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
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
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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