The NSFW Image Detection API is a cutting-edge solution that empowers developers and businesses to safeguard their platforms and users from inappropriate or explicit content. With real-time image analysis, this API provides a powerful tool to identify and filter out "Not Safe For Work" (NSFW) content, ensuring a safe and secure environment for all users.
At the core of the NSFW Image Detection API is its exceptional accuracy and completeness. The sophisticated algorithms behind the API have been meticulously trained on vast and diverse datasets, making it one of the most comprehensive solutions available. This enables the API to detect NSFW content across a wide range of topics, including adult content, violence, explicit imagery, and more, ensuring that even the most nuanced and sensitive content is accurately flagged.
Developers can effortlessly integrate the NSFW Image Detection API into their applications, platforms, or websites, enhancing user experiences and bolstering safety measures. Whether it's a social media platform, an e-commerce website, or a content aggregator, this API offers a powerful layer of protection against inappropriate visuals, fostering trust and confidence among users.
Furthermore, the real-time capabilities of the API ensure that content is analyzed instantly, allowing platforms to proactively prevent the exposure of harmful or offensive images to their audiences. By leveraging the NSFW Image Detection API, businesses can mitigate risks associated with inappropriate content and uphold community guidelines, ultimately safeguarding their brand reputation and user base.
Privacy and security are paramount concerns when dealing with sensitive content. Rest assured that the NSFW Image Detection API is designed with privacy in mind. The API does not store or retain images, ensuring that all image analysis is performed in real time without compromising user data or privacy.
In conclusion, the NSFW Image Detection API is a powerful and comprehensive tool to detect "Not Safe For Work" content in images in real-time. Its accuracy, completeness, and real-time capabilities make it an invaluable asset for platforms seeking to maintain a safe and respectful environment for their users. Embrace the NSFW Image Detection API today and take a proactive stance against inappropriate content, ensuring a positive and secure user experience for all.
Pass the image URL that you want to analyze. Detect if it has NSFW content with its classification.
Social Media Moderation: Social media platforms can utilize the NSFW Image Detection API to automatically moderate user-generated content in real-time. By detecting and filtering out inappropriate or explicit images, the API helps maintain a safe and family-friendly environment, ensuring that users can interact with content free from harmful visuals.
Content Sharing Apps: Content-sharing apps that allow users to upload images can integrate the NSFW Image Detection API to prevent the dissemination of NSFW content within their platform. This ensures that the content remains appropriate and compliant with community guidelines, enhancing the overall user experience.
E-commerce Platforms: E-commerce websites can use the NSFW Image Detection API to ensure that product images and user-generated content are free from NSFW visuals. By filtering out inappropriate images, businesses can maintain a professional and trustworthy brand image, fostering confidence among their customers.
Ad Networks and Content Monetization: Ad networks and content monetization platforms can leverage the NSFW Image Detection API to ensure that ads and sponsored content displayed on their platforms are free from explicit or offensive visuals. This enhances the quality of advertisements and ensures brand safety for advertisers and publishers.
Content Moderation for Chat and Messaging Apps: Chat and messaging applications can employ the NSFW Image Detection API to automatically scan and moderate images shared between users. By preventing the exchange of NSFW content in private messages, these apps can create a secure and respectful environment for their users.
Besides the number of API calls, there is no other limitation
Check if an image is NSFW. Return a JSON with labels.
Moderate - Endpoint Features
Object | Description |
---|---|
Request Body |
[Required] Json |
{"unsafe":false,"objects":[{"box":[280,31,652,399],"score":0.8855571150779724,"label":"FACE_F"}]}
curl --location --request POST 'https://zylalabs.com/api/2295/nsfw+image+detection+api/2187/moderate' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw '{
"url": "https://www.lavieenrose.com/globalassets/lver/pictures-24f2/swim/70100657_p00367_4.jpg?width=1024&format=webp"
}'
Header | Description |
---|---|
Authorization
|
[Required] Should be Bearer access_key . See "Your API Access Key" above when you are subscribed. |
No long term commitments. One click upgrade/downgrade or cancellation. No questions asked.
The NSFW Image Detection API is a powerful image analysis tool that allows developers to detect "Not Safe For Work" (NSFW) content in images. It uses advanced machine learning algorithms to analyze image content and identify inappropriate or explicit visuals, helping businesses maintain a safe and respectful online environment.
The NSFW Image Detection API utilizes a combination of deep learning models and image recognition techniques. These models are trained on large datasets containing a wide range of NSFW content, enabling the API to accurately identify explicit images and flag them for further action or moderation.
The API is designed to detect various types of NSFW content, including adult content, violence, explicit imagery, and other inappropriate visuals. Its comprehensive training ensures it can accurately identify explicit content across multiple topics.
Yes, the NSFW Image Detection API is optimized for real-time performance. It delivers fast responses, making it well-suited for integration into real-time applications, such as social media platforms and chat applications.
Yes, the API returns confidence scores alongside the detection results. These scores indicate the level of confidence the model has in its predictions, helping developers make informed decisions on how to handle flagged content.
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