Aiservermodel

AIServerModel

A comprehensive class for handling AI model inference using an AIServer over WebSocket. Designed to provide a streamlined interface for sending data to the server for inference, receiving processed results, and displaying or further processing these results as needed.

Features:

• WebSocket Communication: Handles the full lifecycle of a WebSocket connection for real-time data streaming.
  
• Preprocessing & Postprocessing: Integrates with PreProcess and PostProcess classes to prepare data for the model and visualize results.
  
• Queue Management: Uses AsyncQueue instances to manage inbound and outbound data flow.
  
• Concurrency Control: Ensures thread-safe operations through mutex usage.
  
• Dynamic Configuration: Allows runtime modification of model and overlay parameters.
  
• Callback Integration: Supports custom callback functions for handling results outside the class.
  

Kind: global class

• AIServerModel
  • new AIServerModel(options, [additionalParams])
  • .predict(imageFile, [info], [bypassPreprocessing]) ⇒ Promise.<Object>
  • .predict_batch(data_source, [bypassPreprocessing])
  • .displayResultToCanvas(combinedResult, outputCanvasName, [justResults])
  • .setModelParameter(key, value) ⇒ Promise.<void>
  • .getModelParameter(key) ⇒ *
  • .resetTimeStats()
  • .getTimeStats() ⇒ string
  • .modelInfo() ⇒ Object
  • .labelDictionary() ⇒ Object
  • .processImageFile(combinedResult) ⇒ Promise.<Blob>
  • .cleanup()

new AIServerModel(options, [additionalParams])

Do not call the constructor directly. Use the loadModel method of an AIServerZoo instance to create an AIServerModel.

Param	Type	Default	Description
options	Object		Options for initializing the model.
options.modelName	string		The name of the model to load.
options.serverUrl	string		The URL of the server.
options.modelParams	Object		The default model parameters.
[options.max_q_len]	number	10	Maximum queue length.
[options.callback]	function		Callback function for handling results.
[options.labels]	Object		Label dictionary for the model.
[additionalParams]	Object		Additional parameters for the model (e.g., measureTime, deviceType).

Example (Usage:)

- Create an instance with the required model details and server URL.
let model = zoo.loadModel('some_model_name', {} );
- Use the `predict` method for inference with individual data items or `predict_batch` for multiple items.
let result = await model.predict(someImage);
for await (let result of model.predict_batch(someDataGeneratorFn)) { ... }
- Access processed results directly or set up a callback function for custom result handling.
- You can display results to a canvas to view drawn overlays.
await model.displayResultToCanvas(result, canvas);

aiServerModel.predict(imageFile, [info], [bypassPreprocessing]) ⇒ Promise.<Object>

Predicts the result for a given image.

Kind: instance method of AIServerModel
Returns: Promise.<Object> -

The prediction result.

Param	Type	Default	Description
imageFile	Blob | File | string | HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | ArrayBuffer | TypedArray | ImageBitmap
[info]	string	"performance.now()"	Unique frame information provided by user (such as frame num). Used for matching results back to input images within callback.
[bypassPreprocessing]	boolean	false	Whether to bypass preprocessing. Used to send Blob data directly to the socket without any preprocessing.

Example

If callback is provided:
The WebSocket onmessage will invoke the callback directly when the result arrives.

Example

If callback is not provided:
The function waits for the resultQ to get a result, then returns it.
let result = await model.predict(someImage);

aiServerModel.predict_batch(data_source, [bypassPreprocessing])

Predicts results for a batch of data. Will yield results if a callback is not provided.

Kind: instance method of AIServerModel

Param	Type	Default	Description
data_source	AsyncIterable | ReadableStream		Either an async iterable or a ReadableStream.
[bypassPreprocessing]	boolean	false	Whether to bypass preprocessing.

Example

The function asynchronously processes results. If a callback is not provided, it will yield results.
for await (let result of model.predict_batch(data_source)) { console.log(result); }

aiServerModel.displayResultToCanvas(combinedResult, outputCanvasName, [justResults])

Overlay the result onto the image frame and display it on the canvas.

Kind: instance method of AIServerModel

Param	Type	Default	Description
combinedResult	Object		The result object combined with the original image frame. This is directly received from predict or predict_batch
outputCanvasName	string | HTMLCanvasElement | OffscreenCanvas		The canvas to draw the image onto. Either the canvas element or the ID of the canvas element.
[justResults]	boolean	false	Whether to show only the result overlay without the image frame.

aiServerModel.setModelParameter(key, value) ⇒ Promise.<void>

Updates a single parameter in the model's parameters. Use this function to set arbitrary parameters in the model's configuration. Get a list of available parameters using model.modelInfo()

Kind: instance method of AIServerModel

Param	Type	Description
key	string	The name of the parameter to set.
value	*	The new value for the parameter.

aiServerModel.getModelParameter(key) ⇒ *

Retrieves a model parameter from the local copy of the model parameters JSON.

Kind: instance method of AIServerModel
Returns: * -

The value of the parameter.

Param	Type	Description
key	string	The key of the parameter to retrieve.

Example

let threshold = model.getModelParameter('OutputConfThreshold');

aiServerModel.resetTimeStats()

Resets the internal performance statistics dictionary.

Kind: instance method of AIServerModel

aiServerModel.getTimeStats() ⇒ string

Returns the internal performance statistics as a string.

Kind: instance method of AIServerModel
Returns: string -

A string representation of the performance statistics.

aiServerModel.modelInfo() ⇒ Object

Returns a read-only copy of the model parameters.

Kind: instance method of AIServerModel
Returns: Object -

The model parameters.

aiServerModel.labelDictionary() ⇒ Object

Returns the label dictionary for this AIServerModel instance.

Kind: instance method of AIServerModel
Returns: Object -

The label dictionary.

aiServerModel.processImageFile(combinedResult) ⇒ Promise.<Blob>

Processes the original image and draws the results on it, return png image with overlayed results.

Kind: instance method of AIServerModel
Returns: Promise.<Blob> -

The processed image file as a Blob of a PNG image.

Param	Type	Description
combinedResult	Object	The result object combined with the original image frame.

aiServerModel.cleanup()

Cleans up resources and closes the server connection. Does so by following a destructor-like pattern which is manually called by the user.
Call this whenever switching models or when the model instance is no longer needed!

Kind: instance method of AIServerModel