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profientw3456/
inception-wildlife

Name: inception-wildlife
Availability: InStock

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Inception Wildlife

Production-ready wildlife detection model using Inception v3 + Faster R-CNN, optimized for real-world API deployment.

Model Details

Architecture: Inception v3 + Faster R-CNN
Framework: Detectron2 + PyTorch
Classes: 11 wildlife animals
Pretrained: Yes (Inception v3 backbone)
Upload Date: 2025-06-12

Detected Animals

Antelope, Buffalo, Elephant, Giraffe, Gorilla, Hippopotamus, Leopard, Lion, Rhino, Wolf, Zebra

Quick Start

python

from inference_api import WildlifeDetectorAPI

detector = WildlifeDetectorAPI(
    model_path="model_final.pth",
    config_path="production_config.json"
)
result = detector.predict("image.jpg", confidence_threshold=0.5)
print(result)

API Response Format

json

{
  "success": true,
  "detections": [
    {
      "class_id": 0,
      "class_name": "antelope",
      "confidence": 0.85,
      "confidence_level": "high",
      "bbox": {
        "x1": 100.0,
        "y1": 200.0,
        "x2": 300.0,
        "y2": 450.0,
        "width": 200.0,
        "height": 250.0
      }
    }
  ],
  "summary": {
    "total_detections": 1,
    "high_confidence": 1,
    "medium_confidence": 0,
    "low_confidence": 0
  }
}

Installation

bash

pip install -r requirements.txt
# Install detectron2 (platform-specific, example for CUDA 11.3, PyTorch 1.10)
pip install detectron2 -f https://dl.fbaipublicfiles.com/detectron2/wheels/cu113/torch1.10/index.html

Files Included

model_final.pth: Trained model weights
production_config.json: Production configuration
inference_api.py: Inference script for API integration
requirements.txt: Dependencies

Confidence Levels

High: ≥ 80%
Medium: 60-79%
Low: 40-59%

Production Tips

Use GPU for faster inference.
Set confidence threshold based on application needs.
Cache model instance for API performance.
Handle invalid image inputs gracefully.

License

Apache-2.0 (ensure compliance with your dataset).

profientw3456/inception-wildlife