fairpredictor 0.0.21
pip install fairpredictor==0.0.21
Released:
A package for running predictions using fAIr
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- License: MIT License (MIT)
- Author: Kshitij Raj Sharma
Classifiers
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Project description
fAIr Predictor
Run your fAIr Model Predictions anywhere !
Prerequisites
fAIr Predictor has support for GPU , CPU and tflite based devices
- Install
tensorflow-cpu
ortflite-runtime
according to your requirements
tflite-runtime
support is for having very light deployment in order to run inference &
tensorflow-cpu
might require installation of efficientnet
Example on Collab
# Install
!pip install fairpredictor
# Import
from predictor import predict
# Parameters for your predictions
bbox=[100.56228021333352,13.685230854641182,100.56383321235313,13.685961853747969]
model_path='checkpoint.h5'
zoom_level=20
tms_url='https://tiles.openaerialmap.org/6501a65c0906de000167e64d/0/6501a65c0906de000167e64e/{z}/{x}/{y}'
# Run your prediction
my_predictions=predict(bbox,model_path,zoom_level,tms_url)
print(my_predictions)
## Visualize your predictions
import geopandas as gpd
import matplotlib.pyplot as plt
gdf = gpd.GeoDataFrame.from_features(my_predictions)
gdf.plot()
plt.show()
Works on CPU ! Can work on serverless functions, No other dependencies to run predictions
Use raster2polygon
There is another postprocessing option that supports distance threshold between polygon for merging them , If it is useful for you install raster2polygon by :
pip install raster2polygon
Project details
Unverified details
These details have not been verified by PyPIProject links
Meta
- License: MIT License (MIT)
- Author: Kshitij Raj Sharma
Classifiers
- Development Status
- License
- Programming Language
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