Inference
Run Trained Model Inference
Inference
Run Trained Model Inference
Run inference of trained model on your data.
POST
/
inference
curl --request POST \
--url https://api.bluesight.ai/inference \
--header 'Content-Type: application/json' \
--data '{
"model": "<string>",
"images": [
{
"gsd": 0.6,
"bands": [
"red",
"green",
"blue"
],
"pixels": [
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application/json
ID of the model to use.
Obtained from a trained_model field of a
TrainingJob object.
List of images to run inference on.
gsd's of each band in images list (should be the same across all bands)
Example:
0.6
Order of bands in pixels array. Used to retrieve means, stds and wavelengths. Pick from 'blue', 'green', 'red', 'rededge1', 'rededge2', 'rededge3', 'nir', 'nir08', 'swir16', 'swir22'.
Example:
["red", "green", "blue"]
3D float array (number of bands, h, w) representing an image.
Example:
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[
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152.0760175700288,
178.035902507884,
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87.09810625573444,
251.1461435281864
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[
17.82431314243659,
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104.24079767576025
],
[
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141.31700632269425
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],
[
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247.54606164678304,
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240.68822048838112,
88.06782534124572,
134.1054530683633
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[
150.36524353550124,
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],
[
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]
]
One of ['sentinel-2-l2a', 'landsat-c2l1', 'landsat-c2l2-sr', 'naip', 'linz', 'sentinel-1-rtc']. Used to retrieve means, stds and wavelengths across bands. If not provided, means and stds will be calculated from list of images, and default wavelengths will be used
Example:
"sentinel-2-l2a"
Bands' wavelengths. Should be provided only if platform is None, because when platform is provided wavelengths will be loaded from config. If platform is None and wavelengths are not provided, default values from sentinel-2-l2a will be used: {'blue': 0.493, 'green': 0.56, 'red': 0.665, 'rededge1': 0.704, 'rededge2': 0.74, 'rededge3': 0.783, 'nir': 0.842, 'nir08': 0.865, 'swir16': 1.61, 'swir22': 2.19}
Example:
[0.665, 0.56, 0.493]
(lat, lon) coordinate of the center of an image. Doesn't have a huge impact on model output.
Example:
[37.77625, -122.43267]
Timestamp when image was taken. Doesn't have a huge impact on model output.
Example:
1714423534
Response
200
application/json
Successful Response
Segmentation model inference: 3D (b, h, w) int label array.
Example:
[
[
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0,
0,
0,
1,
1,
1,
1,
1,
0,
1,
0,
0,
0,
0,
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[
0,
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1,
1,
0,
1,
0,
0,
0,
1,
1,
1,
0,
0,
0,
0
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[
1,
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1,
1,
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[
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0,
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0,
1,
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[
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0,
1,
0,
0,
0,
1
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[
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[
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[
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[
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[
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[
1,
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1,
0,
0,
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1,
1,
1,
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],
[
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[
1,
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1,
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1,
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],
[
1,
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curl --request POST \
--url https://api.bluesight.ai/inference \
--header 'Content-Type: application/json' \
--data '{
"model": "<string>",
"images": [
{
"gsd": 0.6,
"bands": [
"red",
"green",
"blue"
],
"pixels": [
[
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39.53571207596972,
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151.10610568996773,
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92.37225375636102,
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],
[
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],
[
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],
[
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],
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],
[
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[
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],
[
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[
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[
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