def extract_features_from_images(image_path, file_name):
'''
Changing results path for processing a single day of images
'''
feat_results = []
print "get active region map..."
image, hdu= get_active_region_map(image_path, file_name)
print "save image data to picke file..."
#trans_image_path = "/Users/Alexander/NASA/trans_image_data_test/"
trans_image_path = "/Users/Alexander/NASA/trans_image_data_singleDay/"
save_to_file(image, trans_image_path, file_name)
# Now we want to separate the active regions in the image
# Generate the markers as local maxima of the distance to the background
print "identify active regions in image for file"
labels = get_active_region_labels(image)
# extract features from image
print "extract features from image"
extract_results = extract_features(labels,image, hdu, file_name)
#feat_results.append((file_name, extract_results))
print "saving extracted features to pickle file from image"
#feature_results_path = "/Users/Alexander/NASA/feature_extraction_results_test/"
feature_results_path = "/Users/Alexander/NASA/feature_extraction_results_singleDay/"
#save_to_file((file_name, extract_results), feature_results_path, file_name)
save_to_file([file_name, extract_results], feature_results_path, file_name)
def extract_features_from_images(image_path, file_name, mdi_flux_filter = 120, hmi_flux_filter = 90, kernal_std = 8,num_pixel_in_active_region = 100): ''' Changing results path for processing a single day of images INPUT: image_path, string file_name, string mdi_flux_filter (int) is passed into get_active_region_map hmi_flux_filter (int) is passed into get_active_region_map kernal_std (int) is passed into get_active_region_map ''' print "get active region map..." image, hdu= get_active_region_map(image_path, file_name, mdi_flux_filter , hmi_flux_filter, kernal_std) # print "save image data to picke file..." # save_to_file(image, trans_image_path, file_name) # Now we want to separate the active regions in the image # Generate the markers as local maxima of the distance to the background print "identify active regions in image for file" labels = get_active_region_labels(image) # extract features from image print "extract features from image" extract_results = extract_features(labels, image, hdu, file_name, num_pixel_in_active_region) new_feat_objects = extract_image_features.map_centroids_long_lat(extract_results) return new_feat_objects
