{ "DETAILS": { "NAME": "Doodleverse/Segmentation Zoo/Seg2Map SegFormer models for CoastTrain/8-class segmentation of RGB 768x768 NAIP images", "DATE": "2023-02-14", "URL":"10.5281/zenodo.7641708", "CITATION":"Buscombe, D. (2022) Doodleverse/Segmentation Zoo/Seg2Map SegFormer models for CoastTrain/8-class segmentation of RGB 768x768 NAIP images. Zenodo data release 10.5281/zenodo.7641708", "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": "coastal shoreline", "7": "Seg2Map", "8": "Machine Learning" } }, "DATASET": { "NAME": "Coast Train v1 (custom subset)", "SOURCE": "https://doi.org/10.5281/zenodo.6410157", "CITATION": "Wernette, P.A., Buscombe, D.D., Favela, J., Fitzpatrick, S., and Goldstein E., 2022, Coast Train--Labeled imagery for training and evaluation of data-driven models for image segmentation: U.S. Geological Survey data release, https://doi.org/10.5066/P91NP87I.", "NUMBER_LABELED_IMAGES": 694, "CLASSES": { "0": "null", "1": "water", "2": "whitewater", "3": "sediment", "4": "bare terrain", "5": "other terrain" }, "REMAP_CLASSES": {"0": 0, "1": 1, "2": 2, "3":3, "4":4, "5":4, "6":4,"7":4,"8":4,"9":4,"10":4,"11":4}, "N_DATA_BANDS": 3, "BAND_NAMES": { "0": "red", "1": "green", "2": "blue" } }, "MODEL": { "TARGET_SIZE": [768,768], "NAME": "segformer" }, "TRAINING": { "BATCH_SIZE": 7, "PATIENCE": 10, "MAX_EPOCHS": 100, "VALIDATION_SPLIT": 0.7, "RAMPUP_EPOCHS": 10, "SUSTAIN_EPOCHS": 0, "EXP_DECAY": 0.9, "START_LR": 1e-8, "MIN_LR": 1e-8, "MAX_LR": 1e-5, "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": 5 } }