{
	"DETAILS": {
	"NAME": "Doodleverse/Segmentation Zoo/Seg2Map SegFormer models for segmentation of xBD/damaged buildings in RGB 768x768 high-res. images",
    "DATE": "2023-02-06",
    "URL":"10.5281/zenodo.7613175",
    "CITATION":"Buscombe, D. (2022) Doodleverse/Segmentation Zoo/Seg2Map SegFormer models for segmentation of xBD/damaged buildings in RGB 768x768 high-res. images. Zenodo data release 10.5281/zenodo.7613175",
    "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": "Segformer",
      "4": "aerial",
	  "5": "semantic segmentation",
	  "6": "buildings",
	  "7": "Seg2Map",
	  "8": "Machine Learning"
    }
	},  
	"DATASET": {
		"NAME": "XBD (custom subset)", 
		"SOURCE": "https://github.com/DIUx-xView/xView2_baseline",
		"CITATION": "Gupta, R., Hosfelt, R., Sajeev, S., Patel, N., Goodman, B., Doshi, J., Heim, E., Choset, H. and Gaston, M., 2019. xbd: A dataset for assessing building damage from satellite imagery. arXiv preprint arXiv:1911.09296.",
		"NUMBER_LABELED_IMAGES": 4046,
			"CLASSES": {
				"0": "null",
				"1": "building"
			},
			"N_DATA_BANDS": 3,
		"BAND_NAMES": {
			"0": "red",
			"1": "green",
			"2": "blue"    }
		},
	"MODEL": {
		"TARGET_SIZE": [768,768],	
	"NAME": "segformer" 
	},
	"TRAINING": {
    "BATCH_SIZE": 7,
	"PATIENCE": 15,
	"MAX_EPOCHS": 100,
	"VALIDATION_SPLIT": 0.6,
	"RAMPUP_EPOCHS": 20,
	"SUSTAIN_EPOCHS": 5,
	"EXP_DECAY": 0.9,
	"START_LR":  1e-5,
	"MIN_LR": 1e-5,
	"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": false,
	"AUG_LOOPS": 10,
	"AUG_COPIES": 3
	}     
}