Open kavithar0608 opened 2 months ago
I ran the demo_lazy.py as shown below (on google colab) -
!cd /content/APE && python3 demo/demo_lazy.py \ --config-file configs/LVISCOCOCOCOSTUFF_O365_OID_VGR_SA1B_REFCOCO_GQA_PhraseCut_Flickr30k/ape_deta/ape_deta_vitl_eva02_clip_vlf_lsj1024_cp_16x4_1080k.py \ --input image1.jpg \ --output /content/APE/APE_Output/ \ --confidence-threshold 0.1 \ --text-prompt 'person' \ --with-box \ --with-mask \ --with-sseg \ --opts \ train.init_checkpoint=/content/APE_Models/APE/configs/LVISCOCOCOCOSTUFF_O365_OID_VGR_SA1B_REFCOCO_GQA_PhraseCut_Flickr30k/ape_deta/ape_deta_vitl_eva02_clip_vlf_lsj1024_cp_16x4_1080k_mdl_20230829_162438/model_final.pth \ model.model_language.cache_dir="" \ model.model_vision.select_box_nums_for_evaluation=500 \ model.model_vision.text_feature_bank_reset=True
But the execution abruptly stops after some point (I see a ^C character generated automatically here in the output) - i dont see any output image generated either.
How can i resolve this issue?
Output of the execution given below -
[04/15 17:52:57 detectron2]: Arguments: Namespace(config_file='configs/LVISCOCOCOCOSTUFF_O365_OID_VGR_SA1B_REFCOCO_GQA_PhraseCut_Flickr30k/ape_deta/ape_deta_vitl_eva02_clip_vlf_lsj1024_cp_16x4_1080k.py', webcam=False, video_input=None, input=['image1.jpg'], output='/content/APE/APE_Output/', confidence_threshold=0.1, opts=['train.init_checkpoint=/content/APE_Models/APE/configs/LVISCOCOCOCOSTUFF_O365_OID_VGR_SA1B_REFCOCO_GQA_PhraseCut_Flickr30k/ape_deta/ape_deta_vitl_eva02_clip_vlf_lsj1024_cp_16x4_1080k_mdl_20230829_162438/model_final.pth', 'model.model_language.cache_dir=', 'model.model_vision.select_box_nums_for_evaluation=500', 'model.model_vision.text_feature_bank_reset=True'], text_prompt='person', with_box=True, with_mask=True, with_sseg=True) /usr/local/lib/python3.10/dist-packages/transformers/utils/generic.py:260: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead. torch.utils._pytree._register_pytree_node( apex.normalization.FusedLayerNorm not found, will use pytorch implementations Please 'pip install xformers' apex.normalization.FusedLayerNorm not found, will use pytorch implementations ======== shape of rope freq torch.Size([1024, 64]) ======== ======== shape of rope freq torch.Size([4096, 64]) ======== [04/15 17:53:06 ape.data.detection_utils]: Using builtin metadata 'image_count' for dataset '['lvis_v1_train+coco_panoptic_separated']' [04/15 17:53:06 ape.modeling.ape_deta.deformable_criterion]: fed_loss_cls_weights: torch.Size([1203]) num_classes: 1256 [04/15 17:53:06 ape.modeling.ape_deta.deformable_criterion]: pad fed_loss_cls_weights with type cat and value 0 [04/15 17:53:06 ape.modeling.ape_deta.deformable_criterion]: pad fed_loss_classes with tensor([1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255]) [04/15 17:53:06 ape.modeling.ape_deta.deformable_criterion]: fed_loss_cls_weights: tensor([ 1.0000, 1.0000, 3.1623, 7.3485, 43.8520, 25.0998, 5.5678, 8.3066, 2.6458, 3.3166, 1.0000, 5.4772, 7.0711, 6.7082, 5.2915, 10.6771, 13.8924, 4.5826, 9.5394, 5.5678, 38.3275, 43.8634, 9.3274, 8.7750, 3.3166, 6.8557, 4.5826, 6.8557, 8.3666, 42.8719, 4.3589, 23.0434, 3.3166, 46.6798, 10.6301, 5.0990, 2.2361, 7.4833, 8.5440, 5.6569, 11.3137, 24.9600, 3.4641, 7.2111, 3.3166, 41.0731, 9.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000]) [04/15 17:53:06 ape.modeling.ape_deta.deformable_criterion]: fed_loss_cls_weights: torch.Size([1256]) num_classes: 1256 [04/15 17:53:06 ape.data.detection_utils]: Using builtin metadata 'image_count' for dataset '['openimages_v6_train_bbox_nogroup']' [04/15 17:53:06 ape.modeling.ape_deta.deformable_criterion]: fed_loss_cls_weights: torch.Size([601]) num_classes: 601 [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_id: 0 [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_name: lvis_v1_train+coco_panoptic_separated ...... [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: stuff_classes: None [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_entity: thing [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_id: 4 [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_name: sa1b_6m [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: thing_classes: ['object'] [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: stuff_classes: None [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_entity: thing [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_id: 5 [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_name: refcoco-mixed_group-by-image [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: thing_classes: ['object'] [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: stuff_classes: None [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_entity: thing [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_id: 6 [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_name: gqa_region_train [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: thing_classes: None [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: stuff_classes: None [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_entity: thing [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_id: 7 [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_name: phrasecut_train [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: thing_classes: None [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: stuff_classes: None [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_entity: thing [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_id: 8 [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_name: flickr30k_separateGT_train [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: thing_classes: None [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: stuff_classes: None [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_entity: thing [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_id: 9 [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_name: refcoco-mixed [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: thing_classes: ['object'] [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: stuff_classes: None [04/15 17:53:06 ape.modeling.ape_deta.deformable_detr]: dataset_entity: thing ^C
I think it may be out of memory.
I ran the demo_lazy.py as shown below (on google colab) -
But the execution abruptly stops after some point (I see a ^C character generated automatically here in the output) - i dont see any output image generated either.
How can i resolve this issue?
Output of the execution given below -