Lightweight Nudity Detection
Project description
Looking for contributors/ maintainers for this repo: I have become busy with other stuff in the last years, still trying to maintain this repo as it is the current best OSS option for nudity detection, Looking for interested mainttainer, who can add/ work on more features for this repo (with my help of course)
NudeNet: lightweight Nudity detection
https://nudenet.notai.tech/ in-browser demo (the detector is run client side, i.e: in your browser, images are not sent to a server)
pip install --upgrade "nudenet>=3.4.2"
from nudenet import NudeDetector
detector = NudeDetector()
# the 320n model included with the package will be used
detector.detect('image.jpg') # Returns list of detections
detector.detect_batch(['image_1.jpg', 'image_2.jpg']) # Returns list of [list of detections]
-
detect
anddetect_batch
accept file path(s), opencv image(s), image bytes(s), open(image_path, 'rb') (buffereader) objects
Available models
Model | resolution trained | based on | onnx link | pytorch link |
---|---|---|---|---|
320n | 320x320 | ultralytics yolov8n | link | link |
640m | 640x640 | ultralytics yolov8m | link | link |
# To use the 640m model, download the onnx file and pass the path to the model_path argument
detector = NudeDetector(model_path="downloaded_640m.onnx path", inference_resolution=640)
- 320n is the default model and is included in the
nudenet
python package by default
detection_example = [
{'class': 'BELLY_EXPOSED',
'score': 0.799403190612793,
'box': [64, 182, 49, 51]},
{'class': 'FACE_FEMALE',
'score': 0.7881264686584473,
'box': [82, 66, 36, 43]},
]
nude_detector.censor('image.jpg') # returns censored image output path
# optional censor(self, image_path, classes=[], output_path=None) classes and output_path can be passed
all_labels = [
"FEMALE_GENITALIA_COVERED",
"FACE_FEMALE",
"BUTTOCKS_EXPOSED",
"FEMALE_BREAST_EXPOSED",
"FEMALE_GENITALIA_EXPOSED",
"MALE_BREAST_EXPOSED",
"ANUS_EXPOSED",
"FEET_EXPOSED",
"BELLY_COVERED",
"FEET_COVERED",
"ARMPITS_COVERED",
"ARMPITS_EXPOSED",
"FACE_MALE",
"BELLY_EXPOSED",
"MALE_GENITALIA_EXPOSED",
"ANUS_COVERED",
"FEMALE_BREAST_COVERED",
"BUTTOCKS_COVERED",
]
Docker
docker run -it -p8080:8080 ghcr.io/notai-tech/nudenet:latest
curl -F f1=@"images.jpeg" "http://localhost:8080/infer"
{"prediction": [[{"class": "BELLY_EXPOSED", "score": 0.8511635065078735, "box": [71, 182, 31, 50]}, {"class": "FACE_FEMALE", "score": 0.8033977150917053, "box": [83, 69, 21, 37]}, {"class": "FEMALE_BREAST_EXPOSED", "score": 0.7963727712631226, "box": [85, 137, 24, 38]}, {"class": "FEMALE_BREAST_EXPOSED", "score": 0.7709134817123413, "box": [63, 136, 20, 37]}, {"class": "ARMPITS_EXPOSED", "score": 0.7005534172058105, "box": [60, 127, 10, 20]}, {"class": "FEMALE_GENITALIA_EXPOSED", "score": 0.6804671287536621, "box": [81, 241, 14, 24]}]], "success": true}⏎
Some interesting projects based on NudeNet
1 - by https://github.com/w-e-w, censor extension ps://github.com/notAI-tech/NudeNet/issues/131
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