Detect
1 credit / requestPOST /api/v1/detectBest for classical wildlife camera traps. Use this endpoint to analyze one image and get wildlife detections with bounding boxes, labels, and taxonomy details.
Try in PlaygroundRequired Parameters
image(file | base64 string) Image data. Practical raw limit is about 1.1MB because Vertex enforces a 1.5MB encoded request cap.
Optional Parameters
country(string) Optional geofencing hint (CCA2/CCA3/full country name).threshold(number) Confidence threshold between 0.01 and 0.99. Default: 0.2.
Supports multipart/form-data (recommended for files) and application/json with base64 image. This Vertex-backed route enforces the upstream 1.5MB request cap, so keep raw images around 1.1MB or less.
Status Codes
200Detection completed.
400Validation error (bad payload/threshold/image).
401Invalid, missing, or revoked API key.
402Credit limit exceeded.
413Payload too large for the Vertex-backed request limit.
429Rate limit exceeded.
500Unexpected internal server error.
503Upstream Vertex service error.
- Best for: classical wildlife camera traps.
- Uses the same camera-trap Vertex SpeciesNet preset as the internal full-detection pipeline.
- Use `/detect-urban` when your imagery is urban, indoor, roadside, zoo, farm, or other human-modified settings.
Node.js / Express
const form = new FormData()
form.append('image', imageFile)
form.append('country', 'USA')
form.append('threshold', '0.2')
const response = await fetch('https://www.animaldetect.com/api/v1/detect', {
method: 'POST',
headers: {
Authorization: 'Bearer ' + process.env.ANIMAL_DETECT_API_KEY,
},
body: form,
})
const data = await response.json()Example Response
JSON
{
"id": "5e4e5dbd-2604-46b4-bb87-8f42fd682b08",
"expires_at": "2026-03-12T09:44:20.954Z",
"annotations": [
{
"id": 0,
"bbox": [0.41, 0.82, 0.20, 0.17],
"score": 0.997,
"label": "canine family",
"taxonomy": {
"id": "3184697f-51ad-4608-9a28-9edb5500159c",
"class": "mammalia",
"order": "carnivora",
"family": "canidae",
"genus": "",
"species": ""
}
}
],
"info": {
"processing_time_ms": 919,
"model_version": "mdv1000-speciesnet",
"model_id": "mdv1000-speciesnet",
"country_processed": "USA",
"threshold_applied": 0.2
}
}