Open jiyuwangbupt opened 3 days ago
cfg.MODEL.MASK_FORMER.TEST.INSTANCE_ON False [11/27 16:57:19 d2.evaluation.evaluator]: Start inference on 48 batches [11/27 16:57:23 d2.evaluation.evaluator]: Inference done 11/48. Dataloading: 0.0013 s/iter. Inference: 0.3060 s/iter. Eval: 0.0386 s/iter. Total: 0.3459 s/iter. ETA=0:00:12 [11/27 16:57:28 d2.evaluation.evaluator]: Inference done 26/48. Dataloading: 0.0016 s/iter. Inference: 0.3064 s/iter. Eval: 0.0410 s/iter. Total: 0.3491 s/iter. ETA=0:00:07 [11/27 16:57:33 d2.evaluation.evaluator]: Inference done 41/48. Dataloading: 0.0016 s/iter. Inference: 0.3061 s/iter. Eval: 0.0424 s/iter. Total: 0.3502 s/iter. ETA=0:00:02 [11/27 16:57:36 d2.evaluation.evaluator]: Total inference time: 0:00:15.058916 (0.350207 s / iter per device, on 1 devices) [11/27 16:57:36 d2.evaluation.evaluator]: Total inference pure compute time: 0:00:13 (0.304743 s / iter per device, on 1 devices) [11/27 16:57:36 d2.evaluation.sem_seg_evaluation]: OrderedDict([('sem_seg', {'mIoU': 100.0, 'fwIoU': 100.0, 'IoU-fg': 100.0, 'BoundaryIoU-fg': 100.0, 'min(IoU, B-Iou)-fg': 100.0, 'mACC': 100.0, 'pACC': 100.0, 'ACC-fg': 100.0})]) [11/27 16:57:36 d2.engine.defaults]: Evaluation results for roto_val in csv format: [11/27 16:57:36 d2.evaluation.testing]: copypaste: Task: sem_seg [11/27 16:57:36 d2.evaluation.testing]: copypaste: mIoU,fwIoU,mACC,pACC [11/27 16:57:36 d2.evaluation.testing]: copypaste: 100.0000,100.0000,100.0000,100.0000
cfg.MODEL.MASK_FORMER.TEST.INSTANCE_ON False [11/27 16:57:19 d2.evaluation.evaluator]: Start inference on 48 batches [11/27 16:57:23 d2.evaluation.evaluator]: Inference done 11/48. Dataloading: 0.0013 s/iter. Inference: 0.3060 s/iter. Eval: 0.0386 s/iter. Total: 0.3459 s/iter. ETA=0:00:12 [11/27 16:57:28 d2.evaluation.evaluator]: Inference done 26/48. Dataloading: 0.0016 s/iter. Inference: 0.3064 s/iter. Eval: 0.0410 s/iter. Total: 0.3491 s/iter. ETA=0:00:07 [11/27 16:57:33 d2.evaluation.evaluator]: Inference done 41/48. Dataloading: 0.0016 s/iter. Inference: 0.3061 s/iter. Eval: 0.0424 s/iter. Total: 0.3502 s/iter. ETA=0:00:02 [11/27 16:57:36 d2.evaluation.evaluator]: Total inference time: 0:00:15.058916 (0.350207 s / iter per device, on 1 devices) [11/27 16:57:36 d2.evaluation.evaluator]: Total inference pure compute time: 0:00:13 (0.304743 s / iter per device, on 1 devices) [11/27 16:57:36 d2.evaluation.sem_seg_evaluation]: OrderedDict([('sem_seg', {'mIoU': 100.0, 'fwIoU': 100.0, 'IoU-fg': 100.0, 'BoundaryIoU-fg': 100.0, 'min(IoU, B-Iou)-fg': 100.0, 'mACC': 100.0, 'pACC': 100.0, 'ACC-fg': 100.0})]) [11/27 16:57:36 d2.engine.defaults]: Evaluation results for roto_val in csv format: [11/27 16:57:36 d2.evaluation.testing]: copypaste: Task: sem_seg [11/27 16:57:36 d2.evaluation.testing]: copypaste: mIoU,fwIoU,mACC,pACC [11/27 16:57:36 d2.evaluation.testing]: copypaste: 100.0000,100.0000,100.0000,100.0000