/Image-Forgery-Detection

Collected dataset for Image Forgery and labeled the data and tried different models to train

Primary LanguagePython

Datasets

  • Initial Dataset
    • Downloaded the images from here
    • Labeled the downloaded images as 1 -> Forged Image, 0 -> Original Image
    • 96 image samples (50% of them are Original Image and rest 50% are forged version of them)
  • VCL Dataset
    • Downloaded the images from here
    • Labeled the downloaded images as 1 -> Forged Image, 0 -> Original Image
    • 1096 image samples (50% of them are Original Image and rest 50% are forged version of them)