| --- |
| library_name: onnx |
| tags: |
| - efficientnet |
| - image-classification |
| - imagenet |
| - computer-vision |
| - onnx |
| - inference4j |
| license: apache-2.0 |
| pipeline_tag: image-classification |
| --- |
| |
| # EfficientNet-Lite4 — ONNX |
|
|
| ONNX export of [EfficientNet-Lite4](https://huggingface.co/onnx/EfficientNet-Lite4), a lightweight and efficient image classification model optimized for mobile/edge deployment. Trained on ImageNet with 1000-class output. |
|
|
| Mirrored for use with [inference4j](https://github.com/inference4j/inference4j), an inference-only AI library for Java. |
|
|
| ## Original Source |
|
|
| - **Repository:** [ONNX](https://huggingface.co/onnx/EfficientNet-Lite4) |
| - **License:** apache-2.0 |
|
|
| ## Usage with inference4j |
|
|
| ```java |
| try (EfficientNet model = EfficientNet.fromPretrained("models/efficientnet-lite4")) { |
| List<Classification> results = model.classify(Path.of("cat.jpg")); |
| results.forEach(c -> System.out.printf("%s: %.2f%%%n", c.label(), c.score() * 100)); |
| } |
| ``` |
|
|
| ## Model Details |
|
|
| | Property | Value | |
| |----------|-------| |
| | Architecture | EfficientNet-Lite4 (compound-scaled CNN) | |
| | Task | Image classification (ImageNet 1000 classes) | |
| | Input | `[batch, 224, 224, 3]` — RGB, pixel values 0-255 | |
| | Output | `[batch, 1000]` — class probabilities | |
| | ONNX opset | 11 | |
| | Original framework | TensorFlow Lite → ONNX | |
|
|
| ## License |
|
|
| This model is licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). Original model from [ONNX](https://huggingface.co/onnx). |
|
|
