It's interesting. I've not tested the model on anything too risque, but again, with the well known Baywatch intro as a frame of reference, wide shots of the who

It's interesting. I've not tested the model on anything too risque, but again, with the well known Baywatch intro as a frame of reference, wide shots of the whole cast in their swimsuits, are fine. But a close up of any single cast member a swimsuit will invariably trigger the model. Male or female. In the blog, I suggest this could be the result of an uncultured data set when training the CNN. Or perhaps the dataset was fine, and this is pushing the hard limit of what ResNet50 CNN architecture can do (the off the shelf model I use for this is an extension of ResNet50). Some of the anomalous results are amusing. One day, I uploaded a video of a female violinist in concert, and the model flagged every close up of her as NSFW! Just those closeups. Wide shots, and closeups of other musicians were absolutely fine. Again some of that might be down to me (clunky code / very low NSFW threshold). And I suspect the model I used was itself a PoC (https://github.com/emiliantolo/pytorch_nsfw_model https://github.com/emiliantolo/pytorch_nsfw_model). But it does make you wonder how the bigger labs with critical products, like Palantir, handle doubts like this.