"\n\n\n \n \n \n 403 Forbidden<\/title>\n \n<\/head>\n \n\n \n Server Error<\/h1>\n 403<\/div>\n Forbidden<\/h2>\n
You do not have permission to access this document.<\/p>\n
\n That's what you can do<\/p>\n
Here is an example of a black and white image containing nudity. Neural Machine understands what's depicted in the image despite of skin tone colors.
"\n\n\n \n \n \n 403 Forbidden<\/title>\n \n<\/head>\n \n\n \n Server Error<\/h1>\n 403<\/div>\n Forbidden<\/h2>\n
You do not have permission to access this document.<\/p>\n
\n That's what you can do<\/p>\n
Below there is an example of a picture depicting what may trigger a false positive nudity. Despite that, Neural Machine performs perfectly fine and identifies a totally safe image with "neutral" rating.
"\n\n\n \n \n \n 403 Forbidden<\/title>\n \n<\/head>\n \n\n \n Server Error<\/h1>\n 403<\/div>\n Forbidden<\/h2>\n
You do not have permission to access this document.<\/p>\n
\n That's what you can do<\/p>\n
Below is an image of a shirtless person. It is marked as safe, but score variance denotes that the subject is not completely covered. A "moderate" rating is present. Such scores and ratings can be used to implement customized solutions based on thresholds and flags.