def merge_near_duplicates(near_duplicate_objects):
if near_duplicate_objects == None or len(near_duplicate_objects) == 0:
return {}
if len(near_duplicate_objects) == 1:
# near_duplicate_objects is a tuple (index, image_dictionary)
return near_duplicate_objects[0][1]
final_dict = {}
first_nd = None
second_nd = None
for index, (simhash_index, image_dictionary) in enumerate(near_duplicate_objects):
if index < len(near_duplicate_objects) - 1:
sim_index1, img_dict1 = near_duplicate_objects[index]
sim_index2, img_dict2 = near_duplicate_objects[index+1]
first_nd, second_nd = NearDuplicate([]), NearDuplicate([])
first_nd.image_dictionary, second_nd.image_dictionary = img_dict1, img_dict2
first_nd.simhash_index, second_nd.simhash_index = sim_index1, sim_index2
final_dict.update(first_nd.merge_near_duplicate_dictionaries(second_nd))
return final_dict
def near_deduplicate_images(file_array, bit_distance, metadata = None):
"""Given a list of file names, return a dictionary of "nearly" deduplicated images"""
nd = NearDuplicate(file_array, k=bit_distance, metadata_dictionary = metadata)
nd.deduplicate_images()
return nd.simhash_index,nd.image_dictionary