Output.mp4

Intrusion-Detection-System-IDS-

1. Dataset

• Domain: person
• Source: three video yotube with person walking on street (30 fps, total ~85 minute)
• Pre-processing data:
  • Extract image in three video (Skip 30 frame, final: ~5000 image)
  • Labeling per image using lib LabelImg
  • Split data to train model (train & val)
  • Test data: ~500 image from Kaggle (follow: https://www.kaggle.com/datasets/constantinwerner/human-detection-dataset)

2. Models:

• Using yolov5 custom
• Train model, transfer learning on yolov5s
• Export model to ONNX format & inference by opencv (function ReadNetFromONNX)

3. Pipeline IDS:

• Create coords of polygon (Area need to detection)
• In detect, find centroid per object
• Check the centroid with area
• While true: Send massage to telegram user

4. Interface:

• Deverlop with streamlit (Open lib)
• Home
• Cam 1
• Cam 2
• Start detection & result
• Message on telegram

THANKS FOR WATCHING!