github.com
  
  
    googlelee/TORCHVISION-OBJECT-DETECTION-FINETUNING-TUTORIAL/blob/master/main.py#L91 4



def get_instance_segmentation_model(num_classes):

    # load an instance segmentation model pre-trained on COCO

    model = torchvision.models.detection.maskrcnn_resnet50_fpn(pretrained=True)



    # get the mumber of input features of the classifier

    in_features = model.roi_heads.box_predictor.cls_score.in_features

    # replace the pre-trained head with a new one

    model.roi_heads.box_predictor = FastRCNNPredictor(in_features, num_classes)

    # now get the number of input features for the mask classifier

    in_features_mask = model.roi_heads.box_predictor.conv5_mask.in_channels

    hidden_layer = 256

    # and replace the mask predictor with a new one

    model.roi_heads.mask_predictor = MaskRCNNPredictor(in_features_mask, hidden_layer, num_classes)



    return model





def get_transform(train):

    transforms = []

    # convert the image, a PIL image, into a PyTorch Tensor




  
  
    
    
  
  


line 91 should be mask predictor … not box predictor
look at the tutorial again
 # now get the number of input features for the mask classifier
    in_features_mask = model.roi_heads.mask_predictor.conv5_mask.in_channels
    hidden_layer = 256