{
	"DETAILS": {
	"NAME": "Doodleverse/Segmentation Zoo Res-UNet models for 4-class (water, whitewater, sediment and other) segmentation of Sentinel-2 and Landsat-7/8 7-band (RGB+NIR+SWIR+NDWI+MNDWI) images of coasts.",
    "DATE": "2022-11-24",
    "URL":"10.5281/zenodo.7358284",
    "CITATION":"Buscombe, D. (2022) Doodleverse/Segmentation Zoo Res-UNet models for 4-class (water, whitewater, sediment and other) segmentation of Sentinel-2 and Landsat-7/8 7-band (RGB+NIR+SWIR+NDWI+MNDWI) images of coasts. Zenodo data release 10.5281/zenodo.7358284",
    "QUERIES": "https://github.com/Doodleverse/segmentation_zoo/issues",
    "CREDIT":"Daniel Buscombe, @MARDAScience",
    "INTENDED_PURPOSE":"Landsat-7/8 and Sentinel-2 satellite image segmentation",
    "KEYWORDS": {
      "1": "Landsat",
      "2": "Landsat-8",
      "3": "Landsat-7",
      "4": "Sentinel-2",
	  "5": "water",
	  "6": "whitewater",
	  "7": "sediment",
	  "8": "other"
    }
	},  
	"DATASET": {
		"NAME": "Images and 4-class labels for semantic segmentation of Sentinel-2 and Landsat RGB, NIR, and SWIR satellite images of coasts (water, whitewater, sediment, other)", 
    "SOURCE": "https://doi.org/10.5281/zenodo.7344571",
    "CITATION": "Buscombe, Daniel. (2022). Images and 4-class labels for semantic segmentation of Sentinel-2 and Landsat RGB, NIR, and SWIR satellite images of coasts (water, whitewater, sediment, other) (v1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7344571",
    "NUMBER_LABELED_IMAGES": 579,
		"CLASSES": {
			"0": "water",
			"1": "whitewater",
			"2": "sediment",
			"3": "other"
		},
		"N_DATA_BANDS": 7,
    "BAND_NAMES": {
      "0": "red",
      "1": "green",
      "2": "blue",
	  "3": "NIR",
	  "4:": "SWIR",
	  "5:": "NDWI",
	  "6:": "MNDWI"
    }
	},
	"MODEL": {
	"NAME": "resunet",
    "KERNEL":9,
    "STRIDE":2,
    "FILTERS":6    
	},
	"TRAINING": {
    "BATCH_SIZE": 32,
    "DROPOUT":0.05,
    "DROPOUT_CHANGE_PER_LAYER":0.0,
    "DROPOUT_TYPE":"standard",
    "USE_DROPOUT_ON_UPSAMPLING":false,
    "LOSS":"dice",
	"PATIENCE": 20,
	"MAX_EPOCHS": 100,
	"VALIDATION_SPLIT": 0.7,
	"RAMPUP_EPOCHS": 40,
	"SUSTAIN_EPOCHS": 5.0,
	"EXP_DECAY": 0.9,
	"START_LR":  1e-6,
	"MIN_LR": 1e-6,
	"MAX_LR": 1e-2,
	"MODE": "all"	 
	},
	"AUGMENTATION": {
    "AUGMENTATION_USED": true,
	"AUG_ROT": 5,
	"AUG_ZOOM": 0.05,
	"AUG_WIDTHSHIFT": 0.05,
	"AUG_HEIGHTSHIFT": 0.05,
	"AUG_HFLIP": true,
	"AUG_VFLIP": true,
	"AUG_LOOPS": 10,
	"AUG_COPIES": 5
	}     
}