tt_object_yolo

YOLOv8-based room occupancy analyzer. Detects people, chairs, and benches in a room image and estimates seating capacity, available space, and overall occupancy status.

Features

• Uses YOLOv8 for object detection (person, chair, bench)
• Estimates seating capacity and available space
• Annotates image with bounding boxes and labels
• Outputs human-readable occupancy summary

Requirements

• Python 3.8+
• ultralytics
• opencv-python
• supervision
• torch

Install dependencies:

pip install -r requirements.txt

Usage

python main.py <path_to_image> [--model yolov8x.pt] [--no-show] [--no-save]

Arguments

• <path_to_image>: Image file to analyze (.jpg, .jpeg, .png)
• --model: Optional. YOLOv8 model file. Defaults to yolov8x.pt
• --no-show: Don’t display annotated image after saving
• --no-save: Don’t save or display annotated image at all

Output

• Console: Counts people, chairs, benches, seating capacity, available space, and interpretation
• Image: Saved as <original_name>_annotated.<ext> unless --no-save is set

Example

python main.py room.jpg