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fix docs example, add object_detection to DETR docs (#19377)

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Alara Dirik 2022-10-07 01:02:26 +03:00 committed by GitHub
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2 changed files with 4 additions and 3 deletions
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1
docs/source/en/model_doc/detr.mdx
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@ -171,6 +171,7 @@ mean Average Precision (mAP) and Panoptic Quality (PQ). The latter objects are i
[[autodoc]] DetrFeatureExtractor [[autodoc]] DetrFeatureExtractor
- __call__ - __call__
- pad_and_create_pixel_mask - pad_and_create_pixel_mask
- post_process_object_detection
- post_process_semantic_segmentation - post_process_semantic_segmentation
- post_process_instance_segmentation - post_process_instance_segmentation
- post_process_panoptic_segmentation - post_process_panoptic_segmentation

6
src/transformers/models/detr/modeling_detr.py
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@ -1605,11 +1605,11 @@ class DetrForSegmentation(DetrPreTrainedModel):
>>> # Use the `post_process_panoptic_segmentation` method of `DetrFeatureExtractor` to retrieve post-processed panoptic segmentation maps >>> # Use the `post_process_panoptic_segmentation` method of `DetrFeatureExtractor` to retrieve post-processed panoptic segmentation maps
>>> # Segmentation results are returned as a list of dictionaries >>> # Segmentation results are returned as a list of dictionaries
>>> result = feature_extractor.post_process_panoptic_segmentation(outputs, target_size=[(300, 500)]) >>> result = feature_extractor.post_process_panoptic_segmentation(outputs, target_sizes=[(300, 500)])
>>> # A tensor of shape (height, width) where each value denotes a segment id >>> # A tensor of shape (height, width) where each value denotes a segment id, filled with -1 if no segment is found
>>> panoptic_seg = result[0]["segmentation"] >>> panoptic_seg = result[0]["segmentation"]
>>> # Get mapping of segment ids to semantic class ids >>> # Get prediction score and segment_id to class_id mapping of each segment
>>> panoptic_segments_info = result[0]["segments_info"] >>> panoptic_segments_info = result[0]["segments_info"]
```""" ```"""