Image Classification
Transformers
ONNX
Safetensors
vit
adult-content-classifier-image
classifier
adult
adult-content
image-classifier
image
Instructions to use jiechau/adult-content-identify-image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jiechau/adult-content-identify-image with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jiechau/adult-content-identify-image") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("jiechau/adult-content-identify-image") model = AutoModelForImageClassification.from_pretrained("jiechau/adult-content-identify-image") - Notebooks
- Google Colab
- Kaggle
adult-content-identify-image
(text version here 文字版本請參考 這裡)
Determine whether online sales products are adult content. Input: image content, Output results: 0 Unknown, 1 Adult Content, 2 General Merchandise.
判斷網路銷售商品是否屬於成人內容。輸入圖片內容,輸出結果: 0 未知, 1 成人內容, 2 一般商品。
use transformers pipeline
from transformers import pipeline, AutoConfig
pipe = pipeline("image-classification", model="jiechau/adult-content-identify-image")
config = AutoConfig.from_pretrained("jiechau/adult-content-identify-image")
label2id = config.label2id
id2label = config.id2label
q = 'https://xxx.xxx.xxx/images/xxx/xxx.webp'
q = 'https://xxx.xxx.xxx/images/xxx/xxx.jpg'
result = pipe(q)
print(result)
print(label2id[result[0]['label']])
# [{'label': 'adult_成人商品', 'score': 0.7516837120056152}, {'label': 'regular_一般商品', 'score': 0.2475457787513733}, {'label': 'unknown', 'score': 0.0007705678581260145}]
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