{
	"DETAILS": {
	"NAME": "Doodleverse/Segmentation Zoo/Seg2Map Res-UNet models for DeepGlobe/7-class segmentation of RGB 512x512 high-res. images.",
    "DATE": "2023-01-24",
    "URL":"10.5281/zenodo.7576898",
    "CITATION":"Buscombe, D. (2022) Doodleverse/Segmentation Zoo/Seg2Map Res-UNet models for DeepGlobe/7-class segmentation of RGB 512x512 high-res. images. Zenodo data release 10.5281/zenodo.7576898",
    "QUERIES": "https://github.com/Doodleverse/segmentation_zoo/issues",
    "CREDIT":"Daniel Buscombe, @MARDAScience",
    "INTENDED_PURPOSE":"High-resolution (UAV) image segmentation",
    "KEYWORDS": {
      "1": "image segmentation",
      "2": "The Doodleverse",
      "3": "Residual UNet",
      "4": "UAV",
	  "5": "semantic segmentation",
	  "6": "land use / land cover",
	  "7": "Seg2Map",
	  "8": "Machine Learning"
    }
	},  
	"DATASET": {
		"NAME": "Deepglobe 2018: A challenge to parse the earth through satellite images", 
    "SOURCE": "https://www.kaggle.com/datasets/balraj98/deepglobe-land-cover-classification-dataset",
    "CITATION": "Demir, I., Koperski, K., Lindenbaum, D., Pang, G., Huang, J., Basu, S., Hughes, F., Tuia, D. and Raskar, R., 2018.  Deepglobe 2018: A challenge to parse the earth through satellite images. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (pp. 172-181).",
    "NUMBER_LABELED_IMAGES": 1951,
		"CLASSES": {
			"0": "Urban", 
			"1": "Agriculture",
			"2": "Rangeland",
			"3": "Forest",
			"4": "Water",
			"5": "Bare",
			"6": "Unknown"
		},
		"N_DATA_BANDS": 3,
    "BAND_NAMES": {
      "0": "red",
      "1": "green",
      "2": "blue"
    }
	},
	"MODEL": {
	"NAME": "resunet",
    "KERNEL":9,
    "STRIDE":2,
    "FILTERS":6    
	},
	"TRAINING": {
    "BATCH_SIZE": 24,
    "DROPOUT":0.0,
    "DROPOUT_CHANGE_PER_LAYER":0.0,
    "DROPOUT_TYPE":"standard",
    "USE_DROPOUT_ON_UPSAMPLING":false,
    "LOSS":"dice",
	"PATIENCE": 20,
	"MAX_EPOCHS": 100,
	"VALIDATION_SPLIT": 0.6,
	"RAMPUP_EPOCHS": 20,
	"SUSTAIN_EPOCHS": 5.0,
	"EXP_DECAY": 0.9,
	"START_LR":  1e-7,
	"MIN_LR": 1e-7,
	"MAX_LR": 1e-3,
	"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": 3
	}     
}