Auramask Ensemble Moon

🚀 Keras模型

本模型是基於Keras的圖像到圖像轉換模型，運用了對抗、美學、質量和過濾等技術，可用於處理圖像相關任務，在圖像質量提升等方面具有一定價值。

🚀 快速開始

本模型使用了修改後的vnet進行2D輸入輸出，具體實現可參考此處 。

模型配置

{
    "activation": "ReLU",
    "batch_norm": false,
    "filter_num": [
        128,
        256,
        512,
        1024,
        1024
    ],
    "n_labels": 3,
    "output_activation": "tanh",
    "pool": false,
    "res_num_ini": 1,
    "res_num_max": 3,
    "unpool": false
}

訓練配置

{
    "alpha": 0.0001,
    "batch": 32,
    "epochs": 500,
    "epsilon": 1,
    "input": "(256, 256)",
    "losses": {
        "FEAT_ArcFace": {
            "d": "cosine_similarity",
            "f": "ArcFace",
            "name": "FEAT_ArcFace",
            "reduction": "sum_over_batch_size",
            "threshold": 0.68,
            "weight": 0.05
        },
        "FEAT_VGG-Face": {
            "d": "cosine_similarity",
            "f": "VGG-Face",
            "name": "FEAT_VGG-Face",
            "reduction": "sum_over_batch_size",
            "threshold": 0.68,
            "weight": 0.05
        },
        "IQASSIMC": {
            "lower_better": false,
            "name": "IQASSIMC",
            "reduction": "sum_over_batch_size",
            "weight": 0.5
        },
        "TopIQ": {
            "full_ref": true,
            "lower_better": false,
            "name": "TopIQ",
            "reduction": "sum_over_batch_size",
            "score_range": "~0, ~1",
            "weight": 0.5
        }
    },
    "mixed_precision": true,
    "optimizer": {
        "amsgrad": false,
        "beta_1": 0.9,
        "beta_2": 0.999,
        "clipnorm": null,
        "clipvalue": null,
        "ema_momentum": 0.99,
        "ema_overwrite_frequency": null,
        "epsilon": 1e-07,
        "global_clipnorm": null,
        "gradient_accumulation_steps": null,
        "learning_rate": 9.999999747378752e-05,
        "loss_scale_factor": null,
        "name": "adamw",
        "use_ema": false,
        "weight_decay": 0.004
    },
    "seed": "BIIIIIGSTRETCH",
    "testing": 0.01,
    "training": 0.99
}

📚 詳細文檔

模型信息

可視化示例