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*This model was released on 2022-01-19 and added to Hugging Face Transformers on 2022-03-22 and contributed by [nielsr](https://huggingface.co/nielsr).*

# GLPN

[GLPN](https://huggingface.co/papers/2201.07436) combines SegFormer's hierarchical mix-Transformer with a lightweight decoder for monocular depth estimation. The decoder integrates global context and local connectivity through a selective feature fusion module, enhancing fine detail recovery. This approach achieves state-of-the-art performance on the NYU Depth V2 dataset with improved generalization and robustness, while maintaining lower computational complexity compared to previous decoders.

<hfoptions id="usage">
<hfoption id="Pipeline">

```py
import torch
from transformers import pipeline

pipeline = pipeline(task="depth-estimation", model="vinvino02/glpn-kitti", dtype="auto")
pipeline("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/pipeline-cat-chonk.jpeg")
```

</hfoption>
<hfoption id="AutoModel">

```python
import torch
import requests
import numpy as np
from PIL import Image
from transformers import AutoImageProcessor, AutoModelForDepthEstimation

image_processor = AutoImageProcessor.from_pretrained("vinvino02/glpn-kitti")
model = AutoModelForDepthEstimation.from_pretrained("vinvino02/glpn-kitti", dtype="auto")
url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/pipeline-cat-chonk.jpeg"
image = Image.open(requests.get(url, stream=True).raw)
inputs = image_processor(images=image, return_tensors="pt")

with torch.no_grad():
    outputs = model(**inputs)

post_processed_output = image_processor.post_process_depth_estimation(
    outputs,
    target_sizes=[(image.height, image.width)],
)
predicted_depth = post_processed_output[0]["predicted_depth"]
depth = (predicted_depth - predicted_depth.min()) / (predicted_depth.max() - predicted_depth.min())
depth = depth.detach().cpu().numpy() * 255
Image.fromarray(depth.astype("uint8"))
```

</hfoption>
</hfoptions>

## GLPNConfig

[[autodoc]] GLPNConfig

## GLPNImageProcessor

[[autodoc]] GLPNImageProcessor
    - preprocess

## GLPNModel

[[autodoc]] GLPNModel
    - forward

## GLPNForDepthEstimation

[[autodoc]] GLPNForDepthEstimation
    - forward

