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AI-assisted venom risk screening
Know the risk
before you get close.
Upload a photo of a snake for an instant assessment of whether it is likely venomous. The model runs entirely in your browser — your image never leaves your device.
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Awaiting image
Assessment
Your result will appear here
Choose a clear photo showing the snake's head and body. The model compares the image against learned patterns of venomous and non-venomous snakes.
- Good lighting
- Head in focus
- Single snake
Analyzing image…
Running EfficientNet-B0
Assessment result
Non-venomous
Low venom risk predicted
Class probabilities
Venomous—
Non-venomous—
Low-confidence result. The model is close to its decision boundary — treat this as inconclusive and seek expert identification.
How it works
- 1 Upload a clear photo of the snake.
- 2 The image is resized to 224 × 224 and analyzed.
- 3 The predicted probability is compared to a 0.50 threshold.
Under the hood
A fine-tuned EfficientNet-B0 binary classifier exported to TensorFlow.js. Inference runs locally using WebGL when available, with a CPU fallback.
Input224 × 224 × 3
OutputP(venomous)
Private by design
Your photo is processed in the browser and is never uploaded to a server. There are no accounts, no storage, and no tracking pixels.
On-device inference
Not a substitute for expert identification.
Never handle or approach a snake based on this tool's output. The model always returns one of two classes, even for images that do not contain a snake. Treat every wild snake with caution and contact a local expert or emergency service if there is any risk to people or pets.