image dict | image_id stringlengths 58 100 | width int32 384 2.3k | height int32 288 1.92k | objects listlengths 0 13 | source_dataset stringclasses 4
values | source_image_path stringlengths 71 113 | source_label_path stringlengths 71 113 | mime_type stringclasses 2
values |
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{"bytes":"/9j/4AAQSkZJRgABAQAAAQABAAD/4gIoSUNDX1BST0ZJTEUAAQEAAAIYAAAAAAIQAABtbnRyUkdCIFhZWiAAAAAAAA(...TRUNCATED) | Overhead.yolov8/B_No_d800mm_R1_mp4-106_jpg.rf.WNJ87nXsXEyMgJMKJAld.jpg | 384 | 288 | [{"bbox":[214.8000030517578,94.80000305175781,34.0,33.0],"category_id":0,"category":"person","source(...TRUNCATED) | Overhead.yolov8 | Overhead.yolov8/train/images/B_No_d800mm_R1_mp4-106_jpg.rf.WNJ87nXsXEyMgJMKJAld.jpg | Overhead.yolov8/train/labels/B_No_d800mm_R1_mp4-106_jpg.rf.WNJ87nXsXEyMgJMKJAld.txt | image/jpeg |
{"bytes":"/9j/4AAQSkZJRgABAQAAAQABAAD/4gIoSUNDX1BST0ZJTEUAAQEAAAIYAAAAAAIQAABtbnRyUkdCIFhZWiAAAAAAAA(...TRUNCATED) | Overhead.yolov8/B_No_d800mm_R1_mp4-107_jpg.rf.roLmYEMFkUXRM8VzZDLZ.jpg | 384 | 288 | [{"bbox":[154.0,87.01000213623047,31.0,32.0],"category_id":0,"category":"person","source_category":"(...TRUNCATED) | Overhead.yolov8 | Overhead.yolov8/train/images/B_No_d800mm_R1_mp4-107_jpg.rf.roLmYEMFkUXRM8VzZDLZ.jpg | Overhead.yolov8/train/labels/B_No_d800mm_R1_mp4-107_jpg.rf.roLmYEMFkUXRM8VzZDLZ.txt | image/jpeg |
{"bytes":"/9j/4AAQSkZJRgABAQAAAQABAAD/4gIoSUNDX1BST0ZJTEUAAQEAAAIYAAAAAAIQAABtbnRyUkdCIFhZWiAAAAAAAA(...TRUNCATED) | Overhead.yolov8/B_No_d800mm_R1_mp4-108_jpg.rf.Ee1eXj7r6UHIwq5hnMbl.jpg | 384 | 288 | [{"bbox":[205.0,94.0,34.0,33.0],"category_id":0,"category":"person","source_category":"Person"},{"bb(...TRUNCATED) | Overhead.yolov8 | Overhead.yolov8/train/images/B_No_d800mm_R1_mp4-108_jpg.rf.Ee1eXj7r6UHIwq5hnMbl.jpg | Overhead.yolov8/train/labels/B_No_d800mm_R1_mp4-108_jpg.rf.Ee1eXj7r6UHIwq5hnMbl.txt | image/jpeg |
End of preview. Expand in Data Studio
Overhead People RGB
Unified overhead RGB people detection dataset converted from local Roboflow YOLOv8 exports.
Images are stored as original encoded bytes without resizing, recompression, or preprocessing. All retained boxes use a single category:
category_id:0category:personbbox: COCO-style[x, y, width, height]in pixel coordinates
Source labels such as Man, Woman, Person, ero, and 0 are preserved in objects.source_category. Source label object is omitted.
## Loading The Dataset
```python
from io import BytesIO
from datasets import load_dataset
from PIL import Image
repo_id = "bdanko/overhead-people-rgb"
# Loads all parquet shards from Hugging Face.
dataset = load_dataset(repo_id, split="train")
print(dataset)
print(dataset[0].keys())
row = dataset[0]
# Images are stored as original encoded bytes.
image = Image.open(BytesIO(row["image"]["bytes"])).convert("RGB")
# COCO-style boxes in pixel coordinates: [x, y, width, height]
boxes = [obj["bbox"] for obj in row["objects"]]
labels = [obj["category_id"] for obj in row["objects"]]
print(row["image_id"])
print(image.size)
print(boxes[:3])
print(labels[:3])
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