   
]
```

Bug Fixes

Unclear error message 'NoneType' object has no attribute 'shape' appears when supplying non-existing file for model inference.
Local AI inference of a model with Python post-processor hangs on model destruction due to Python GIL deadlock.
degirum sys-info command re-initializes DeGirum Orca AI accelerator hardware not in interprocess-safe way, disrupting operation of other processes using the same Orca accelerator hardware. The first attempt to fix this bug was in PySDK version 0.9.6, this release finally fixes this bug.