Wildlife Detector - Detectron2
A Faster R-CNN model with optimized Inception v1 backbone for detecting 10 wildlife species.
Classes
- Antelope
- Buffalo
- Elephant
- Giraffe
- Gorilla
- Leopard
- Lion
- Rhino
- Wolf
- Zebra
Performance
Metric |
Value |
AP |
45.7% |
AP50 |
81.8% |
AP75 |
47.7% |
Per-Class Performance (AP)
Animal |
AP |
Animal |
AP |
Buffalo |
58.9% |
Elephant |
58.5% |
Gorilla |
51.2% |
Leopard |
49.4% |
Wolf |
48.0% |
Antelope |
46.4% |
Rhino |
44.1% |
Zebra |
43.7% |
Lion |
31.9% |
Giraffe |
24.5% |
Usage
import torch
from detectron2.config import get_cfg
from detectron2.engine import DefaultPredictor
from detectron2 import model_zoo
from huggingface_hub import hf_hub_download
model_path = hf_hub_download(
repo_id="mynane/inception-wildlife-detector-detectron2",
filename="pytorch_model.bin"
)
cfg = get_cfg()
cfg.merge_from_file(model_zoo.get_config_file("COCO-Detection/faster_rcnn_R_50_C4_3x.yaml"))
cfg.MODEL.WEIGHTS = model_path
cfg.MODEL.ROI_HEADS.NUM_CLASSES = 10
cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5
predictor = DefaultPredictor(cfg)
import cv2
image = cv2.imread("wildlife_image.jpg")
outputs = predictor(image)
Model Details
- Architecture: Faster R-CNN with Optimized Inception v1 backbone
- Framework: Detectron2
- Input Size: 800x1333 (min x max)
- Confidence Threshold: 0.5