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https://github.com/lancedb/lancedb.git
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@@ -224,7 +224,6 @@ This embedding function supports ingesting images as both bytes and urls. You ca
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!!! info
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LanceDB supports ingesting images directly from accessible links.
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```python
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db = lancedb.connect(tmp_path)
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@@ -290,4 +289,67 @@ print(actual.label)
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```
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### Imagebind embeddings
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We have support for [imagebind](https://github.com/facebookresearch/ImageBind) model embeddings. You can download our version of the packaged model via - `pip install imagebind-packaged==0.1.2`.
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This function is registered as `imagebind` and supports Audio, Video and Text modalities(extending to Thermal,Depth,IMU data):
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| Parameter | Type | Default Value | Description |
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|---|---|---|---|
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| `name` | `str` | `"imagebind_huge"` | Name of the model. |
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| `device` | `str` | `"cpu"` | The device to run the model on. Can be `"cpu"` or `"gpu"`. |
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| `normalize` | `bool` | `False` | set to `True` to normalize your inputs before model ingestion. |
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Below is an example demonstrating how the API works:
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```python
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db = lancedb.connect(tmp_path)
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registry = EmbeddingFunctionRegistry.get_instance()
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func = registry.get("imagebind").create()
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class ImageBindModel(LanceModel):
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text: str
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image_uri: str = func.SourceField()
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audio_path: str
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vector: Vector(func.ndims()) = func.VectorField()
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# add locally accessible image paths
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text_list=["A dog.", "A car", "A bird"]
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image_paths=[".assets/dog_image.jpg", ".assets/car_image.jpg", ".assets/bird_image.jpg"]
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audio_paths=[".assets/dog_audio.wav", ".assets/car_audio.wav", ".assets/bird_audio.wav"]
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# Load data
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inputs = [
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{"text": a, "audio_path": b, "image_uri": c}
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for a, b, c in zip(text_list, audio_paths, image_paths)
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]
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#create table and add data
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table = db.create_table("img_bind", schema=ImageBindModel)
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table.add(inputs)
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```
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Now, we can search using any modality:
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#### image search
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```python
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query_image = "./assets/dog_image2.jpg" #download an image and enter that path here
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actual = table.search(query_image).limit(1).to_pydantic(ImageBindModel)[0]
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print(actual.text == "dog")
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```
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#### audio search
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```python
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query_audio = "./assets/car_audio2.wav" #download an audio clip and enter path here
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actual = table.search(query_audio).limit(1).to_pydantic(ImageBindModel)[0]
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print(actual.text == "car")
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```
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#### Text search
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You can add any input query and fetch the result as follows:
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```python
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query = "an animal which flies and tweets"
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actual = table.search(query).limit(1).to_pydantic(ImageBindModel)[0]
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print(actual.text == "bird")
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```
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If you have any questions about the embeddings API, supported models, or see a relevant model missing, please raise an issue [on GitHub](https://github.com/lancedb/lancedb/issues).
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569
docs/src/notebooks/multi_modal_video_RAG.ipynb
Normal file
569
docs/src/notebooks/multi_modal_video_RAG.ipynb
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File diff suppressed because one or more lines are too long
@@ -31,7 +31,7 @@ class ImageBindEmbeddings(EmbeddingFunction):
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six different modalities: images, text, audio, depth, thermal, and IMU data
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to download package, run :
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`pip install imagebind@git+https://github.com/raghavdixit99/ImageBind`
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`pip install imagebind-packaged==0.1.2`
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"""
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name: str = "imagebind_huge"
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