Image Violence Detection

What Image Violence Detection does

Screen images for killing, shooting, blood, and gore with a 1–5 risk score. Human review remains required.

The tool invokes a third-party service through a ToolKK OpenAPI Product and presents the response with human-readable labels. Its main input is one JPG, PNG, or BMP image for an initial safety screen; the useful output includes a violence-likelihood description and a 1–5 model risk score. Use the response for screening, review, and organization rather than triggering an irreversible action from one field alone.

Last updated September 21, 2026 · Maintained by ToolKK

How to prepare and submit input

1. Prepare one JPG, PNG, or BMP image for an initial safety screen in the format shown by the form, removing names, notes, internal identifiers, and unrelated data.
2. Check formatting, country codes, file size, or character limits before submitting. The displayed coin price applies to each successful call.
3. Read the headline result first, then verify related scores, sources, regions, lists, and detail fields. A missing field normally means that the provider returned no value.

Content copied from documents or spreadsheets can contain invisible spaces, full-width punctuation, and accidental line breaks. If a request fails, distinguish invalid input from quota limits, timeouts, or temporary provider faults. HTTP 429 and 5xx responses are not proof that the submitted value is invalid.

Practical use cases

Typical workflows include community upload screening, chat-attachment triage, asset-library checks, and moderation prioritization. Adding a structured check before the final workflow can reduce manual entry, repeated research, and inconsistent interpretation. For team use, retain the lookup time, an input summary, returned fields, and the eventual human conclusion.

The result is a point-in-time decision aid. Publishing, payment, user rejection, tax filing, hiring, or content removal should follow documented business rules and preserve a human review or appeal path.

How to interpret the response

The result view prioritizes a violence-likelihood description and a 1–5 model risk score. Read numbers and Boolean values in context: valid does not mean permanently valid, low risk does not mean impossible, and an empty list does not always prove absence. If repeated results differ, consider the lookup time, provider update cycle, and an authoritative source.

Limitations and uncertainty

news, medical, sports, toy, or artistic content can be misclassified and subtle violence can be missed; thresholds need business rules and human review. Provider databases, model versions, network conditions, free-plan features, and synchronization schedules can also affect the answer. Borderline scores, missing fields, and commercially important records should be retained and verified through an authoritative channel.

Privacy and safe handling

images may contain people or traumatic scenes, so restrict access, minimize retention, and do not publicly associate scores with individuals. Follow data minimization and submit only what the task requires. Protect copied or downloaded results with suitable access controls and retention limits, then delete them when the purpose ends. The page never asks users for an APILayer key; credentials remain in the server-side shared Provider and support multi-key rotation.