Fixing similarity index bugs

[brimoor]

Fixes issues ID'd in #168 and #170

mongodb backend

import fiftyone as fo
import fiftyone.brain as fob
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset(
    "quickstart",
    max_samples=10,
    dataset_name="zzz",
    drop_existing_dataset=True,
)

view = dataset[:5]

# optional: precompute embeddings
model = foz.load_zoo_model("clip-vit-base32-torch")
embeddings = view.compute_embeddings(model)
view.set_values("embeddings", embeddings.tolist())

index = fob.compute_similarity(
    view,  # although not recommended, this does work
    model="clip-vit-base32-torch",
    backend="mongodb",
    brain_key="img_sim",
    embeddings="embeddings",
)

print(index.total_index_size)  # 5
print(index.index_size)  # 5

# index is created even though embeddings already existed
assert index._index

# issues warnings for skipped IDs
embeddings, sample_ids, _ = index.compute_embeddings(dataset[3:6])
index.add_to_index(embeddings, sample_ids, overwrite=False, warn_existing=True)

print(index.total_index_size)  # 6
print(index.index_size)  # 5

# skips existing but no warnings
embeddings, sample_ids, _ = index.compute_embeddings(dataset[5:])
index.add_to_index(embeddings, sample_ids, overwrite=False)

print(index.total_index_size)  # 10
print(index.index_size)  # 5

del_view = dataset[4:6]
index.use_view(del_view)

print(index.total_index_size)  # 10
print(index.index_size)  # 2

# works even though some IDs are not in the index's original view
index.remove_from_index(sample_ids=del_view.values("id"))

print(index.total_index_size)  # 8
print(index.index_size)  # 0

index.use_view(dataset)

print(index.total_index_size)  # 8
print(index.index_size)  # 8

assert index.ready

# issues a warning rather than raising an error
puppies = dataset.take(5).sort_by_similarity("puppies")
# The MongoDB backend does not yet support views; the full index will instead be queried, which may result in fewer matches in your current view

sklearn backend

import fiftyone as fo
import fiftyone.brain as fob
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset(
    "quickstart",
    max_samples=10,
    dataset_name="zzz",
    drop_existing_dataset=True,
)

view = dataset[:5]

index = fob.compute_similarity(
    view,  # although not recommended, this does work
    model="clip-vit-base32-torch",
    backend="sklearn",
    brain_key="img_sim",
    embeddings="embeddings",
)

print(index.total_index_size)  # 5
print(index.index_size)  # 5

# issues warnings for skipped IDs
embeddings, sample_ids, _ = index.compute_embeddings(dataset[3:6])
index.add_to_index(embeddings, sample_ids, overwrite=False, warn_existing=True)

print(index.total_index_size)  # 6
print(index.index_size)  # 5

# skips existing but no warnings
embeddings, sample_ids, _ = index.compute_embeddings(dataset[5:])
index.add_to_index(embeddings, sample_ids, overwrite=False)

print(index.total_index_size)  # 10
print(index.index_size)  # 5

del_view = dataset[4:6]
index.use_view(del_view)

print(index.total_index_size)  # 10
print(index.index_size)  # 2

# works even though some IDs are not in the index's original view
index.remove_from_index(sample_ids=del_view.values("id"))

print(index.total_index_size)  # 8
print(index.index_size)  # 0

index.use_view(dataset)

print(index.total_index_size)  # 8
print(index.index_size)  # 8

puppies = dataset.take(5).sort_by_similarity("puppies")

[allenleetc]

@brimoor in #169, issues 1 2 3 are resolved but issue 0 still errors, guessing due to

fiftyone-brain/fiftyone/brain/internal/core/utils.py

Line 483 in 5a9b163

m = jj[-1] - n + 1

Do we want to try to resolve in this PR?

[brimoor]

@allenleetc ah yes, you are correct! Added your fix in bd2fffe 👍

[allenleetc]

LGTM!