WildVision AI
Camera-trap photograph of a deer in a misty forest at night

AI · Computer Vision · Zoology

AI That Sees Wildlife

Detect · Identify · Count · Learn

WildVision AI uses computer vision to find every animal in a camera-trap image or live camera feed, label the species, count individuals and read the result out loud.

Start Live Camera Upload Wildlife Image Camera Trap Analysis

How It Works

Capture → Detect → Identify → Count → Speak

  1. Camera / Image
  2. Preprocessing
  3. AI Model
  4. Object Detection
  5. Species ID
  6. Counting
  7. Analysis
  8. Speech

Capabilities

Real-Time Detection

Live camera inference at a configurable frame interval.

Multiple Animals

Every individual animal gets its own green bounding box.

Animal Counting

Per-species aggregation with totals and averages.

Text-to-Speech

Natural sentences spoken aloud for classroom demos.

Camera-Trap Analysis

Batch analysis with per-image species breakdown.

Species Information

Taxonomy, diet, habitat and conservation profiles.

Educational Purpose

WildVision AI demonstrates how computer vision can support wildlife observation, biodiversity studies and biological education. Each detection links to a species profile with taxonomy, diet, habitat and conservation information, so the same screen serves both an AI and a zoology audience.

See the detection pipeline

Replaceable ML backend

Inference runs behind a DetectionEngine abstraction. Point ML_API_URL at your own YOLO/ONNX service and the whole app switches to your custom-trained wildlife model — no UI changes required.

View model status