| --- |
| language: |
| - en |
| task_categories: |
| - object-detection |
| tags: |
| - object-detection |
| - "384" |
| - resized |
| - coco |
| size_categories: |
| - 1M<n<10M |
| --- |
| |
| # Objects365 (384) |
|
|
| Large-scale object detection dataset with 365 categories. |
|
|
| This is a **384×384 resized** version of the **Objects365** dataset, with annotations in **COCO format** (`images`, `annotations`, `categories`). |
|
|
| ## Contents |
|
|
| - `images.zip` — all images, resized to 384×384 (JPEG). |
| - `annotations.zip` — COCO-format JSON annotation files. |
|
|
| ## Extract |
|
|
| ```bash |
| unzip images.zip |
| ``` |
| ```bash |
| unzip annotations.zip |
| ``` |
|
|
| ## Splits |
|
|
| | Split | Images | Annotations | Categories | |
| |---|---:|---:|---:| |
| | train | 1,742,289 | 25,407,543 | 365 | |
| | val | 80,000 | 1,240,584 | 365 | |
|
|
| ## Categories |
|
|
| 365 categories (e.g. Person, Sneakers, Chair, Other Shoes, Hat, Car, Lamp, Glasses, Bottle, Desk, Cup, Street Lights, Cabinet/shelf, Handbag/Satchel, Bracelet, Plate, Picture/Frame, Helmet, Book, Gloves...). |
|
|
| ## Notes |
|
|
| - Images resized to **384×384** (JPEG). |
| - Annotations in **COCO format**. |
| - License & citation: please refer to the original **Objects365** dataset. |
|
|
