README.md

metadata

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:

from datasets import load_dataset
dataset = load_dataset("jjldo21/IndustrialDetectionStaticCameras")