ImageBind - LanceDB

We have support for imagebind model embeddings. You can download our version of the packaged model via - pip install imagebind-packaged==0.1.2. This function is registered as imagebind and supports Audio, Video and Text modalities(extending to Thermal,Depth,IMU data):

Parameter	Type	Default Value	Description
`name`	`str`	`"imagebind_huge"`	Name of the model.
`device`	`str`	`"cpu"`	The device to run the model on. Can be `"cpu"` or `"gpu"`.
`normalize`	`bool`	`False`	set to `True` to normalize your inputs before model ingestion.

Below is an example demonstrating how the API works:

import lancedb
from lancedb.embeddings import get_registry
from lancedb.pydantic import LanceModel, Vector

db = lancedb.connect("/tmp/imagebind-db")
func = get_registry().get("imagebind").create()

class ImageBindModel(LanceModel):
text: str
image_uri: str = func.SourceField()
audio_path: str
vector: Vector(func.ndims()) = func.VectorField()

text_list = ["A dog.", "A car", "A bird"]
image_paths = [
"./assets/dog_image.jpg",
"./assets/car_image.jpg",
"./assets/bird_image.jpg",
]
audio_paths = [
"./assets/dog_audio.wav",
"./assets/car_audio.wav",
"./assets/bird_audio.wav",
]

inputs = [
{"text": a, "audio_path": b, "image_uri": c}
for a, b, c in zip(text_list, audio_paths, image_paths)
]

table = db.create_table("img_bind", schema=ImageBindModel)
table.add(inputs)

Now, we can search using any modality:

image search

query_image = "./assets/dog_image2.jpg"
actual = table.search(query_image).limit(1).to_pydantic(ImageBindModel)[0]
print(actual.text == "dog")

audio search

query_audio = "./assets/car_audio2.wav"
actual = table.search(query_audio).limit(1).to_pydantic(ImageBindModel)[0]
print(actual.text == "car")

Text search

You can add any input query and fetch the result as follows:

query = "an animal which flies and tweets"
actual = table.search(query).limit(1).to_pydantic(ImageBindModel)[0]
print(actual.text == "bird")

If you have any questions about the embeddings API, supported models, or see a relevant model missing, please raise an issue on GitHub.