https://github.com/silkodenis/metal-tflite-interpreter

Interpreter designed to run TensorFlow Lite models using Metal for real-time GPU processing.
https://github.com/silkodenis/metal-tflite-interpreter

computer-vision gpu interpreter ios macos metal ml objective-c processing tensorflow tflite

Last synced: about 18 hours ago
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Interpreter designed to run TensorFlow Lite models using Metal for real-time GPU processing.

• Host: GitHub
• URL: https://github.com/silkodenis/metal-tflite-interpreter
• Owner: silkodenis
• License: apache-2.0
• Created: 2024-05-04T10:56:09.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-05-04T11:10:31.000Z (5 months ago)
• Last Synced: 2024-09-24T21:28:41.779Z (about 23 hours ago)
• Topics: computer-vision, gpu, interpreter, ios, macos, metal, ml, objective-c, processing, tensorflow, tflite
• Language: Objective-C
• Homepage:
• Size: 8.79 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Metal Tensorflow Lite Interpreter

`MetalTFLiteInterpreter` is an Objective-C class designed to run TensorFlow Lite models using Metal for accelerated GPU execution.

## Key Features

- **TensorFlow Lite Support:** Allows using models exported in TensorFlow Lite.

- **Hardware Acceleration:** Uses the Metal delegate to execute the model on a GPU.

- **Easy Integration:** Effortlessly binds input and output buffers.

## Requirements

- Xcode 12.5+ (to support Metal)

- TensorFlow Lite C API

- macOS or iOS with Metal support

## Installation

1. **CocoaPods (Recommended):** Add the TensorFlow Lite C API to your project via CocoaPods. In the `Podfile`, add the following configuration:

    ```ruby

    pod 'TensorFlowLiteC', :subspecs => ['Metal']

    ```

    Then, run:

    ```bash

    pod install

    ```

2. **Cloning:** Clone the repository with the code or copy the necessary files to your project.

3. **Dependency Configuration:** Make sure that TensorFlow Lite and TensorFlowLiteCMetal are correctly added to your project.

## Usage

1. **Initialization:**

Create an instance of `MetalTFLiteInterpreter`, specifying the path to your model:

```objc

NSString *modelPath = @"path/to/your/model.tflite";

MetalTFLiteInterpreter *interpreter = [[MetalTFLiteInterpreter alloc] initWithFilePath:modelPath];

```

2. **Buffer Binding:**

Bind an MTLBuffer to an input or output tensor by specifying the index:

```objc

BOOL success = [interpreter bindMetalBuffer:yourMTLBuffer toTensor:INPUT index:0];

if (!success) {

    NSLog(@"Failed to bind Metal buffer.");

}

```

3. **Invoke Model:**

Call invoke to execute the model:

```objc

BOOL invocationSuccess = [interpreter invoke];

if (!invocationSuccess) {

    NSLog(@"Failed to invoke interpreter.");

}

```

4. **Access Results:**

Access results through the output buffer:

```objc

void *outputBuffer = [interpreter bufferPointerForOutputTensor:0];

size_t outputSize = [interpreter bufferSizeForOutputTensor:0];

```

## License

This project is licensed under the [Apache License, Version 2.0](LICENSE).