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President Barack Obama waves to members of the NFL Super Bowl champion Seattle Seahawks football team after welcoming the team to the East Room of the White House in Washington, Wednesday, May 21, 2014. The Seahawks defeated the Denver Broncos in Super Bowl XLVIII. (AP Photo/Susan Walsh)
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business education: Help concept and corporate support as a group of people excluded from advancing on a drawing of a line that is being erased and sketched by a pencil. Stock Photo
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Classic Nude Painting - The White Slave Ernest Normand Classical Nude
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By Vivian Maier. A full time nanny living in Chicago in the Vivian captured over 100000 vivid portraits of street life with her Rolleiflex. The post By Vivian Maier. A full time nanny living in Chicago in the Vivian captured appeared first on street. Photo New York, Video Humour, Weegee, Robert Doisneau, Street Photographers, Famous Photographers, Documentary Photography, Documentary Film, Vintage Photography
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91079f7c6f6 Disney s The Nutcracker and the Four Realms Movie Review - Theresa s Reviews
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Example of a mountain style medium tone wood floor family room design in Seattle with brown walls
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Sunflowers and Brass
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Keri Russell - Casual Medium Wavy Hairstyle
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JYP Entertainment Experiences Sharp Decline in Stock Value Following TWICE's Tzuyu's Controversy
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Painting - Captain Jack Sparrow by Edward Pebworth
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Image of Phyllida Law
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International Furniture Direct SalamancaRound Table
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17 Best Images About Classic Contemporary On Pinterest
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photo of Apple TV+ orders new six-part World Surf League docuseries image
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Point Sur | Watercolor Landscapes | Gordon Meggison IV
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"Hero rider Santosh ""resuscitated"" by rival after Dakar crash"
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Australian Gum Tree by artsaus
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Dr. Joel Schlessinger shares an article about Botox and skin elasticity
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Felled: Trees along an avenue in Locre, Belgium, lie torn to shreds. These images are from a series documenting the devastation caused along the Western Front
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This robotically-woven canopy will rise atop Pier 17 in Manhattan. (Courtesy Achim Menges)
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George and Amal Clooney Wedding - Gallery
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beautiful view sky rays lake town canal HD Wallpaper
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Michael Faraday (1791-1867) is known for his work in magnetism and electricity. In 1831, he discovered electromagnetic induction and in 1839, he proposed that there is an underlying relationship between electricity and magnetism.
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Pierre Auguste Renoir facts: Top 8 facts about life of famous artist
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Moon halo over Chile
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Beck Enlists All-Star Lineup for <i>Song Reader</i> Performance
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Pet Portraits in Pencil Gallery by Melanie Phillips
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Despite a spirited comeback, late tries from Joaquin Tuculet and Juan Imhoff (pictured) confirmed the defeat for Schmidt's Ireland
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Furniture Discount Websites: Amazon Home Launch First Own Brand Furniture Collection
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Lighthouse in coastal zone - Fondos de pantalla gratis para iPad 2
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"""We saw it on the 1stdibs floor and immediately thought, 'That is it!'"" says designer Brandon Quattrone of the love-at-first-sight reaction he and his business partner Mat Sanders had to the vintage A.R. Cordemeijer daybed that now sits in their client's Tribeca living room. The circle mirror from Consort's showroom is suspended above a Montauk Sofa sectional in the room's corner."
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Game of Thrones' Emilia Clarke Stunned at the 2014 Golden Globe Awards: Here's how You can get her Hot Look! (PHOTOS)
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360 of coral head in Palmyra
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Ninety One Good Chinese Girls by Jennifer Hom Inspired by a photo the artist saw of a swarm of singing, uniform, asian girls.:
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Rating: Safe Score: 164 Tags: aqua_eyes aqua_hair blonde_hair blush elbow_gloves gloves green_eyes green_hair guitar gumi hatsune_miku instrument kagamine_rin kazeno long_hair megurine_luka pink_hair short_hair thighhighs twintails vocaloid User: SciFi
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A participant tests his motorcycle ahead of the launch of the Rally of Morocco 2021, in the desert Zagora region, on October 7, 2021. The rally will be held from October 8 to 13, 2021. (Photo by Fadel Senna/AFP Photo)
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Order Blueberry Cakes Online From Cake Express: Blueberry Cakes Delivery in Delhi NCR
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bubble forest sprout beauty beautiful wallpaper
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"""Falling In Reverse and Atreyu Announce the """"Christmas Vacation Tour"""""""
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Forget social media, your best Facebook Oculus Rift experience could be all about adorable and deeply moving VR storytelling.
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Lapwing Hybrid Collar hand knitting design from Glamourie by Alice Starmore
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Keala Kennelly pulls into a crazy, heavy death defying Teahupoo wave. Photo Brent Bielmann
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LAION-Aesthetics :: CLIP → UMAP

This dataset is a CLIP (text) → UMAP embedding of the LAION-Aesthetics dataset - specifically the improved_aesthetics_6plus version, which filters the full dataset to images with scores of > 6 under the "aesthetic" filtering model.

Thanks LAION for this amazing corpus!


The dataset here includes coordinates for 3x separate UMAP fits using different values for the n_neighbors parameter - 10, 30, and 60 - which are broken out as separate columns with different suffixes:

  • n_neighbors=10 → (x_nn10, y_nn10)
  • n_neighbors=30 → (x_nn30, y_nn30)
  • n_neighbors=60 → (x_nn60, y_nn60)

nn10

nn10

nn30

nn30

nn60

(The version from Twitter.)

nn60

Pipeline

The script for producing this can be found here:

https://github.com/davidmcclure/loam-viz/blob/laion/laion.py

And is very simple - just using the openai/clip-vit-base-patch32 model out-of-the-box to encode the text captions:

@app.command()
def clip(
    src: str,
    dst: str,
    text_col: str = 'TEXT',
    limit: Optional[int] = typer.Option(None),
    batch_size: int = typer.Option(512),
):
    """Embed with CLIP."""
    df = pd.read_parquet(src)

    if limit:
        df = df.head(limit)

    tokenizer = CLIPTokenizerFast.from_pretrained('openai/clip-vit-base-patch32')
    model = CLIPTextModel.from_pretrained('openai/clip-vit-base-patch32')

    model = model.to(device)

    texts = df[text_col].tolist()

    embeds = []
    for batch in chunked_iter(tqdm(texts), batch_size):

        enc = tokenizer(
            batch,
            return_tensors='pt',
            padding=True,
            truncation=True,
        )

        enc = enc.to(device)

        with torch.no_grad():
            res = model(**enc)

        embeds.append(res.pooler_output.to('cpu'))

    embeds = torch.cat(embeds).numpy()

    np.save(dst, embeds)

    print(embeds.shape)

Then using cuml.GaussianRandomProjection to do an initial squeeze to 64d (which gets the embedding tensor small enough to fit onto a single GPU for the UMAP) -

@app.command()
def random_projection(src: str, dst: str, dim: int = 64):
    """Random projection on an embedding matrix."""
    rmm.reinitialize(managed_memory=True)

    embeds = np.load(src)

    rp = cuml.GaussianRandomProjection(n_components=dim)
    embeds = rp.fit_transform(embeds)

    np.save(dst, embeds)
    print(embeds.shape)

And then cuml.UMAP to get from 64d -> 2d -

@app.command()
def umap(
    df_src: str,
    embeds_src: str,
    dst: str,
    n_neighbors: int = typer.Option(30),
    n_epochs: int = typer.Option(1000),
    negative_sample_rate: int = typer.Option(20),
):
    """UMAP to 2d."""
    rmm.reinitialize(managed_memory=True)

    df = pd.read_parquet(df_src)

    embeds = np.load(embeds_src)

    embeds = embeds.astype('float16')

    print(embeds.shape)
    print(embeds.dtype)

    reducer = cuml.UMAP(
        n_neighbors=n_neighbors,
        n_epochs=n_epochs,
        negative_sample_rate=negative_sample_rate,
        verbose=True,
    )

    x = reducer.fit_transform(embeds)

    df['x'] = x[:,0]
    df['y'] = x[:,1]

    df.to_parquet(dst)
    print(df)
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