--- 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 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).