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sartajbhuvaji/self-driving-GTA-V

Self Driving GTA V Dataset Dataset Varients Mini : Link Training Data(1-100) : Link Training Data(101-200) : Link Info Image Resolution : 270, 480 Mode : RGB Dimension : (270, 480, 3) File Count : 100 Size : 1.81 GB/file Total Data Size : 362 GB Total Frames : 1 Million Data Set sizes Mini : Folder Name : mini Files : 01 Total Size : 1.81 GB Total Frames : 5000 First Half Folder Name : Training… See the full description on the dataset page: https://huggingface.co/datasets/sartajbhuvaji/self-driving-GTA-V.

sourceHugging Facemitupdated 3y agoView on Hugging Face
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Dataset Card

Self Driving GTA V Dataset

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Dataset Varients

  • —Mini : Link
  • —Training Data(1-100) : Link)
  • —Training Data(101-200) : Link)

Info

  • —Image Resolution : 270, 480
  • —Mode : RGB
  • —Dimension : (270, 480, 3)
  • —File Count : 100
  • —Size : 1.81 GB/file
  • —Total Data Size : 362 GB
  • —Total Frames : 1 Million

Data Set sizes

Mini :
  • —Folder Name : mini
  • —Files : 01
  • —Total Size : 1.81 GB
  • —Total Frames : 5000
First Half
  • —Folder Name : Training Data(1-100)
  • —Files : 100
  • —Total Size : 181 GB
  • —Total Frames : 500,000
Second Half
  • —Folder Name : Training Data(101-200)
  • —Files : 100
  • —Total Size : 181 GB
  • —Total Frames : 500,000

Data Count

Mini
 'W':  [1, 0, 0, 0, 0, 0, 0, 0, 0] : 3627
 'S':  [0, 1, 0, 0, 0, 0, 0, 0, 0] : 50
 'A':  [0, 0, 1, 0, 0, 0, 0, 0, 0] : 104
 'D':  [0, 0, 0, 1, 0, 0, 0, 0, 0] : 106
 'WA': [0, 0, 0, 0, 1, 0, 0, 0, 0] : 364
 'WD': [0, 0, 0, 0, 0, 1, 0, 0, 0] : 416
 'SA': [0, 0, 0, 0, 0, 0, 1, 0, 0] : 35
 'SD': [0, 0, 0, 0, 0, 0, 0, 1, 0] : 47
 'NK': [0, 0, 0, 0, 0, 0, 0, 0, 1] : 248
  NONE : 3
First Half (Data Count (1-100))
 'W':  [1, 0, 0, 0, 0, 0, 0, 0, 0] : 353725
 'S':  [0, 1, 0, 0, 0, 0, 0, 0, 0] : 2243
 'A':  [0, 0, 1, 0, 0, 0, 0, 0, 0] : 14303
 'D':  [0, 0, 0, 1, 0, 0, 0, 0, 0] : 13114
 'WA': [0, 0, 0, 0, 1, 0, 0, 0, 0] : 30877
 'WD': [0, 0, 0, 0, 0, 1, 0, 0, 0] : 29837
 'SA': [0, 0, 0, 0, 0, 0, 1, 0, 0] : 1952
 'SD': [0, 0, 0, 0, 0, 0, 0, 1, 0] : 1451
 'NK': [0, 0, 0, 0, 0, 0, 0, 0, 1] : 52256
  NONE : 242
Second Half (Data Count (101-200))
 'W':  [1, 0, 0, 0, 0, 0, 0, 0, 0] : 359025
 'S':  [0, 1, 0, 0, 0, 0, 0, 0, 0] : 2834
 'A':  [0, 0, 1, 0, 0, 0, 0, 0, 0] : 11025
 'D':  [0, 0, 0, 1, 0, 0, 0, 0, 0] : 9639
 'WA': [0, 0, 0, 0, 1, 0, 0, 0, 0] : 31896
 'WD': [0, 0, 0, 0, 0, 1, 0, 0, 0] : 29756
 'SA': [0, 0, 0, 0, 0, 0, 1, 0, 0] : 1742
 'SD': [0, 0, 0, 0, 0, 0, 0, 1, 0] : 2461
 'NK': [0, 0, 0, 0, 0, 0, 0, 0, 1] : 51313
  NONE : 309

Graphics Details

  • —Original Resolution : 800 x 600
  • —Aspect Ratio : 16:10
  • —All Video Settings : Low

Camera Details

  • —Camera : Hood Cam
  • —Vehical Camera Height : Low
  • —First Person Vehical Auto-Center : On
  • —First Person Head Bobbing : Off

Other Details

  • —Vehical : Michael's Car
  • —Vehical Mods : All Max
  • —Cv2 Mask : None
  • —Way Point : Enabled/Following
  • —Weather Conditions : Mostly Sunny
  • —Time of Day : Day, Night
  • —Rain : Some

Note

  • —Remove NONE while processing the data
  • —Use the mini dataset for initial setup and testing
  • —Check training_data_count_001-100.csv & training_data_count_101-200.csv for detailed count
  • —Check training_data_stats.py for more info

Inspired From