Open Hezey opened 1 year ago
Who can help me,thanks thanks! I have a log.txt file. I ran the plot_utils.py. It will generate a plot which draw the loss curve and show the mAP.But the plots were empty. This is one line in the log.txt,it seems not have 'map'. {"train_lr": 9.999999999999658e-05, "train_class_error": 57.22874568917938, "train_loss": 7.022901472881381, "train_loss_ce": 0.3194710428784965, "train_loss_bbox": 0.0723700695645175, "train_loss_giou": 0.746639832688087, "train_loss_ce_0": 0.37851527283404396, "train_loss_bbox_0": 0.08132505088743362, "train_loss_giou_0": 0.8278531781138098, "train_loss_ce_1": 0.344907510916609, "train_loss_bbox_1": 0.07426737756104829, "train_loss_giou_1": 0.7597174443249144, "train_loss_ce_2": 0.3258826051627504, "train_loss_bbox_2": 0.07282288214468767, "train_loss_giou_2": 0.7520731556260453, "train_loss_ce_3": 0.311746515574273, "train_loss_bbox_3": 0.07288983175929178, "train_loss_giou_3": 0.753790770667747, "train_loss_ce_4": 0.3132865986696766, "train_loss_bbox_4": 0.07216442618899906, "train_loss_giou_4": 0.7431779136555788, "train_loss_ce_unscaled": 0.3194710428784965, "train_class_error_unscaled": 57.22874568917938, "train_loss_bbox_unscaled": 0.014474013919611443, "train_loss_giou_unscaled": 0.3733199163440435, "train_cardinality_error_unscaled": 2.7939126394052045, "train_loss_ce_0_unscaled": 0.37851527283404396, "train_loss_bbox_0_unscaled": 0.01626501017255314, "train_loss_giou_0_unscaled": 0.4139265890569049, "train_cardinality_error_0_unscaled": 2.4519052044609664, "train_loss_ce_1_unscaled": 0.344907510916609, "train_loss_bbox_1_unscaled": 0.014853475501347111, "train_loss_giou_1_unscaled": 0.3798587221624572, "train_cardinality_error_1_unscaled": 2.7154972118959106, "train_loss_ce_2_unscaled": 0.3258826051627504, "train_loss_bbox_2_unscaled": 0.014564576431317774, "train_loss_giou_2_unscaled": 0.37603657781302263, "train_cardinality_error_2_unscaled": 2.82214219330855, "train_loss_ce_3_unscaled": 0.311746515574273, "train_loss_bbox_3_unscaled": 0.014577966351339032, "train_loss_giou_3_unscaled": 0.3768953853338735, "train_cardinality_error_3_unscaled": 2.8566449814126393, "train_loss_ce_4_unscaled": 0.3132865986696766, "train_loss_bbox_4_unscaled": 0.014432885226634327, "train_loss_giou_4_unscaled": 0.3715889568277894, "train_cardinality_error_4_unscaled": 2.8279507434944238, "test_class_error": 52.52260254927284, "test_loss": 6.66879791974135, "test_loss_ce": 0.32228749480832464, "test_loss_bbox": 0.059777370854852144, "test_loss_giou": 0.6844922150156312, "test_loss_ce_0": 0.38510567725369477, "test_loss_bbox_0": 0.0653020433257559, "test_loss_giou_0": 0.7729063252312544, "test_loss_ce_1": 0.3785227607783332, "test_loss_bbox_1": 0.059598393589396684, "test_loss_giou_1": 0.673128672414996, "test_loss_ce_2": 0.35142186339459897, "test_loss_bbox_2": 0.06057370846336327, "test_loss_giou_2": 0.7068312426260412, "test_loss_ce_3": 0.2984742146386976, "test_loss_bbox_3": 0.06195087088306597, "test_loss_giou_3": 0.72072589225707, "test_loss_ce_4": 0.3151688171640648, "test_loss_bbox_4": 0.05900036001086346, "test_loss_giou_4": 0.693530026587855, "test_loss_ce_unscaled": 0.32228749480832464, "test_class_error_unscaled": 52.52260254927284, "test_loss_bbox_unscaled": 0.011955474161882244, "test_loss_giou_unscaled": 0.3422461075078156, "test_cardinality_error_unscaled": 2.617100371747212, "test_loss_ce_0_unscaled": 0.38510567725369477, "test_loss_bbox_0_unscaled": 0.01306040869025188, "test_loss_giou_0_unscaled": 0.3864531626156272, "test_cardinality_error_0_unscaled": 2.4386617100371746, "test_loss_ce_1_unscaled": 0.3785227607783332, "test_loss_bbox_1_unscaled": 0.011919678703857566, "test_loss_giou_1_unscaled": 0.336564336207498, "test_cardinality_error_1_unscaled": 2.1477695167286246, "test_loss_ce_2_unscaled": 0.35142186339459897, "test_loss_bbox_2_unscaled": 0.012114741692326438, "test_loss_giou_2_unscaled": 0.3534156213130206, "test_cardinality_error_2_unscaled": 2.446096654275093, "test_loss_ce_3_unscaled": 0.2984742146386976, "test_loss_bbox_3_unscaled": 0.012390174164235952, "test_loss_giou_3_unscaled": 0.360362946128535, "test_cardinality_error_3_unscaled": 2.9107806691449816, "test_loss_ce_4_unscaled": 0.3151688171640648, "test_loss_bbox_4_unscaled": 0.011800071982784564, "test_loss_giou_4_unscaled": 0.3467650132939275, "test_cardinality_error_4_unscaled": 2.6942379182156135, "test_coco_eval_bbox": [0.042286592229931017, 0.1255349189119229, 0.016119818543924514, 0.021094165578400922, 0.060808897216835876, 0.21200432267076197, 0.06661826710229846, 0.22895462964793314, 0.37200889886508065, 0.2663834656459775, 0.4671234488938071, 0.579676386913229], "epoch": 12, "n_parameters": 41280266}
Who can help me,thanks thanks! I have a log.txt file. I ran the plot_utils.py. It will generate a plot which draw the loss curve and show the mAP.But the plots were empty. This is one line in the log.txt,it seems not have 'map'. {"train_lr": 9.999999999999658e-05, "train_class_error": 57.22874568917938, "train_loss": 7.022901472881381, "train_loss_ce": 0.3194710428784965, "train_loss_bbox": 0.0723700695645175, "train_loss_giou": 0.746639832688087, "train_loss_ce_0": 0.37851527283404396, "train_loss_bbox_0": 0.08132505088743362, "train_loss_giou_0": 0.8278531781138098, "train_loss_ce_1": 0.344907510916609, "train_loss_bbox_1": 0.07426737756104829, "train_loss_giou_1": 0.7597174443249144, "train_loss_ce_2": 0.3258826051627504, "train_loss_bbox_2": 0.07282288214468767, "train_loss_giou_2": 0.7520731556260453, "train_loss_ce_3": 0.311746515574273, "train_loss_bbox_3": 0.07288983175929178, "train_loss_giou_3": 0.753790770667747, "train_loss_ce_4": 0.3132865986696766, "train_loss_bbox_4": 0.07216442618899906, "train_loss_giou_4": 0.7431779136555788, "train_loss_ce_unscaled": 0.3194710428784965, "train_class_error_unscaled": 57.22874568917938, "train_loss_bbox_unscaled": 0.014474013919611443, "train_loss_giou_unscaled": 0.3733199163440435, "train_cardinality_error_unscaled": 2.7939126394052045, "train_loss_ce_0_unscaled": 0.37851527283404396, "train_loss_bbox_0_unscaled": 0.01626501017255314, "train_loss_giou_0_unscaled": 0.4139265890569049, "train_cardinality_error_0_unscaled": 2.4519052044609664, "train_loss_ce_1_unscaled": 0.344907510916609, "train_loss_bbox_1_unscaled": 0.014853475501347111, "train_loss_giou_1_unscaled": 0.3798587221624572, "train_cardinality_error_1_unscaled": 2.7154972118959106, "train_loss_ce_2_unscaled": 0.3258826051627504, "train_loss_bbox_2_unscaled": 0.014564576431317774, "train_loss_giou_2_unscaled": 0.37603657781302263, "train_cardinality_error_2_unscaled": 2.82214219330855, "train_loss_ce_3_unscaled": 0.311746515574273, "train_loss_bbox_3_unscaled": 0.014577966351339032, "train_loss_giou_3_unscaled": 0.3768953853338735, "train_cardinality_error_3_unscaled": 2.8566449814126393, "train_loss_ce_4_unscaled": 0.3132865986696766, "train_loss_bbox_4_unscaled": 0.014432885226634327, "train_loss_giou_4_unscaled": 0.3715889568277894, "train_cardinality_error_4_unscaled": 2.8279507434944238, "test_class_error": 52.52260254927284, "test_loss": 6.66879791974135, "test_loss_ce": 0.32228749480832464, "test_loss_bbox": 0.059777370854852144, "test_loss_giou": 0.6844922150156312, "test_loss_ce_0": 0.38510567725369477, "test_loss_bbox_0": 0.0653020433257559, "test_loss_giou_0": 0.7729063252312544, "test_loss_ce_1": 0.3785227607783332, "test_loss_bbox_1": 0.059598393589396684, "test_loss_giou_1": 0.673128672414996, "test_loss_ce_2": 0.35142186339459897, "test_loss_bbox_2": 0.06057370846336327, "test_loss_giou_2": 0.7068312426260412, "test_loss_ce_3": 0.2984742146386976, "test_loss_bbox_3": 0.06195087088306597, "test_loss_giou_3": 0.72072589225707, "test_loss_ce_4": 0.3151688171640648, "test_loss_bbox_4": 0.05900036001086346, "test_loss_giou_4": 0.693530026587855, "test_loss_ce_unscaled": 0.32228749480832464, "test_class_error_unscaled": 52.52260254927284, "test_loss_bbox_unscaled": 0.011955474161882244, "test_loss_giou_unscaled": 0.3422461075078156, "test_cardinality_error_unscaled": 2.617100371747212, "test_loss_ce_0_unscaled": 0.38510567725369477, "test_loss_bbox_0_unscaled": 0.01306040869025188, "test_loss_giou_0_unscaled": 0.3864531626156272, "test_cardinality_error_0_unscaled": 2.4386617100371746, "test_loss_ce_1_unscaled": 0.3785227607783332, "test_loss_bbox_1_unscaled": 0.011919678703857566, "test_loss_giou_1_unscaled": 0.336564336207498, "test_cardinality_error_1_unscaled": 2.1477695167286246, "test_loss_ce_2_unscaled": 0.35142186339459897, "test_loss_bbox_2_unscaled": 0.012114741692326438, "test_loss_giou_2_unscaled": 0.3534156213130206, "test_cardinality_error_2_unscaled": 2.446096654275093, "test_loss_ce_3_unscaled": 0.2984742146386976, "test_loss_bbox_3_unscaled": 0.012390174164235952, "test_loss_giou_3_unscaled": 0.360362946128535, "test_cardinality_error_3_unscaled": 2.9107806691449816, "test_loss_ce_4_unscaled": 0.3151688171640648, "test_loss_bbox_4_unscaled": 0.011800071982784564, "test_loss_giou_4_unscaled": 0.3467650132939275, "test_cardinality_error_4_unscaled": 2.6942379182156135, "test_coco_eval_bbox": [0.042286592229931017, 0.1255349189119229, 0.016119818543924514, 0.021094165578400922, 0.060808897216835876, 0.21200432267076197, 0.06661826710229846, 0.22895462964793314, 0.37200889886508065, 0.2663834656459775, 0.4671234488938071, 0.579676386913229], "epoch": 12, "n_parameters": 41280266}