README.md

metadata

license: apache-2.0
task_categories:
  - image-feature-extraction
  - image-classification
  - image-to-image
  - text-to-image
size_categories:
  - n<1K
tags:
  - humans
  - glasses
  - eyewear
  - retrieval

📸 Persons with Spectacles

A curated image dataset of human faces annotated for the presence of spectacles (eyeglasses).

---

Dataset Card for hkanade/persons_with_spectacles

Feature	Detail
Dataset name	persons_with_spectacles
Repository	https://huggingface.co/datasets/hkanade/persons_with_spectacles
License	apache-2.0
Languages	—
Tasks	Text to Image, Image classification
Size	120
File format	Parquet
Dataset version	1.0.0

---

1. Dataset Source

All samples were collected from wikimedia/wit_base.

---

2. Usage

from datasets import load_dataset
from PIL import Image
import os
import matplotlib.pyplot as plt
import math, itertools
import io
from IPython.display import display
import cv2

# load full dataset
 ds = load_dataset("hkanade/persons_with_spectacles")


def rec_to_pil(rec):
    """
    Accepts either
      • dict/StructValue holding the raw bytes, or
      • raw bytes themselves, or
      • a PIL.Image already
    Returns a PIL.Image.Image
    """
    if isinstance(rec, Image.Image):
        return rec                       # already a PIL image
    if isinstance(rec, (bytes, bytearray)):
        return Image.open(io.BytesIO(rec))
    if isinstance(rec, dict):            # pandas case
        # try common key names – adjust if yours differ
        for k in ("bytes", "data", 0):
            if k in rec:
                return Image.open(io.BytesIO(rec[k]))
        # fall‑back: take first value
        return Image.open(io.BytesIO(next(iter(rec.values()))))
    # pyarrow StructValue when you skip .to_pandas()
    if hasattr(rec, "values"):           # StructValue → tuple
        return Image.open(io.BytesIO(rec.values()[0]))
    raise TypeError(f"Unsupported type: {type(rec)}")

plt.imshow(rec_to_pil(ds["train"][0]["image"]))
plt.plot()

---

3. Columns

Column	Datatype	Description
Image	struct<bytes: binary, path: string>	Image
image_url	string	URL of the Wikipedia page
embedding	fixed_size_list<element: double>[2048]	ResNet‑50 embedding
caption_attribution_description	string	Caption text
clip_emb	fixed_size_list<element: float>[512]	CLIP embedding of the image
h	fixed_size_list<element: double>[32]	Hue‑channel histogram
s	fixed_size_list<element: double>[32]	Saturation‑channel histogram
v	fixed_size_list<element: double>[32]	Value‑channel histogram
face_ok	bool	Placeholder flag indicating face validity
sim	float	Cosine similarity with the query embedding

---

4. Citation

@misc{persons_with_spectacles_2025,
  author       = {Hrishikesh Kanade (hkanade)},
  title        = {Persons with Spectacles Dataset},
  year         = {2025},
  howpublished = {\url{https://huggingface.co/datasets/hkanade/persons_with_spectacles}}
}