rs3gw 0.2.1

High-Performance AI/HPC Object Storage Gateway powered by scirs2-io
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{
  "id": "efficientnet-b0-preprocessing",
  "name": "EfficientNet-B0 Preprocessing",
  "version": "1.0.0",
  "description": "EfficientNet-B0 preprocessing pipeline for efficient image classification",
  "steps": [
    {
      "id": "resize",
      "step_type": "image_resize",
      "config": {
        "width": 224,
        "height": 224,
        "mode": "fit",
        "filter": "bicubic"
      },
      "cache_results": false,
      "description": "Resize to 224x224 with bicubic interpolation (EfficientNet-B0 standard)"
    },
    {
      "id": "normalize",
      "step_type": "image_normalization",
      "config": {
        "mean": [0.485, 0.456, 0.406],
        "std": [0.229, 0.224, 0.225],
        "normalize_range": true
      },
      "cache_results": true,
      "description": "Apply ImageNet normalization (EfficientNet uses standard ImageNet stats)"
    }
  ],
  "metadata": {
    "created_at": "2025-12-31T00:00:00Z",
    "author": "rs3gw-team",
    "target_model": "EfficientNet-B0 through B7 (scaled architectures)",
    "use_case": "Efficient image classification, Mobile deployment, Edge computing",
    "framework": "PyTorch/TensorFlow/HuggingFace",
    "reference": "https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet",
    "notes": "EfficientNet scales: B0=224, B1=240, B2=260, B3=300, B4=380, B5=456, B6=528, B7=600 (adjust width/height accordingly)"
  }
}