image dict | image_url stringlengths 61 309 | embedding list | caption_attribution_description stringlengths 6 858 | clip_emb list | h list | s list | v list | face_ok bool 1
class | sim float32 0.26 0.3 |
|---|---|---|---|---|---|---|---|---|---|
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End of preview. Expand in Data Studio
📸 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}}
}
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