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Description
2 occurences of feature_list
should be dataset
instead, also 2048 should be 100.
These are defined earlier in
num_items = 100000
num_dimensions = 100
dataset = np.random.randn(num_items, num_dimensions)
dataset /= np.linalg.norm(dataset, axis=1).reshape(-1, 1)
annoy_training_time = []
annoy_test_time = []
annoy_trees = [
1, 2, 3, 4, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300
]
for num_trees in annoy_trees:
t = AnnoyIndex(2048) # Length of item vector that will be indexed
for i in range(num_images):
feature = feature_list[i]
t.add_item(i, feature)
start_time = time.time()
t.build(num_trees) #50 trees
end_time = time.time()
annoy_training_time.append(end_time - start_time)
start_time = time.time()
indices = t.get_nns_by_vector(feature_list[random_image_index],
5,
include_distances=True)
end_time = time.time()
annoy_test_time.append(end_time - start_time)
print("For number of trees = ", num_trees, ",\tTime to train = ",
annoy_training_time[-1], ",\tTime to test = ", annoy_test_time[-1])
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