Iscrowd = torch.zeros(len(labels), dtype=torch.int64)Ĭlass BalancedObjectsSampler(BatchSampler): Labels = torch.randint(1, self.num_classes, (1, num_objects), dtype=torch.int64) Self.image_ids = torch.tensor(image_ids, dtype=torch.int64) PCS_TYPE="GROUNDWATER_FLOW", NUM_TYPE="NEW"įrom import BatchSampler ("radial", dim=2, rad_out=rad, angles=angles) ("radial", dim=2, rad=rad, angles=angles) # generate a radial mesh and geometry ("boundary" polyline) Model = OGS(task_root="pump_test", task_id="model") From ogs5py import OGS, specialrange, generate_time
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