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Update old existing feature extractor references (#24552)

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* Update old existing feature extractor references

* Typo

* Apply suggestions from code review

* Apply suggestions from code review

* Apply suggestions from code review

* Address comments from review - update 'feature extractor'
Co-authored by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
This commit is contained in:
amyeroberts
2023-06-29 10:17:36 +01:00
committed by GitHub
parent 10c2ac7bc6
commit ae454f41d4
138 changed files with 762 additions and 743 deletions
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docs/source/de/preprocessing.md
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@@ -354,12 +354,12 @@ Als Nächstes sehen Sie sich das Bild mit dem Merkmal 🤗 Datensätze [Bild] (h
### Merkmalsextraktor
Laden Sie den Merkmalsextraktor mit [`AutoFeatureExtractor.from_pretrained`]:
Laden Sie den Merkmalsextraktor mit [`AutoImageProcessor.from_pretrained`]:
```py
>>> from transformers import AutoFeatureExtractor
>>> from transformers import AutoImageProcessor
>>> feature_extractor = AutoFeatureExtractor.from_pretrained("google/vit-base-patch16-224")
>>> image_processor = AutoImageProcessor.from_pretrained("google/vit-base-patch16-224")
```
### Datenerweiterung
@@ -371,9 +371,9 @@ Bei Bildverarbeitungsaufgaben ist es üblich, den Bildern als Teil der Vorverarb
```py
>>> from torchvision.transforms import Compose, Normalize, RandomResizedCrop, ColorJitter, ToTensor
>>> normalize = Normalize(mean=feature_extractor.image_mean, std=feature_extractor.image_std)
>>> normalize = Normalize(mean=image_processor.image_mean, std=image_processor.image_std)
>>> _transforms = Compose(
... [RandomResizedCrop(feature_extractor.size), ColorJitter(brightness=0.5, hue=0.5), ToTensor(), normalize]
... [RandomResizedCrop(image_processor.size["height"]), ColorJitter(brightness=0.5, hue=0.5), ToTensor(), normalize]
... )
```