REAL-TIME ANIMAL OBJECT DETECTION MODEL (PRODUCT)

I have trained a custom model using YOLOv8 with a dataset containing 80 different classes of animals. The classes range

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Description

State-of-the-Art Detection

This is a custom-trained YOLOv8 (You Only Look Once) model designed for high-speed tracking and detection of animals. Unlike standard classifiers, this model provides bounding boxes and confidence scores in real-time.

Dataset Diversity

Trained on 80 distinct animal classes including mammals, birds, and insects. The dataset was sourced from Kaggle and manually verified for bounding box accuracy.

Performance Highlights

  • Real-time Inference: 60+ FPS on compatible hardware.
  • Format: Available in .pt (PyTorch) and .onnx formats.
  • Versatile: Works on both static images and live video streams.

Applications

Wildlife monitoring, Livestock management, and Automated nature photography.

Live Deployment Sandbox

YOLOv8 Neural Scanner
Core Active
Click to browse or drop image/video here

API Integration Guide

curl --location 'https://api.aimodelplace.com/api/v1/predict' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--form 'model_slug="real-time-animal-object-detection-model_80"' \
--form 'file=@"/path/to/your/image.png"'

Successful response format (JSON):

{
    "labels": [
        {
            "label": "1 Zebra"
        }
    ],
    "message": "Image processed successfully",
    "yolo_result": "1 Zebra, ",
    "tokens_consumed": 10,
    "balance_remaining": 619,
    "result_image_path": "/runs/detect/140c41b0-4e3d-4487-827a-0ce28ae3707c_1778757252/tmpzpdhjlc_.jpg"
}

For more detailed parameters and SDK examples, visit our Full API Documentation.

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