hypso.classification.WaterDetection.waterdetect.WaterDetect module
- class hypso.classification.WaterDetection.waterdetect.WaterDetect.DWWaterDetect(input_folder, output_folder, shape_file, product, config_file, pekel=None, single_mode=False, *args, **kwargs)
Bases:
object
- calc_awei(bands, save_index=False)
Calculates the AWEI Water Index and adds it to the bands dictionary
- Parameters:
save_index – Inform if the index should be saved as array in the output folder
bands – Bands dictionary with the raster bands
- Returns:
mbwi array
- calc_indexes(image, indexes_list, save_index=False)
- calc_m_nd_index(index_name, band1, band2, band3, band4, save_index=False)
Calculates a modified normalized difference index, adds it to the bands dict and update the mask in loader. Proposed by Dhalton. It uses the maximum of visible and the minimum of Nir/Swir
- Parameters:
save_index – Inidicate if we should save this index to a raster image
index_name – name of index to be used as key in the dictionary
band1 – first band to be used in the normalized difference
band2 – second option for the first band to be used in the normalized difference
band3 – second band to be used in the normalized difference
band4 – second option for the second band to be used in the normalized difference
- Returns:
index array
- calc_mbwi(bands, factor=3, save_index=False)
Calculates the Multi band Water Index and adds it to the bands dictionary
- Parameters:
save_index – Inform if the index should be saved as array in the output folder
bands – Bands dictionary with the raster bands
factor – Factor to multiply the Green band as proposed in the original paper
- Returns:
mbwi array
- calc_nd_index(index_name, band1, band2, save_index=False)
Calculates a normalized difference index, adds it to the bands dict and update the mask in loader
- Parameters:
save_index – Indicate if we should save this index to a raster image
index_name – name of index to be used as key in the dictionary
band1 – first band to be used in the normalized difference
band2 – second band to be used in the normalized difference
- Returns:
index array
- property cluster_matrix
- create_colorbar_pdf(param_name, colormap, min_value, max_value, units='')
- create_rgb_burn_in_pdf(product_name, burn_in_arrays, colors=None, min_value=None, max_value=None, fade=None, opt_relative_path=None, colormap='viridis', uniform_distribution=False, no_data_value=0, valid_value=1, transps=None, bright=5.0)
- create_water_mask(band_combination, pdf_merger_image, glint_processor=None)
- necessary_bands(include_rgb)
Return all the necessary bands, based on the bands used for the graphics and the clustering
- Parameters:
include_rgb – Specifies if RGB bands are necessary for creating composite, for example
- Returns:
All necessary bands in a list
- classmethod run_water_detect(input_folder, output_folder, single_mode, shape_file=None, product='S2_THEIA', config_file=None, pekel=None, post_callback=None, **kwargs)
Main function to launch the water detect algorithm processing. This is the function called from the script.
- Parameters:
input_folder – If single_mode=True, this is the uncompressed image product. If single_mode=False, this is the folder that contains all uncompressed images.
output_folder – Output directory
single_mode – For batch processing (multiple images at a time), single_mode should be set to False
shape_file – Shape file to clip the image (optional).
product – The product to be processed (S2_THEIA, L8_USGS, S2_L1C or S2_S2COR)
config_file – Configuration .ini file. If not specified WaterDetect.ini from current dir and used as default
pekel – Optional path for an occurrence base map like Pekel
post_callback – Used for the WaterQuality add-on package
kwargs – Additional parameters.
- Returns:
DWWaterDetect instance with the generated mask.
- save_graphs(dw_image, pdf_merger_image)
- static save_report(report_name, pdf_merger, folder)
- test_pekel(image, dw_image, pdf_merger_image)
Test Pekel Function
- Parameters:
image –
dw_image –
pdf_merger_image –
- Returns:
- property water_mask