Describe the bug
A clear and concise description of what the bug is.
The inference do not work for semantic segmentation.
To Reproduce
Steps to reproduce the behavior:
AttributeError: BaseRecord has no attribute segmentation
imgs_array = list([PIL.Image.open(f) for f in image_files[:10]])
infer_ds = Dataset.from_images(imgs_array, valid_tfms, class_map=class_map)
Batch Inference
infer_dl = model_type.infer_dl(infer_ds, batch_size=1, shuffle=False)
preds = model_type.predict_from_dl(model, infer_dl, keep_images=True)
`
I get the following error:
"AttributeError: BaseRecord has no attribute segmentation"
File /projects/icevision/icevision/models/fastai/unet/prediction.py:69, in convert_raw_predictions(batch, raw_preds, records, keep_images)
58 for record, tensor_image, mask_pred, tensor_gt in zip(
59 records, tensor_images, mask_preds, tensor_gts
60 ):
61 pred = BaseRecord(
62 (
63 ImageRecordComponent(),
(...)
66 )
67 )
---> 69 pred.segmentation.set_class_map(record.segmentation.class_map)
70 pred.segmentation.set_mask_array(MaskArray(mask_pred.cpu().numpy()[None]))
72 if tensor_gt is not None:
73
74 # This is used at train time to have mask available for metric computation
File /projects/icevision/icevision/core/components/composite.py:46, in TaskComposite.getattr(self, name)
43 except KeyError:
44 pass
---> 46 raise AttributeError(f"{self.class.name} has no attribute {name}")
AttributeError: BaseRecord has no attribute segmentation
ghamarian
commented
1 year ago
🐛 Bug
Describe the bug A clear and concise description of what the bug is. The inference do not work for semantic segmentation.
To Reproduce Steps to reproduce the behavior:
AttributeError: BaseRecord has no attribute segmentationimgs_array = list([PIL.Image.open(f) for f in image_files[:10]]) infer_ds = Dataset.from_images(imgs_array, valid_tfms, class_map=class_map)Batch Inference
infer_dl = model_type.infer_dl(infer_ds, batch_size=1, shuffle=False) preds = model_type.predict_from_dl(model, infer_dl, keep_images=True) ` I get the following error:
"AttributeError: BaseRecord has no attribute segmentation"
AttributeError Traceback (most recent call last) Cell In [131], line 9 5 # model_type.show_results(model, infer_ds, num_samples=4) 6 7 # Batch Inference 8 infer_dl = model_type.infer_dl(infer_ds, batch_size=4, shuffle=False) ----> 9 preds = model_type.predict_from_dl(model, infer_dl, keep_images=True)
File /projects/icevision/icevision/models/fastai/unet/prediction.py:112, in predict_from_dl(model, infer_dl, show_pbar, keep_images, predict_kwargs) 105 def predict_from_dl( 106 model: nn.Module, 107 infer_dl: DataLoader, (...) 110 predict_kwargs, 111 ): --> 112 return _predict_from_dl( 113 predict_fn=_predict_batch, 114 model=model, 115 infer_dl=infer_dl, 116 show_pbar=show_pbar, 117 keep_images=keep_images, 118 **predict_kwargs, 119 )
File ~/.pyenv/versions/3.10.7/envs/3107/lib/python3.10/site-packages/torch/autograd/grad_mode.py:27, in _DecoratorContextManager.call..decorate_context(*args, kwargs)
24 @functools.wraps(func)
25 def decorate_context(*args, *kwargs):
26 with self.clone():
---> 27 return func(args, kwargs)
File /projects/icevision/icevision/models/utils.py:107, in _predict_from_dl(predict_fn, model, infer_dl, keep_images, show_pbar, predict_kwargs) 105 all_preds = [] 106 for batch, records in pbar(infer_dl, show=show_pbar): --> 107 preds = predict_fn( 108 model=model, 109 batch=batch, 110 records=records, 111 keep_images=keep_images, 112 predict_kwargs, 113 ) 114 all_preds.extend(preds) 116 return all_preds
File ~/.pyenv/versions/3.10.7/envs/3107/lib/python3.10/site-packages/torch/autograd/grad_mode.py:27, in _DecoratorContextManager.call..decorate_context(*args, kwargs)
24 @functools.wraps(func)
25 def decorate_context(*args, *kwargs):
26 with self.clone():
---> 27 return func(args, kwargs)
File /projects/icevision/icevision/models/fastai/unet/prediction.py:25, in _predict_batch(model, batch, records, keep_images, device) 22 images = images.to(device) 24 raw_preds = model(images) ---> 25 preds = convert_raw_predictions( 26 batch=batch, 27 raw_preds=raw_preds, 28 records=records, 29 keep_images=keep_images, 30 ) 32 return preds
File /projects/icevision/icevision/models/fastai/unet/prediction.py:69, in convert_raw_predictions(batch, raw_preds, records, keep_images) 58 for record, tensor_image, mask_pred, tensor_gt in zip( 59 records, tensor_images, mask_preds, tensor_gts 60 ): 61 pred = BaseRecord( 62 ( 63 ImageRecordComponent(), (...) 66 ) 67 ) ---> 69 pred.segmentation.set_class_map(record.segmentation.class_map) 70 pred.segmentation.set_mask_array(MaskArray(mask_pred.cpu().numpy()[None])) 72 if tensor_gt is not None: 73 74 # This is used at train time to have mask available for metric computation
File /projects/icevision/icevision/core/components/composite.py:46, in TaskComposite.getattr(self, name) 43 except KeyError: 44 pass ---> 46 raise AttributeError(f"{self.class.name} has no attribute {name}")
AttributeError: BaseRecord has no attribute segmentation