## Motivation
Supports inference for ultra-large-scale remote sensing images.
## Modification
Add RSImageInference.py in demo.
## Use cases
Taking the inference of Vaihingen dataset images using PSPNet as an
example, the following settings are required:
**img**: Specify the path of the image.
**model**: Provide the configuration file for the model.
**checkpoint**: Specify the weight file for the model.
**out**: Set the output path for the results.
**batch_size**: Determine the batch size used during inference.
**win_size**: Specify the width and height(512x512) of the sliding
window.
**stride**: Set the stride(400x400) for sliding the window.
**thread(default: 1)**: Specify the number of threads to be used for
inference.
**Inference device (default: cuda:0)**: Specify the device for inference
(e.g., cuda:0 for CPU).
```shell
python demo/rs_image_inference.py demo/demo.png projects/pp_mobileseg/configs/pp_mobileseg/pp_mobileseg_mobilenetv3_2x16_80k_ade20k_512x512_tiny.py pp_mobileseg_mobilenetv3_2xb16_3rdparty-tiny_512x512-ade20k-a351ebf5.pth --batch-size 8 --device cpu --thread 2
```
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Co-authored-by: xiexinch <xiexinch@outlook.com>
