This API is designed to accurately identify whether an image was generated using artificial intelligence or whether it comes from the real world. It uses advanced computer vision and deep learning models that analyze visual patterns, textures, digital artifacts, and characteristic features present in images. Through its processing, the API calculates and returns two main probabilities: AI Probability (probability that the image was created by AI) and Real Probability (probability that it is an authentic photograph).
In addition, the endpoint includes a predictive result field—for example, “artificial” or “real”—that summarizes the final classification of the image. This data allows users to make quick and informed decisions about the authenticity of visual content. The API is especially useful in environments where verifying the provenance of an image is essential, such as media outlets, security agencies, social media platforms, and misinformation detection systems.
This technology helps combat digital disinformation, visual manipulation, and the misuse of AI-generated images, providing a reliable tool for transparency and trust in digital media. In an environment where the boundaries between the real and the synthetic are increasingly blurred, this API provides clarity and security through automated, objective, AI-based analysis.
In short, the AI Image Detection API converts visual uncertainty into verifiable information, strengthening the authenticity and credibility of digital content.
{"ai_probability":"99.99%","real_probability":"0.01%","predicted_results":"artical","analysed_results":["🤖 Metallic Surface and Texture \nThe metallic surface of the suit exhibits a high level of detail, including realistic scratches, small specks, and reflections that suggest wear and tear. These details are very consistent and uniformly distributed, which can be a sign of digital rendering rather than real-world imperfections that usually present a bit more randomness.","💡 Lighting and Eye Glow \nThe bright blue glow of the eyes is very clean and perfectly symmetrical, with a sharp contrast against the darker parts of the mask. The glow effect is consistent and lacks subtle light diffusion or spillover that would naturally occur, indicating a digital creation.","🔧 Mechanical and Armor Details \nThe intricate paneling and mechanical junctions on the suit are precise and look highly stylized. The lines and edges are too perfect, with uniform spacing and shape that lean towards a computer-generated model rather than an assembled physical suit.","🌆 Background and Depth of Field \nThe blurred urban background is natural but also exhibits a uniform bokeh effect that is typical in CGI to simulate photographic depth of field. The positioning of the character in sharp focus against this background supports the artificial composite feel.","Overall, the image has characteristics typical of high-quality AI-generated or digitally rendered content, including immaculate detailing, perfect symmetry, and controlled lighting effects."]}
curl --location 'https://zylalabs.com/api/10912/ai+image+detection+api/20622/image+analyzer' \
--header 'Content-Type: multipart/form-data' \
--form 'image=@"FILE_PATH"'
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Authorization
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[Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed. |
No long-term commitment. Upgrade, downgrade, or cancel anytime. Free Trial includes up to 50 requests.
The Image Analyzer endpoint returns data that includes AI Probability, Real Probability, predicted results, and analyzed results. These fields provide insights into whether an image is AI-generated or real, along with detailed observations about visual characteristics.
The key fields in the response data are "ai_probability," "real_probability," "predicted_results," and "analyzed_results." These fields indicate the likelihood of AI generation, authenticity, and detailed analysis of the image's features.
The response data is structured in JSON format, with key-value pairs. The main probabilities are presented as percentages, while the analyzed results provide a list of observations about the image, helping users understand the basis for the classification.
The Image Analyzer endpoint provides information on the likelihood of an image being AI-generated or real, along with detailed analysis of visual elements such as textures, lighting, and mechanical details that contribute to the classification.
Users can customize their data requests by providing different image inputs to the POST Image Analyzer endpoint. The API processes each image independently, allowing for tailored analysis based on the specific content submitted.
Typical use cases include verifying the authenticity of images in media outlets, detecting misinformation on social media, and ensuring security in environments where image provenance is critical. The API aids in combating digital disinformation effectively.
Data accuracy is maintained through advanced computer vision and deep learning models that analyze visual patterns and features. Continuous training and updates to these models ensure reliable performance in distinguishing between AI-generated and real images.
Standard data patterns in the analyzed results include detailed observations about textures, lighting effects, and mechanical details. These patterns help users identify characteristics typical of AI-generated images, such as overly perfect symmetry or unnatural lighting.
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