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Fix image segmentation example - don't reopen image (#30481)

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Fix image segmentation example - don't repoen image
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amyeroberts 2024-05-01 16:52:57 +01:00 committed by GitHub
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10
docs/source/en/tasks/semantic_segmentation.md
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@ -60,7 +60,7 @@ image
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/segmentation_input.jpg" alt="Segmentation Input"/>
</div>
We will use [nvidia/segformer-b1-finetuned-cityscapes-1024-1024](https://huggingface.co/nvidia/segformer-b1-finetuned-cityscapes-1024-1024).
We will use [nvidia/segformer-b1-finetuned-cityscapes-1024-1024](https://huggingface.co/nvidia/segformer-b1-finetuned-cityscapes-1024-1024).
```python
semantic_segmentation = pipeline("image-segmentation", "nvidia/segformer-b1-finetuned-cityscapes-1024-1024")
@ -68,7 +68,7 @@ results = semantic_segmentation(image)
results
```
The segmentation pipeline output includes a mask for every predicted class.
The segmentation pipeline output includes a mask for every predicted class.
```bash
[{'score': None,
'label': 'road',
@ -111,11 +111,11 @@ results[-1]["mask"]
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/semantic_segmentation_output.png" alt="Semantic Segmentation Output"/>
</div>
In instance segmentation, the goal is not to classify every pixel, but to predict a mask for **every instance of an object** in a given image. It works very similar to object detection, where there is a bounding box for every instance, there's a segmentation mask instead. We will use [facebook/mask2former-swin-large-cityscapes-instance](https://huggingface.co/facebook/mask2former-swin-large-cityscapes-instance) for this.
In instance segmentation, the goal is not to classify every pixel, but to predict a mask for **every instance of an object** in a given image. It works very similar to object detection, where there is a bounding box for every instance, there's a segmentation mask instead. We will use [facebook/mask2former-swin-large-cityscapes-instance](https://huggingface.co/facebook/mask2former-swin-large-cityscapes-instance) for this.
```python
instance_segmentation = pipeline("image-segmentation", "facebook/mask2former-swin-large-cityscapes-instance")
results = instance_segmentation(Image.open(image))
results = instance_segmentation(image)
results
```
@ -148,7 +148,7 @@ Panoptic segmentation combines semantic segmentation and instance segmentation,
```python
panoptic_segmentation = pipeline("image-segmentation", "facebook/mask2former-swin-large-cityscapes-panoptic")
results = panoptic_segmentation(Image.open(image))
results = panoptic_segmentation(image)
results
```
As you can see below, we have more classes. We will later illustrate to see that every pixel is classified into one of the classes.