historic-newspaper-illustrations-yolov11

pip install ultralytics huggingface_hub

from huggingface_hub import hf_hub_download
from ultralytics import YOLO

# Download and load nano model
model = YOLO(hf_hub_download(
    repo_id="small-models-for-glam/historic-newspaper-illustrations-yolov11",
    filename="yolo11n.pt"
))

# Or download and load small model
model = YOLO(hf_hub_download(
    repo_id="small-models-for-glam/historic-newspaper-illustrations-yolov11",
    filename="yolo11s.pt"
))

# Run inference on an image
results = model("path/to/newspaper_page.jpg")

# Process results
for result in results:
    boxes = result.boxes  # Boxes object for bbox outputs
    for box in boxes:
        # Get box coordinates
        x1, y1, x2, y2 = box.xyxy[0]
        # Get confidence score
        conf = box.conf[0]
        # Get class
        cls = box.cls[0]
        # Get class name
        class_name = model.names[int(cls)]
        print(f"Detected {class_name} with confidence {conf:.2f}")