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stevewongv / SSIS

Instance Shadow Detection with A Single-Stage Detector [SSIS & SSISv2] (CVPR 2021 Oral & TPAMI 2022)
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An error is reported when running the demo #10

Closed 834810269 closed 1 year ago

834810269 commented 1 year ago

The prediction is {'instances': None}

`[03/22 21:39:26 detectron2]: Arguments: Namespace(config_file='../configs/SSIS/MS_R_101_BiFPN_SSISv2.yaml', webcam=False, video_input=None, input='./samples', output='./res/', confidence_threshold=0.1, opts=[]) WARNING [03/22 21:39:26 d2.config.compat]: Config '../configs/SSIS/MS_R_101_BiFPN_SSISv2.yaml' has no VERSION. Assuming it to be compatible with latest v2. [03/22 21:39:30 d2.checkpoint.detection_checkpoint]: [DetectionCheckpointer] Loading from detectron2://ImageNetPretrained/MSRA/R-101.pkl ... [03/22 21:39:30 d2.checkpoint.c2_model_loading]: Renaming Caffe2 weights ...... [03/22 21:39:30 d2.checkpoint.c2_model_loading]: Following weights matched with submodule backbone.bottom_up.backbone: Names in Model Names in Checkpoint Shapes
res2.0.conv1.* res2_0branch2a{bn_*,w} (64,) (64,) (64,) (64,) (64,64,1,1)
res2.0.conv2.* res2_0branch2b{bn_*,w} (64,) (64,) (64,) (64,) (64,64,3,3)
res2.0.conv3.* res2_0branch2c{bn_*,w} (256,) (256,) (256,) (256,) (256,64,1,1)
res2.0.shortcut.* res2_0branch1{bn_*,w} (256,) (256,) (256,) (256,) (256,64,1,1)
res2.1.conv1.* res2_1branch2a{bn_*,w} (64,) (64,) (64,) (64,) (64,256,1,1)
res2.1.conv2.* res2_1branch2b{bn_*,w} (64,) (64,) (64,) (64,) (64,64,3,3)
res2.1.conv3.* res2_1branch2c{bn_*,w} (256,) (256,) (256,) (256,) (256,64,1,1)
res2.2.conv1.* res2_2branch2a{bn_*,w} (64,) (64,) (64,) (64,) (64,256,1,1)
res2.2.conv2.* res2_2branch2b{bn_*,w} (64,) (64,) (64,) (64,) (64,64,3,3)
res2.2.conv3.* res2_2branch2c{bn_*,w} (256,) (256,) (256,) (256,) (256,64,1,1)
res3.0.conv1.* res3_0branch2a{bn_*,w} (128,) (128,) (128,) (128,) (128,256,1,1)
res3.0.conv2.* res3_0branch2b{bn_*,w} (128,) (128,) (128,) (128,) (128,128,3,3)
res3.0.conv3.* res3_0branch2c{bn_*,w} (512,) (512,) (512,) (512,) (512,128,1,1)
res3.0.shortcut.* res3_0branch1{bn_*,w} (512,) (512,) (512,) (512,) (512,256,1,1)
res3.1.conv1.* res3_1branch2a{bn_*,w} (128,) (128,) (128,) (128,) (128,512,1,1)
res3.1.conv2.* res3_1branch2b{bn_*,w} (128,) (128,) (128,) (128,) (128,128,3,3)
res3.1.conv3.* res3_1branch2c{bn_*,w} (512,) (512,) (512,) (512,) (512,128,1,1)
res3.2.conv1.* res3_2branch2a{bn_*,w} (128,) (128,) (128,) (128,) (128,512,1,1)
res3.2.conv2.* res3_2branch2b{bn_*,w} (128,) (128,) (128,) (128,) (128,128,3,3)
res3.2.conv3.* res3_2branch2c{bn_*,w} (512,) (512,) (512,) (512,) (512,128,1,1)
res3.3.conv1.* res3_3branch2a{bn_*,w} (128,) (128,) (128,) (128,) (128,512,1,1)
res3.3.conv2.* res3_3branch2b{bn_*,w} (128,) (128,) (128,) (128,) (128,128,3,3)
res3.3.conv3.* res3_3branch2c{bn_*,w} (512,) (512,) (512,) (512,) (512,128,1,1)
res4.0.conv1.* res4_0branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,512,1,1)
res4.0.conv2.* res4_0branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.0.conv3.* res4_0branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.0.shortcut.* res4_0branch1{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,512,1,1)
res4.1.conv1.* res4_1branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.1.conv2.* res4_1branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.1.conv3.* res4_1branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.10.conv1.* res4_10branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.10.conv2.* res4_10branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.10.conv3.* res4_10branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.11.conv1.* res4_11branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.11.conv2.* res4_11branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.11.conv3.* res4_11branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.12.conv1.* res4_12branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.12.conv2.* res4_12branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.12.conv3.* res4_12branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.13.conv1.* res4_13branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.13.conv2.* res4_13branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.13.conv3.* res4_13branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.14.conv1.* res4_14branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.14.conv2.* res4_14branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.14.conv3.* res4_14branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.15.conv1.* res4_15branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.15.conv2.* res4_15branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.15.conv3.* res4_15branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.16.conv1.* res4_16branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.16.conv2.* res4_16branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.16.conv3.* res4_16branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.17.conv1.* res4_17branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.17.conv2.* res4_17branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.17.conv3.* res4_17branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.18.conv1.* res4_18branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.18.conv2.* res4_18branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.18.conv3.* res4_18branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.19.conv1.* res4_19branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.19.conv2.* res4_19branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.19.conv3.* res4_19branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.2.conv1.* res4_2branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.2.conv2.* res4_2branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.2.conv3.* res4_2branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.20.conv1.* res4_20branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.20.conv2.* res4_20branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.20.conv3.* res4_20branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.21.conv1.* res4_21branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.21.conv2.* res4_21branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.21.conv3.* res4_21branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.22.conv1.* res4_22branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.22.conv2.* res4_22branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.22.conv3.* res4_22branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.3.conv1.* res4_3branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.3.conv2.* res4_3branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.3.conv3.* res4_3branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.4.conv1.* res4_4branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.4.conv2.* res4_4branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.4.conv3.* res4_4branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.5.conv1.* res4_5branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.5.conv2.* res4_5branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.5.conv3.* res4_5branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.6.conv1.* res4_6branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.6.conv2.* res4_6branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.6.conv3.* res4_6branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.7.conv1.* res4_7branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.7.conv2.* res4_7branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.7.conv3.* res4_7branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.8.conv1.* res4_8branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.8.conv2.* res4_8branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.8.conv3.* res4_8branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res4.9.conv1.* res4_9branch2a{bn_*,w} (256,) (256,) (256,) (256,) (256,1024,1,1)
res4.9.conv2.* res4_9branch2b{bn_*,w} (256,) (256,) (256,) (256,) (256,256,3,3)
res4.9.conv3.* res4_9branch2c{bn_*,w} (1024,) (1024,) (1024,) (1024,) (1024,256,1,1)
res5.0.conv1.* res5_0branch2a{bn_*,w} (512,) (512,) (512,) (512,) (512,1024,1,1)
res5.0.conv2.* res5_0branch2b{bn_*,w} (512,) (512,) (512,) (512,) (512,512,3,3)
res5.0.conv3.* res5_0branch2c{bn_*,w} (2048,) (2048,) (2048,) (2048,) (2048,512,1,1)
res5.0.shortcut.* res5_0branch1{bn_*,w} (2048,) (2048,) (2048,) (2048,) (2048,1024,1,1)
res5.1.conv1.* res5_1branch2a{bn_*,w} (512,) (512,) (512,) (512,) (512,2048,1,1)
res5.1.conv2.* res5_1branch2b{bn_*,w} (512,) (512,) (512,) (512,) (512,512,3,3)
res5.1.conv3.* res5_1branch2c{bn_*,w} (2048,) (2048,) (2048,) (2048,) (2048,512,1,1)
res5.2.conv1.* res5_2branch2a{bn_*,w} (512,) (512,) (512,) (512,) (512,2048,1,1)
res5.2.conv2.* res5_2branch2b{bn_*,w} (512,) (512,) (512,) (512,) (512,512,3,3)
res5.2.conv3.* res5_2branch2c{bn_*,w} (2048,) (2048,) (2048,) (2048,) (2048,512,1,1)
stem.conv1.norm.* res_conv1bn* (64,) (64,) (64,) (64,)
stem.conv1.weight conv1_w (64, 3, 7, 7)

Some model parameters or buffers are not found in the checkpoint: backbone.bottom_up.res6.reduction.norm.{bias, running_mean, running_var, weight} backbone.bottom_up.res6.reduction.weight backbone.repeated_bifpn.0.lateral_0_f0.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.0.lateral_0_f0.{bias, weight} backbone.repeated_bifpn.0.lateral_1_f1.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.0.lateral_1_f1.{bias, weight} backbone.repeated_bifpn.0.lateral_2_f2.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.0.lateral_2_f2.{bias, weight} backbone.repeated_bifpn.0.outputs_f0_0_7.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.0.outputs_f0_0_7.weight backbone.repeated_bifpn.0.outputs_f1_1_6.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.0.outputs_f1_1_6.weight backbone.repeated_bifpn.0.outputs_f1_1_7_8.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.0.outputs_f1_1_7_8.weight backbone.repeated_bifpn.0.outputs_f2_2_5.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.0.outputs_f2_2_5.weight backbone.repeated_bifpn.0.outputs_f2_2_6_9.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.0.outputs_f2_2_6_9.weight backbone.repeated_bifpn.0.outputs_f3_3_4.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.0.outputs_f3_3_4.weight backbone.repeated_bifpn.0.outputs_f3_3_5_10.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.0.outputs_f3_3_5_10.weight backbone.repeated_bifpn.0.outputs_f4_4_11.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.0.outputs_f4_4_11.weight backbone.repeated_bifpn.0.{weights_f0_0_7, weights_f1_1_6, weights_f1_1_7_8, weights_f2_2_5, weights_f2_2_6_9, weights_f3_3_4, weights_f3_3_5_10, weights_f4_4_11} backbone.repeated_bifpn.1.outputs_f0_0_7.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.1.outputs_f0_0_7.weight backbone.repeated_bifpn.1.outputs_f1_1_6.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.1.outputs_f1_1_6.weight backbone.repeated_bifpn.1.outputs_f1_1_7_8.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.1.outputs_f1_1_7_8.weight backbone.repeated_bifpn.1.outputs_f2_2_5.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.1.outputs_f2_2_5.weight backbone.repeated_bifpn.1.outputs_f2_2_6_9.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.1.outputs_f2_2_6_9.weight backbone.repeated_bifpn.1.outputs_f3_3_4.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.1.outputs_f3_3_4.weight backbone.repeated_bifpn.1.outputs_f3_3_5_10.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.1.outputs_f3_3_5_10.weight backbone.repeated_bifpn.1.outputs_f4_4_11.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.1.outputs_f4_4_11.weight backbone.repeated_bifpn.1.{weights_f0_0_7, weights_f1_1_6, weights_f1_1_7_8, weights_f2_2_5, weights_f2_2_6_9, weights_f3_3_4, weights_f3_3_5_10, weights_f4_4_11} backbone.repeated_bifpn.2.outputs_f0_0_7.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.2.outputs_f0_0_7.weight backbone.repeated_bifpn.2.outputs_f1_1_6.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.2.outputs_f1_1_6.weight backbone.repeated_bifpn.2.outputs_f1_1_7_8.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.2.outputs_f1_1_7_8.weight backbone.repeated_bifpn.2.outputs_f2_2_5.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.2.outputs_f2_2_5.weight backbone.repeated_bifpn.2.outputs_f2_2_6_9.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.2.outputs_f2_2_6_9.weight backbone.repeated_bifpn.2.outputs_f3_3_4.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.2.outputs_f3_3_4.weight backbone.repeated_bifpn.2.outputs_f3_3_5_10.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.2.outputs_f3_3_5_10.weight backbone.repeated_bifpn.2.outputs_f4_4_11.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.2.outputs_f4_4_11.weight backbone.repeated_bifpn.2.{weights_f0_0_7, weights_f1_1_6, weights_f1_1_7_8, weights_f2_2_5, weights_f2_2_6_9, weights_f3_3_4, weights_f3_3_5_10, weights_f4_4_11} backbone.repeated_bifpn.3.outputs_f0_0_7.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.3.outputs_f0_0_7.weight backbone.repeated_bifpn.3.outputs_f1_1_6.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.3.outputs_f1_1_6.weight backbone.repeated_bifpn.3.outputs_f1_1_7_8.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.3.outputs_f1_1_7_8.weight backbone.repeated_bifpn.3.outputs_f2_2_5.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.3.outputs_f2_2_5.weight backbone.repeated_bifpn.3.outputs_f2_2_6_9.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.3.outputs_f2_2_6_9.weight backbone.repeated_bifpn.3.outputs_f3_3_4.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.3.outputs_f3_3_4.weight backbone.repeated_bifpn.3.outputs_f3_3_5_10.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.3.outputs_f3_3_5_10.weight backbone.repeated_bifpn.3.outputs_f4_4_11.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.3.outputs_f4_4_11.weight backbone.repeated_bifpn.3.{weights_f0_0_7, weights_f1_1_6, weights_f1_1_7_8, weights_f2_2_5, weights_f2_2_6_9, weights_f3_3_4, weights_f3_3_5_10, weights_f4_4_11} backbone.repeated_bifpn.4.outputs_f0_0_7.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.4.outputs_f0_0_7.weight backbone.repeated_bifpn.4.outputs_f1_1_6.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.4.outputs_f1_1_6.weight backbone.repeated_bifpn.4.outputs_f1_1_7_8.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.4.outputs_f1_1_7_8.weight backbone.repeated_bifpn.4.outputs_f2_2_5.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.4.outputs_f2_2_5.weight backbone.repeated_bifpn.4.outputs_f2_2_6_9.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.4.outputs_f2_2_6_9.weight backbone.repeated_bifpn.4.outputs_f3_3_4.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.4.outputs_f3_3_4.weight backbone.repeated_bifpn.4.outputs_f3_3_5_10.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.4.outputs_f3_3_5_10.weight backbone.repeated_bifpn.4.outputs_f4_4_11.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.4.outputs_f4_4_11.weight backbone.repeated_bifpn.4.{weights_f0_0_7, weights_f1_1_6, weights_f1_1_7_8, weights_f2_2_5, weights_f2_2_6_9, weights_f3_3_4, weights_f3_3_5_10, weights_f4_4_11} backbone.repeated_bifpn.5.outputs_f0_0_7.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.5.outputs_f0_0_7.weight backbone.repeated_bifpn.5.outputs_f1_1_6.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.5.outputs_f1_1_6.weight backbone.repeated_bifpn.5.outputs_f1_1_7_8.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.5.outputs_f1_1_7_8.weight backbone.repeated_bifpn.5.outputs_f2_2_5.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.5.outputs_f2_2_5.weight backbone.repeated_bifpn.5.outputs_f2_2_6_9.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.5.outputs_f2_2_6_9.weight backbone.repeated_bifpn.5.outputs_f3_3_4.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.5.outputs_f3_3_4.weight backbone.repeated_bifpn.5.outputs_f3_3_5_10.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.5.outputs_f3_3_5_10.weight backbone.repeated_bifpn.5.outputs_f4_4_11.norm.{bias, running_mean, running_var, weight} backbone.repeated_bifpn.5.outputs_f4_4_11.weight backbone.repeated_bifpn.5.{weights_f0_0_7, weights_f1_1_6, weights_f1_1_7_8, weights_f2_2_5, weights_f2_2_6_9, weights_f3_3_4, weights_f3_3_5_10, weights_f4_4_11} controller.{bias, weight} controller2.{bias, weight} mask_branch.refine.0.0.weight mask_branch.refine.0.1.{bias, running_mean, running_var, weight} mask_branch.refine.1.0.weight mask_branch.refine.1.1.{bias, running_mean, running_var, weight} mask_branch.refine.2.0.weight mask_branch.refine.2.1.{bias, running_mean, running_var, weight} mask_branch.tower.0.0.weight mask_branch.tower.0.1.{bias, running_mean, running_var, weight} mask_branch.tower.1.0.weight mask_branch.tower.1.1.{bias, running_mean, running_var, weight} mask_branch.tower.2.0.weight mask_branch.tower.2.1.{bias, running_mean, running_var, weight} mask_branch.tower.3.0.weight mask_branch.tower.3.1.{bias, running_mean, running_var, weight} mask_branch.tower.4.{bias, weight} mask_head.maskiou_head.conv.{bias, weight} mask_head.maskiou_head.conv1x1_1.{bias, weight} mask_head.maskiou_head.conv1x1_2.{bias, weight} mask_head.maskiou_head.conv_offset.weight mask_head.maskiou_head.maskiou.{bias, weight} mask_head.maskiou_head.maskiou_deformfcn1.{bias, weight} mask_head.maskiou_head.maskiou_deformfcn2.{bias, weight} mask_head.maskiou_head.maskiou_deformfcn3.{bias, weight} mask_head.maskiou_head.maskiou_deformmask1.weight mask_head.maskiou_head.maskiou_fc1.{bias, weight} mask_head.maskiou_head.maskiou_fc2.{bias, weight} mask_head.{sizes_of_interest, strides} proposal_generator.fcos_head.bbox_pred.{bias, weight} proposal_generator.fcos_head.bbox_tower.0.{bias, weight} proposal_generator.fcos_head.bbox_tower.1.{bias, weight} proposal_generator.fcos_head.bbox_tower.10.{bias, weight} proposal_generator.fcos_head.bbox_tower.3.{bias, weight} proposal_generator.fcos_head.bbox_tower.4.{bias, weight} proposal_generator.fcos_head.bbox_tower.6.{bias, weight} proposal_generator.fcos_head.bbox_tower.7.{bias, weight} proposal_generator.fcos_head.bbox_tower.9.{bias, weight} proposal_generator.fcos_head.cls_logits.{bias, weight} proposal_generator.fcos_head.cls_tower.0.{bias, weight} proposal_generator.fcos_head.cls_tower.1.{bias, weight} proposal_generator.fcos_head.cls_tower.10.{bias, weight} proposal_generator.fcos_head.cls_tower.3.{bias, weight} proposal_generator.fcos_head.cls_tower.4.{bias, weight} proposal_generator.fcos_head.cls_tower.6.{bias, weight} proposal_generator.fcos_head.cls_tower.7.{bias, weight} proposal_generator.fcos_head.cls_tower.9.{bias, weight} proposal_generator.fcos_head.ctrness.{bias, weight} proposal_generator.fcos_head.offset_pred.{bias, weight} proposal_generator.fcos_head.scales.0.scale proposal_generator.fcos_head.scales.1.scale proposal_generator.fcos_head.scales.2.scale proposal_generator.fcos_head.scales.3.scale proposal_generator.fcos_head.scales.4.scale The checkpoint state_dict contains keys that are not used by the model: fc1000.{bias, weight} 0%| | 0/4 [00:00<?, ?it/s]/home/xyw/miniconda3/envs/pytorch111/lib/python3.9/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /opt/conda/conda-bld/pytorch_1646756402876/work/aten/src/ATen/native/TensorShape.cpp:2228.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] {'instances': None} instances 0%| | 0/4 [00:01<?, ?it/s] Traceback (most recent call last): File "/raid/xiayuwei/code/SSIS/demo/demo.py", line 93, in instances, visualized_output = demo.run_on_image(img) File "/raid/xiayuwei/code/SSIS/demo/predictor.py", line 83, in run_on_image instances.pred_masks = instances.pred_masks.numpy() AttributeError: 'NoneType' object has no attribute 'pred_masks'`

stevewongv commented 1 year ago

Currently, you load the backbone weight to the network, so it cannot output correct results. You need to download the weight first.

834810269 commented 1 year ago

Currently, you load the backbone weight to the network, so it cannot output correct results. You need to download the weight first.

Thanks for your reply！Where should I load the weights in demo.py. I have downloaded the pre-trained model according to the readme and put it in the specified path.

stevewongv commented 1 year ago

Currently, you load the backbone weight to the network, so it cannot output correct results. You need to download the weight first.

Thanks for your reply！Where should I load the weights in demo.py. I have downloaded the pre-trained model according to the readme and put it in the specified path.

See the yaml file: configs/SSIS/MS_R_101_BiFPN_SSISv2_demo.yaml

834810269 commented 1 year ago

Currently, you load the backbone weight to the network, so it cannot output correct results. You need to download the weight first.

Thanks for your reply！Where should I load the weights in demo.py. I have downloaded the pre-trained model according to the readme and put it in the specified path.

See the yaml file: configs/SSIS/MS_R_101_BiFPN_SSISv2_demo.yaml

Thanks a lot！