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camscanner-image-detect-aigc

Use CamScanner to detect whether an image was generated by an AI model (e.g. Stable Diffusion, Midjourney, DALL·E). Powered by an AIGC-detection engine that classifies an image as genuine, suspected AI-generated, or AI-generated, with a confidence score. Returns a JSON result containing `ai_check_result` (1/2/3), `confidence`, and `result_text`. Use when the user asks whether a photo is AI-generated, wants to verify an image's authenticity against AI generation, or asks "is this AI art / Stable Diffusion / Midjourney?". Triggers on "检测AI生成", "是不是AI画的", "AIGC检测", "AI图片识别", "detect AI-generated image", "is this AI art", "is this diffusion / midjourney", or when the user shares an image and asks whether it was produced by AI.

personAuthor: camscannerhubgithub
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CamScanner Image Detect AIGC

Overview

CamScanner provides an AIGC-detection engine that determines whether an image was produced by an AI generator. The workflow is a 2-step pipeline: upload the image, then validate it with validate_mode: 2. Unlike conversion skills, this skill does not produce a file — the validate step returns a JSON result whose key fields (ai_check_result, confidence, result_text) should be reported back to the user directly.

When to Use

  • User asks whether an image was generated by AI (Stable Diffusion, Midjourney, DALL·E, etc.)
  • User wants to distinguish a real photo from AI-generated artwork
  • User asks "is this AI art / AI-generated?" or similar authenticity questions
  • User shares an image and explicitly asks whether it came from a generative model

Presenting the Result

  • Always read ai_check_result, confidence, and result_text from the response and report them in plain language.
  • Map ai_check_result to a verdict: 1 = not AI-generated, 2 = suspected AI-generated, 3 = AI-generated.
  • Include the confidence value (a float in [0, 1]) so the user understands how certain the verdict is.
  • Match the user's language. result_text is returned in Chinese by the API. If the user asked in English (or any other language), translate/rephrase it into that language. If the user asked in Chinese, you can use result_text as-is.
  • Do not overstate the verdict: "suspected AI-generated" is not the same as "AI-generated".

Privacy & Data

Important: Privacy & Data Flow Notice

  • Third-party service: This skill sends your files to CamScanner's official servers (ai-tools.camscanner.com) for processing.
  • Data retention: CamScanner servers process your files in real-time. Files are not permanently stored on the server.
  • Result: Only a JSON detection result is returned — no file is downloaded.

API Reference

Base URL: https://ai-tools.camscanner.com

Supported Validations

| source_type | validate_mode | Detection | Engine | | ----------- | ------------- | ----------------------- | --------------- | | image | 2 | AIGC (AI-generated) | aigcdetection |

Step 1: Upload Image

BASE="https://ai-tools.camscanner.com"

IN_FILE_ID=$(curl -sS -X POST "$BASE/v1/tools/upload_file/execute" \
  -H "Content-Type: application/octet-stream" \
  --data-binary "@/path/to/image.jpg" | jq -r '.tool_result.data.file_id')

Response:

{
  "code": 200,
  "tool": "upload_file",
  "tool_result": {
    "success": true,
    "data": {
      "file_id": "file_1741857600_ab12cd34ef56.jpg",
      "size": 24576
    }
  }
}

Step 2: Validate Image (Detect AIGC)

curl -sS -X POST "$BASE/v1/tools/validate_image/execute" \
  -H "Content-Type: application/json" \
  -d "{\"file_id\":\"$IN_FILE_ID\",\"validate_mode\":2}"

Response (suspected AI-generated example):

{
  "code": 200,
  "tool": "validate_image",
  "tool_result": {
    "success": true,
    "data": {
      "ai_check_result": 2,
      "confidence": 0.346435546875,
      "engine": "aigcdetection",
      "file_id": "file_xxx.jpg",
      "result_text": "检测结果为疑似 AI 生成图片",
      "review_state": "auto_checked",
      "validate_mode": 2
    },
    "metadata": {
      "ai_check_result": 2,
      "confidence": 0.346435546875,
      "engine": "aigcdetection",
      "result_text": "检测结果为疑似 AI 生成图片",
      "review_state": "auto_checked",
      "validate_mode": 2
    }
  }
}

Interpreting the Result

| Field | Type | Meaning | | ----------------- | ------- | ------------------------------------------------------------------------------ | | ai_check_result | integer | 1 = not AI-generated, 2 = suspected AI-generated, 3 = AI-generated | | confidence | float | Model confidence score in [0, 1] | | result_text | string | Human-readable conclusion (Chinese by default — translate for other languages) | | review_state | string | Review status (e.g. auto_checked) — informational, not user-facing | | validate_mode | integer | Echo of the requested mode (always 2 for AIGC detection) |

Verdict Mapping

| ai_check_result | Verdict | Suggested phrasing (EN) | | ----------------- | ----------------------- | ------------------------------------ | | 1 | Not AI-generated | "Looks like a real image" | | 2 | Suspected AI-generated | "Suspected to be AI-generated" | | 3 | AI-generated | "Detected as AI-generated" |

Quick Reference: Complete Pipeline

Detect whether an image is AI-generated (two-step, reads JSON result):

BASE="https://ai-tools.camscanner.com"
INPUT_IMAGE="/path/to/image.jpg"

# Upload
IN_FILE_ID=$(curl -sS -X POST "$BASE/v1/tools/upload_file/execute" \
  -H "Content-Type: application/octet-stream" \
  --data-binary "@$INPUT_IMAGE" | jq -r '.tool_result.data.file_id')

# Validate and extract key fields
RESULT=$(curl -sS -X POST "$BASE/v1/tools/validate_image/execute" \
  -H "Content-Type: application/json" \
  -d "{\"file_id\":\"$IN_FILE_ID\",\"validate_mode\":2}")

AI_CHECK=$(echo "$RESULT" | jq -r '.tool_result.data.ai_check_result')
CONFIDENCE=$(echo "$RESULT" | jq -r '.tool_result.data.confidence')
RESULT_TEXT=$(echo "$RESULT" | jq -r '.tool_result.data.result_text')

echo "ai_check_result: $AI_CHECK"
echo "confidence:      $CONFIDENCE"
echo "result_text:     $RESULT_TEXT"

Common Mistakes

| Mistake | Fix | | ------------------------------------------ | --------------------------------------------------------------------------- | | Wrong Content-Type on upload | Upload uses application/octet-stream, not multipart/form-data | | Using GET instead of POST | Both endpoints use POST | | Passing validate_mode as a string | validate_mode is an integer — use 2, not "2" | | Including output_mode in the request | validate_image does not use output_mode; it always returns JSON | | Treating ai_check_result as boolean | It is a 3-state integer (1/2/3); map explicitly to a verdict | | Reporting "suspected" as "AI-generated" | ai_check_result == 2 means suspected, not confirmed — phrase accordingly | | Reporting result_text verbatim in EN | result_text is Chinese; translate to match the user's language |

Error Handling

Check each step before proceeding:

# After upload
if [ -z "$IN_FILE_ID" ] || [ "$IN_FILE_ID" = "null" ]; then
  echo "Upload failed"; exit 1
fi

# After validate
if [ "$AI_CHECK" = "null" ] || [ -z "$AI_CHECK" ]; then
  echo "Validation failed"; exit 1
fi