Package vision_models (1.48.0)

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API documentation for vision_models package.

Classes

Image

Image.

ImageCaptioningModel

Generates captions from image.

Examples::

model = ImageCaptioningModel.from_pretrained("imagetext@001")
image = Image.load_from_file("image.png")
captions = model.get_captions(
    image=image,
    # Optional:
    number_of_results=1,
    language="en",
)

ImageQnAModel

Answers questions about an image.

Examples::

model = ImageQnAModel.from_pretrained("imagetext@001")
image = Image.load_from_file("image.png")
answers = model.ask_question(
    image=image,
    question="What color is the car in this image?",
    # Optional:
    number_of_results=1,
)

ImageTextModel

Generates text from images.

Examples::

model = ImageTextModel.from_pretrained("imagetext@001")
image = Image.load_from_file("image.png")

captions = model.get_captions(
    image=image,
    # Optional:
    number_of_results=1,
    language="en",
)

answers = model.ask_question(
    image=image,
    question="What color is the car in this image?",
    # Optional:
    number_of_results=1,
)

MultiModalEmbeddingModel

Generates embedding vectors from images and videos.

Examples::

model = MultiModalEmbeddingModel.from_pretrained("multimodalembedding@001")
image = Image.load_from_file("image.png")
video = Video.load_from_file("video.mp4")

embeddings = model.get_embeddings(
    image=image,
    video=video,
    contextual_text="Hello world",
)
image_embedding = embeddings.image_embedding
video_embeddings = embeddings.video_embeddings
text_embedding = embeddings.text_embedding

MultiModalEmbeddingResponse

The multimodal embedding response.

Video

Video.

VideoEmbedding

Embeddings generated from video with offset times.

VideoSegmentConfig

The specific video segments (in seconds) the embeddings are generated for.