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[Feature] remote sensing inference #3131
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xiexinch
merged 14 commits into
open-mmlab:dev-1.x
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Zoulinx:feature/remote-sensing-inference
Aug 31, 2023
Merged
[Feature] remote sensing inference #3131
xiexinch
merged 14 commits into
open-mmlab:dev-1.x
from
Zoulinx:feature/remote-sensing-inference
Aug 31, 2023
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xiexinch
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Feature/remote sensing inference
[Feature] remote sensing inference
Jul 12, 2023
xiexinch
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Jul 12, 2023
xiexinch
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Aug 31, 2023
emily-lin
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Nov 18, 2023
## 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 ``` --------- Co-authored-by: xiexinch <xiexinch@outlook.com>
nahidnazifi87
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Apr 5, 2024
## 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 ``` --------- Co-authored-by: xiexinch <xiexinch@outlook.com>
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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).