title: detectron 2 custom weight file not detecting object
body: <p>I am trying to train a custom model from within the coco dataset just for one class - apple.This is for instance segmentation. I have used some opensource programs to extract the apple images and corresponding json file with the bounding box data etc. The code I have used for training is</p>
  <pre><code>from detectron2.data.datasets import register_coco_instances
  from detectron2.engine import DefaultTrainer
  from detectron2.config import get_cfg
  from detectron2.model_zoo import model_zoo
  import os
  from detectron2.data.datasets import register_coco_instances
  from detectron2.data import MetadataCatalog
  from detectron2.data import DatasetCatalog
  
  
  register_coco_instances(&quot;train&quot;, {}, &quot;segmentation/coco/my_custom_dataset/annotations/coco_annotation.json&quot;, &quot;/home/segmentation/coco/my_custom_dataset/images&quot;)
  register_coco_instances(&quot;val&quot;, {}, &quot;/home/segmentation/coco/my_custom_dataset_validation/annotations/coco_annotation.json&quot;, &quot;/home/segmentation/coco/my_custom_dataset_validation/images&quot;)
  
  my_dataset_metadata = MetadataCatalog.get(&quot;train&quot;)
  print(my_dataset_metadata)
  dataset_dicts = DatasetCatalog.get(&quot;train&quot;)
  print(dataset_dicts)
  
  #register_coco_instances(&quot;my_dataset_validation&quot;, {}, &quot;/home/akshay/segmentation/coco/my_custom_dataset/annotations/coco_annotation.json&quot;, &quot;/home/akshay/segmentation/coco/my_custom_dataset/images&quot;)
  
  cfg = get_cfg()
  cfg.merge_from_file(
      &quot;../detectron2/configs/COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml&quot;
  )
  cfg.DATASETS.TRAIN = (&quot;train&quot;,)
  cfg.DATASETS.TEST = ()  # no metrics implemented for this dataset
  cfg.DATALOADER.NUM_WORKERS = 2
  cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url(&quot;COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml&quot;)  # initialize from model zoo
  cfg.SOLVER.IMS_PER_BATCH = 2
  cfg.SOLVER.BASE_LR = 0.001
  cfg.SOLVER.MAX_ITER = (
      1000
  )  # 300 iterations seems good enough, but you can certainly train longer
  cfg.MODEL.ROI_HEADS.BATCH_SIZE_PER_IMAGE = (
      128
  )  # faster, and good enough for this toy dataset
  cfg.MODEL.ROI_HEADS.NUM_CLASSES = 1  # 3 classes (data, fig, hazelnut)
  
  os.makedirs(cfg.OUTPUT_DIR, exist_ok=True)
  trainer = DefaultTrainer(cfg)
  trainer.resume_or_load(resume=False)
  trainer.train()
  </code></pre>
  <p>I have then copied the corresponding model_final.pth file to the detectron2 folder and then run my inference code which is as follows</p>
  <pre><code>from detectron2.data import DatasetCatalog, MetadataCatalog, build_detection_test_loader
  from detectron2.evaluation import COCOEvaluator, inference_on_dataset
  from detectron2.engine import DefaultTrainer
  from detectron2.evaluation import COCOEvaluator
  import os
  from detectron2 import model_zoo
  from detectron2.engine import DefaultPredictor
  from detectron2.config import get_cfg
  from detectron2.utils.visualizer import Visualizer
  from detectron2.data import MetadataCatalog
  from detectron2.data.catalog import DatasetCatalog
  import cv2
  
  
  cfg = get_cfg()
  cfg.MODEL.WEIGHTS = (&quot;model_final.pth&quot;)
  cfg.DATASETS.TEST = (&quot;validation&quot;, )
  cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.2   # set the testing threshold for this model
  predictor = DefaultPredictor(cfg)
  test_metadata = MetadataCatalog.get(&quot;validation&quot;).set(thing_classes=[&quot;apple&quot;])
  from detectron2.utils.visualizer import ColorMode
  import glob
  im = cv2.imread(&quot;hi.jpg&quot;)
  outputs = predictor(im)
  v = Visualizer(im[:, :, ::-1],
                  metadata=test_metadata, 
                  scale=0.8
                   )
  out = v.draw_instance_predictions(outputs[&quot;instances&quot;].to(&quot;cpu&quot;))
  cv2.imwrite(&quot;evaluate_output.jpg&quot;,out.get_image()[:, :, ::-1])
  </code></pre>
  <p>However, I am not geting the required output with the mask. I am jst getting the same input image back again.
  This is the output of the code</p>
  <pre><code>Skip loading parameter 'proposal_generator.rpn_head.conv.weight' to the model due to incompatible shapes: (256, 256, 3, 3) in the checkpoint but (1024, 1024, 3, 3) in the model! You might want to double check if this is expected.
  Skip loading parameter 'proposal_generator.rpn_head.conv.bias' to the model due to incompatible shapes: (256,) in the checkpoint but (1024,) in the model! You might want to double check if this is expected.
  Skip loading parameter 'proposal_generator.rpn_head.objectness_logits.weight' to the model due to incompatible shapes: (3, 256, 1, 1) in the checkpoint but (15, 1024, 1, 1) in the model! You might want to double check if this is expected.
  Skip loading parameter 'proposal_generator.rpn_head.objectness_logits.bias' to the model due to incompatible shapes: (3,) in the checkpoint but (15,) in the model! You might want to double check if this is expected.
  Skip loading parameter 'proposal_generator.rpn_head.anchor_deltas.weight' to the model due to incompatible shapes: (12, 256, 1, 1) in the checkpoint but (60, 1024, 1, 1) in the model! You might want to double check if this is expected.
  Skip loading parameter 'proposal_generator.rpn_head.anchor_deltas.bias' to the model due to incompatible shapes: (12,) in the checkpoint but (60,) in the model! You might want to double check if this is expected.
  Skip loading parameter 'roi_heads.box_predictor.cls_score.weight' to the model due to incompatible shapes: (2, 1024) in the checkpoint but (81, 2048) in the model! You might want to double check if this is expected.
  Skip loading parameter 'roi_heads.box_predictor.cls_score.bias' to the model due to incompatible shapes: (2,) in the checkpoint but (81,) in the model! You might want to double check if this is expected.
  Skip loading parameter 'roi_heads.box_predictor.bbox_pred.weight' to the model due to incompatible shapes: (4, 1024) in the checkpoint but (320, 2048) in the model! You might want to double check if this is expected.
  Skip loading parameter 'roi_heads.box_predictor.bbox_pred.bias' to the model due to incompatible shapes: (4,) in the checkpoint but (320,) in the model! You might want to double check if this is expected.
  Some model parameters or buffers are not found in the checkpoint:
  backbone.res2.0.conv1.norm.{bias, weight}
  backbone.res2.0.conv1.weight
  backbone.res2.0.conv2.norm.{bias, weight}
  backbone.res2.0.conv2.weight
  backbone.res2.0.conv3.norm.{bias, weight}
  backbone.res2.0.conv3.weight
  backbone.res2.0.shortcut.norm.{bias, weight}
  backbone.res2.0.shortcut.weight
  backbone.res2.1.conv1.norm.{bias, weight}
  backbone.res2.1.conv1.weight
  backbone.res2.1.conv2.norm.{bias, weight}
  backbone.res2.1.conv2.weight
  backbone.res2.1.conv3.norm.{bias, weight}
  backbone.res2.1.conv3.weight
  backbone.res2.2.conv1.norm.{bias, weight}
  backbone.res2.2.conv1.weight
  backbone.res2.2.conv2.norm.{bias, weight}
  backbone.res2.2.conv2.weight
  backbone.res2.2.conv3.norm.{bias, weight}
  backbone.res2.2.conv3.weight
  backbone.res3.0.conv1.norm.{bias, weight}
  backbone.res3.0.conv1.weight
  backbone.res3.0.conv2.norm.{bias, weight}
  backbone.res3.0.conv2.weight
  backbone.res3.0.conv3.norm.{bias, weight}
  backbone.res3.0.conv3.weight
  backbone.res3.0.shortcut.norm.{bias, weight}
  backbone.res3.0.shortcut.weight
  backbone.res3.1.conv1.norm.{bias, weight}
  backbone.res3.1.conv1.weight
  backbone.res3.1.conv2.norm.{bias, weight}
  backbone.res3.1.conv2.weight
  backbone.res3.1.conv3.norm.{bias, weight}
  backbone.res3.1.conv3.weight
  backbone.res3.2.conv1.norm.{bias, weight}
  backbone.res3.2.conv1.weight
  backbone.res3.2.conv2.norm.{bias, weight}
  backbone.res3.2.conv2.weight
  backbone.res3.2.conv3.norm.{bias, weight}
  backbone.res3.2.conv3.weight
  backbone.res3.3.conv1.norm.{bias, weight}
  backbone.res3.3.conv1.weight
  backbone.res3.3.conv2.norm.{bias, weight}
  backbone.res3.3.conv2.weight
  backbone.res3.3.conv3.norm.{bias, weight}
  backbone.res3.3.conv3.weight
  backbone.res4.0.conv1.norm.{bias, weight}
  backbone.res4.0.conv1.weight
  backbone.res4.0.conv2.norm.{bias, weight}
  backbone.res4.0.conv2.weight
  backbone.res4.0.conv3.norm.{bias, weight}
  backbone.res4.0.conv3.weight
  backbone.res4.0.shortcut.norm.{bias, weight}
  backbone.res4.0.shortcut.weight
  backbone.res4.1.conv1.norm.{bias, weight}
  backbone.res4.1.conv1.weight
  backbone.res4.1.conv2.norm.{bias, weight}
  backbone.res4.1.conv2.weight
  backbone.res4.1.conv3.norm.{bias, weight}
  backbone.res4.1.conv3.weight
  backbone.res4.2.conv1.norm.{bias, weight}
  backbone.res4.2.conv1.weight
  backbone.res4.2.conv2.norm.{bias, weight}
  backbone.res4.2.conv2.weight
  backbone.res4.2.conv3.norm.{bias, weight}
  backbone.res4.2.conv3.weight
  backbone.res4.3.conv1.norm.{bias, weight}
  backbone.res4.3.conv1.weight
  backbone.res4.3.conv2.norm.{bias, weight}
  backbone.res4.3.conv2.weight
  backbone.res4.3.conv3.norm.{bias, weight}
  backbone.res4.3.conv3.weight
  backbone.res4.4.conv1.norm.{bias, weight}
  backbone.res4.4.conv1.weight
  backbone.res4.4.conv2.norm.{bias, weight}
  backbone.res4.4.conv2.weight
  backbone.res4.4.conv3.norm.{bias, weight}
  backbone.res4.4.conv3.weight
  backbone.res4.5.conv1.norm.{bias, weight}
  backbone.res4.5.conv1.weight
  backbone.res4.5.conv2.norm.{bias, weight}
  backbone.res4.5.conv2.weight
  backbone.res4.5.conv3.norm.{bias, weight}
  backbone.res4.5.conv3.weight
  backbone.stem.conv1.norm.{bias, weight}
  backbone.stem.conv1.weight
  proposal_generator.rpn_head.anchor_deltas.{bias, weight}
  proposal_generator.rpn_head.conv.{bias, weight}
  proposal_generator.rpn_head.objectness_logits.{bias, weight}
  roi_heads.box_predictor.bbox_pred.{bias, weight}
  roi_heads.box_predictor.cls_score.{bias, weight}
  roi_heads.res5.0.conv1.norm.{bias, weight}
  roi_heads.res5.0.conv1.weight
  roi_heads.res5.0.conv2.norm.{bias, weight}
  roi_heads.res5.0.conv2.weight
  roi_heads.res5.0.conv3.norm.{bias, weight}
  roi_heads.res5.0.conv3.weight
  roi_heads.res5.0.shortcut.norm.{bias, weight}
  roi_heads.res5.0.shortcut.weight
  roi_heads.res5.1.conv1.norm.{bias, weight}
  roi_heads.res5.1.conv1.weight
  roi_heads.res5.1.conv2.norm.{bias, weight}
  roi_heads.res5.1.conv2.weight
  roi_heads.res5.1.conv3.norm.{bias, weight}
  roi_heads.res5.1.conv3.weight
  roi_heads.res5.2.conv1.norm.{bias, weight}
  roi_heads.res5.2.conv1.weight
  roi_heads.res5.2.conv2.norm.{bias, weight}
  roi_heads.res5.2.conv2.weight
  roi_heads.res5.2.conv3.norm.{bias, weight}
  roi_heads.res5.2.conv3.weight
  The checkpoint state_dict contains keys that are not used by the model:
    backbone.fpn_lateral2.{bias, weight}
    backbone.fpn_output2.{bias, weight}
    backbone.fpn_lateral3.{bias, weight}
    backbone.fpn_output3.{bias, weight}
    backbone.fpn_lateral4.{bias, weight}
    backbone.fpn_output4.{bias, weight}
    backbone.fpn_lateral5.{bias, weight}
    backbone.fpn_output5.{bias, weight}
    backbone.bottom_up.stem.conv1.weight
    backbone.bottom_up.stem.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res2.0.shortcut.weight
    backbone.bottom_up.res2.0.shortcut.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res2.0.conv1.weight
    backbone.bottom_up.res2.0.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res2.0.conv2.weight
    backbone.bottom_up.res2.0.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res2.0.conv3.weight
    backbone.bottom_up.res2.0.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res2.1.conv1.weight
    backbone.bottom_up.res2.1.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res2.1.conv2.weight
    backbone.bottom_up.res2.1.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res2.1.conv3.weight
    backbone.bottom_up.res2.1.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res2.2.conv1.weight
    backbone.bottom_up.res2.2.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res2.2.conv2.weight
    backbone.bottom_up.res2.2.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res2.2.conv3.weight
    backbone.bottom_up.res2.2.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res3.0.shortcut.weight
    backbone.bottom_up.res3.0.shortcut.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res3.0.conv1.weight
    backbone.bottom_up.res3.0.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res3.0.conv2.weight
    backbone.bottom_up.res3.0.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res3.0.conv3.weight
    backbone.bottom_up.res3.0.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res3.1.conv1.weight
    backbone.bottom_up.res3.1.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res3.1.conv2.weight
    backbone.bottom_up.res3.1.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res3.1.conv3.weight
    backbone.bottom_up.res3.1.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res3.2.conv1.weight
    backbone.bottom_up.res3.2.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res3.2.conv2.weight
    backbone.bottom_up.res3.2.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res3.2.conv3.weight
    backbone.bottom_up.res3.2.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res3.3.conv1.weight
    backbone.bottom_up.res3.3.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res3.3.conv2.weight
    backbone.bottom_up.res3.3.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res3.3.conv3.weight
    backbone.bottom_up.res3.3.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.0.shortcut.weight
    backbone.bottom_up.res4.0.shortcut.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.0.conv1.weight
    backbone.bottom_up.res4.0.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.0.conv2.weight
    backbone.bottom_up.res4.0.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.0.conv3.weight
    backbone.bottom_up.res4.0.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.1.conv1.weight
    backbone.bottom_up.res4.1.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.1.conv2.weight
    backbone.bottom_up.res4.1.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.1.conv3.weight
    backbone.bottom_up.res4.1.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.2.conv1.weight
    backbone.bottom_up.res4.2.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.2.conv2.weight
    backbone.bottom_up.res4.2.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.2.conv3.weight
    backbone.bottom_up.res4.2.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.3.conv1.weight
    backbone.bottom_up.res4.3.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.3.conv2.weight
    backbone.bottom_up.res4.3.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.3.conv3.weight
    backbone.bottom_up.res4.3.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.4.conv1.weight
    backbone.bottom_up.res4.4.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.4.conv2.weight
    backbone.bottom_up.res4.4.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.4.conv3.weight
    backbone.bottom_up.res4.4.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.5.conv1.weight
    backbone.bottom_up.res4.5.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.5.conv2.weight
    backbone.bottom_up.res4.5.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.5.conv3.weight
    backbone.bottom_up.res4.5.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.6.conv1.weight
    backbone.bottom_up.res4.6.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.6.conv2.weight
    backbone.bottom_up.res4.6.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.6.conv3.weight
    backbone.bottom_up.res4.6.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.7.conv1.weight
    backbone.bottom_up.res4.7.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.7.conv2.weight
    backbone.bottom_up.res4.7.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.7.conv3.weight
    backbone.bottom_up.res4.7.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.8.conv1.weight
    backbone.bottom_up.res4.8.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.8.conv2.weight
    backbone.bottom_up.res4.8.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.8.conv3.weight
    backbone.bottom_up.res4.8.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.9.conv1.weight
    backbone.bottom_up.res4.9.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.9.conv2.weight
    backbone.bottom_up.res4.9.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.9.conv3.weight
    backbone.bottom_up.res4.9.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.10.conv1.weight
    backbone.bottom_up.res4.10.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.10.conv2.weight
    backbone.bottom_up.res4.10.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.10.conv3.weight
    backbone.bottom_up.res4.10.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.11.conv1.weight
    backbone.bottom_up.res4.11.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.11.conv2.weight
    backbone.bottom_up.res4.11.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.11.conv3.weight
    backbone.bottom_up.res4.11.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.12.conv1.weight
    backbone.bottom_up.res4.12.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.12.conv2.weight
    backbone.bottom_up.res4.12.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.12.conv3.weight
    backbone.bottom_up.res4.12.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.13.conv1.weight
    backbone.bottom_up.res4.13.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.13.conv2.weight
    backbone.bottom_up.res4.13.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.13.conv3.weight
    backbone.bottom_up.res4.13.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.14.conv1.weight
    backbone.bottom_up.res4.14.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.14.conv2.weight
    backbone.bottom_up.res4.14.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.14.conv3.weight
    backbone.bottom_up.res4.14.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.15.conv1.weight
    backbone.bottom_up.res4.15.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.15.conv2.weight
    backbone.bottom_up.res4.15.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.15.conv3.weight
    backbone.bottom_up.res4.15.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.16.conv1.weight
    backbone.bottom_up.res4.16.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.16.conv2.weight
    backbone.bottom_up.res4.16.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.16.conv3.weight
    backbone.bottom_up.res4.16.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.17.conv1.weight
    backbone.bottom_up.res4.17.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.17.conv2.weight
    backbone.bottom_up.res4.17.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.17.conv3.weight
    backbone.bottom_up.res4.17.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.18.conv1.weight
    backbone.bottom_up.res4.18.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.18.conv2.weight
    backbone.bottom_up.res4.18.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.18.conv3.weight
    backbone.bottom_up.res4.18.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.19.conv1.weight
    backbone.bottom_up.res4.19.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.19.conv2.weight
    backbone.bottom_up.res4.19.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.19.conv3.weight
    backbone.bottom_up.res4.19.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.20.conv1.weight
    backbone.bottom_up.res4.20.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.20.conv2.weight
    backbone.bottom_up.res4.20.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.20.conv3.weight
    backbone.bottom_up.res4.20.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.21.conv1.weight
    backbone.bottom_up.res4.21.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.21.conv2.weight
    backbone.bottom_up.res4.21.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.21.conv3.weight
    backbone.bottom_up.res4.21.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.22.conv1.weight
    backbone.bottom_up.res4.22.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.22.conv2.weight
    backbone.bottom_up.res4.22.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res4.22.conv3.weight
    backbone.bottom_up.res4.22.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res5.0.shortcut.weight
    backbone.bottom_up.res5.0.shortcut.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res5.0.conv1.weight
    backbone.bottom_up.res5.0.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res5.0.conv2.weight
    backbone.bottom_up.res5.0.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res5.0.conv3.weight
    backbone.bottom_up.res5.0.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res5.1.conv1.weight
    backbone.bottom_up.res5.1.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res5.1.conv2.weight
    backbone.bottom_up.res5.1.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res5.1.conv3.weight
    backbone.bottom_up.res5.1.conv3.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res5.2.conv1.weight
    backbone.bottom_up.res5.2.conv1.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res5.2.conv2.weight
    backbone.bottom_up.res5.2.conv2.norm.{bias, running_mean, running_var, weight}
    backbone.bottom_up.res5.2.conv3.weight
    backbone.bottom_up.res5.2.conv3.norm.{bias, running_mean, running_var, weight}
    roi_heads.box_head.fc1.{bias, weight}
    roi_heads.box_head.fc2.{bias, weight}
    roi_heads.mask_head.mask_fcn1.{bias, weight}
    roi_heads.mask_head.mask_fcn2.{bias, weight}
    roi_heads.mask_head.mask_fcn3.{bias, weight}
    roi_heads.mask_head.mask_fcn4.{bias, weight}
    roi_heads.mask_head.deconv.{bias, weight}
    roi_heads.mask_head.predictor.{bias, weight}
  /home/akshay/segmentation/detectron2/detectron2/modeling/roi_heads/fast_rcnn.py:154: UserWarning: This overload of nonzero is deprecated:
      nonzero()
  Consider using one of the following signatures instead:
      nonzero(*, bool as_tuple) (Triggered internally at  /pytorch/torch/csrc/utils/python_arg_parser.cpp:882.)
    filter_inds = filter_mask.nonzero()
  </code></pre>
  <p>Is my model not trained properly? I am unsure if this is just a warning or there is an actual error. This is just for one custom class.</p>