GeoSAM-Image-Encoder (Python package)#
This package is part of the Geo-SAM project and is a standalone Python package that does not depend on QGIS. This package allows you to encode remote sensing images into features that can be recognized by Geo-SAM using a remote server, such as Colab, AWS, Azure or your own HPC.
Installation#
Note
Installing GeoSAM-Image-Encoder may directly install the CPU version of PyTorch. Therefore, it is recommended to install the appropriate version of PyTorch before installing GeoSAM-Image-Encoder in your machine. You can install the corresponding version based on the official PyTorch website: https://pytorch.org/get-started/locally/#start-locally
After installing PyTorch, you can install GeoSAM-Image-Encoder via pip.
pip install GeoSAM-Image-Encoder
# or
pip install git+https://github.com/Fanchengyan/GeoSAM-Image-Encoder.git
Usage#
There are two ways to use GeoSAM-Image-Encoder. You can call it in Python or Terminal. We recommend using Python interface directly which will have greater flexibility.
Using Python#
After install GeoSAM-Image-Encoder, you can import it using geosam
import geosam
from geosam import ImageEncoder
check if gpu available
geosam.gpu_available()
Run by specify parameters directly#
If you want to specify the parameters directly, you can run it like this:
checkpoint_path = '/content/sam_vit_l_0b3195.pth'
image_path = '/content/beiluhe_google_img_201211_clip.tif'
feature_dir = './'
## init ImageEncoder
img_encoder = ImageEncoder(checkpoint_path)
## encode image
img_encoder.encode_image(image_path,feature_dir)
Run by parameters from setting.json file#
If you want to using settings.json file which exported from Geo-SAM plugin to provide parameters, you can run it like this:
setting_file = "/content/setting.json"
feature_dir = './'
### parse settings from the setting,json file
settings = geosam.parse_settings_file(setting_file)
### setting file not contains feature_dir, you need add it
settings.update({"feature_dir":feature_dir})
### split settings into init_settings, encode_settings
init_settings, encode_settings = geosam.split_settings(settings)
print(f"settings: {settings}")
print(f"init_settings: {init_settings}")
print(f"encode_settings: {encode_settings}")
Then, you can run image encoding by parameters from setting.json file
img_encoder = ImageEncoder(**init_settings)
img_encoder.encode_image(**encode_settings)
Using Terminal#
check the folder of geosam
print(geosam.folder)
add this folder into environment of your machine. Then run in terminal:
image_encoder.py -i /content/beiluhe_google_img_201211_clip.tif -c /content/sam_vit_l_0b3195.pth -f ./
You can overwrite the settings from file by specify the parameter values. For Example
image_encoder.py -s /content/setting.json -f ./ --stride 256 --value_range "10,255"
check all available parameters:
image_encoder.py -h
This script is for encoding image to SAM features.
=====
Usage
=====
using settings.json:
image_encoder.py -s <settings.json> -f <feature_dir>
or directly using parameters:
image_encoder.py -i <image_path> -c <checkpoint_path> -f <feature_dir>
All Parameters:
-------------------
-s, --settings: Path to the settings json file.
-i, --image_path: Path to the input image.
-c, --checkpoint_path: Path to the SAM checkpoint.
-f, --feature_dir: Path to the output feature directory.
--model_type: one of ["vit_h", "vit_l", "vit_b"] or [0, 1, 2] or None, optional
The type of the SAM model. If None, the model type will be
inferred from the checkpoint path. Default: None.
--bands: list of int, optional .
The bands to be used for encoding. Should not be more than three bands.
If None, the first three bands (if available) will be used. Default: None.
--stride: int, optional
The stride of the sliding window. Default: 512.
--extent: str, optional
The extent of the image to be encoded. Should be in the format of
"minx, miny, maxx, maxy, [crs]". If None, the extent of the input
image will be used. Default: None.
--value_range: tuple of float, optional
The value range of the input image. If None, the value range will be
automatically calculated from the input image. Default: None.
--resolution: float, optional
The resolution of the output feature in the unit of raster crs.
If None, the resolution of the input image will be used. Default: None.
--batch_size: int, optional
The batch size for encoding. Default: 1.
--gpu_id: int, optional
The device id of the GPU to be used. Default: 0.
Colob Example#
You can click on the link below to experience GeoSAM-Image-Encoder in Colab: