Datasets:
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---
license: mit
size_categories:
- 1K<n<10K
task_categories:
- object-detection
tags:
- industry
dataset_info:
features:
- name: image
dtype: image
- name: labels
sequence:
- name: object_type
dtype: string
- name: truncation
dtype: float32
- name: occlusion
dtype: int32
- name: alpha
dtype: int32
- name: left
dtype: float32
- name: top
dtype: float32
- name: right
dtype: float32
- name: bottom
dtype: float32
- name: height
dtype: int32
- name: width
dtype: int32
- name: length
dtype: int32
- name: x
dtype: int32
- name: y
dtype: int32
- name: z
dtype: int32
- name: rotation_y
dtype: int32
splits:
- name: video1
num_bytes: 4497677.132999999
num_examples: 1261
- name: video2
num_bytes: 4116557.136
num_examples: 1221
- name: video3
num_bytes: 4034190.129
num_examples: 1221
- name: video4
num_bytes: 5164007.345000001
num_examples: 1481
- name: video5
num_bytes: 4733783.518
num_examples: 1301
download_size: 19236723
dataset_size: 22546215.261
configs:
- config_name: default
data_files:
- split: video1
path: data/video1-*
- split: video2
path: data/video2-*
- split: video3
path: data/video3-*
- split: video4
path: data/video4-*
- split: video5
path: data/video5-*
---
The **IndustrialDetectionStaticCameras** dataset is divided into five primary files named `videoY`, where `Y=1,2,3,4,5`. Each `videoY` folder contains the following:
- The video of the scene in `.mp4` format: `videoY.mp4`
- A folder with the images of each frame of the video: `imgs_videoY`
- A folder that includes for each frame a `.txt` file that holds for each labelled object a line with the annotation in kitti format: `annotations_videoY`
**Remark:** Each label file contains a set of lines, with each line representing the annotation for a single object in the corresponding image. The format of each line is as follows:
`<object_type> <truncation> <occlusion> <alpha> <left> <top> <right> <bottom> <height> <width> <length> <x> <y> <z> <rotation_y>`,
where only the fields `<object_type>, <left>, <top>, <right>, <bottom>` and `<rotation_y>` are considered. The `<rotation_y>` field has been used to indicate whether the labelled object is a static object in the scene or not -value `1` represents that object is static and value `0` symbolizes that it is not-.
### Download the dataset:
```python
from datasets import load_dataset
dataset = load_dataset("jjldo21/IndustrialDetectionStaticCameras")
``` |