nsfw_model
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GantMan
big difference in results using saved_model.tflite when compared to nsfwjs.com
I have used saved_model.tflite from v1.1.0 and v1.2.0. image used is 224x224, same jpeg in both testing. here are results:
nsfwjs.com Neutral - 67.35% Porn - 31.40% Drawing - 0.79% Hentai - 0.26% Sexy - 0.19%
saved_model.tflite (v1.1.0, on android with tensorflow lite) porn: 0.8919 sexy: 0.0455 hentai: 0.0355 drawings: 0.0209 neutral: 0.0062
jpeg used is here(safe-for-work):
I am new to this, so correct me if am wrong, I have simply used this tflite without any changes. Am I using the correct version?
while using tflite in android, input RGB is normalised to [0,1] from [0,255].
Tried predict.classify() JavaScript function of this project, with v1.1.0's saved_model.h5. It gave exactly same results as with my android code(using saved_model.tflite).
Wondering if model used in nsfwjs.com is same as v1.1.0 of this repo or something else. @GantMan can you please clarify?
The v1.1.0 is much worse than the nswfjs. No idea why.
~~NSFWJS seems to have higher accuracy on all models, not just v1.1.0~~ nvm, it seems that nsfwjs is only using v1.0 models
If anyone find's this thread in the future, I ended up using Bumble's Private Detector for my NSFW-FLASK service.
Bumble's has higher precision and accuracy. Bumble's model is about 400mb compressed while this is 135Mb