hermanshid/yolo-layout-detector

YOLOv5 for Layout Detection

Dataset

Dataset available in kaggle

Supported Labels

["caption", "chart", "image", "image_caption", "table", "table_caption", "text", "title"]

How to use

• Install library

pip install yolov5==7.0.5 torch

Load model and perform prediction

import yolov5
from PIL import Image

model = yolov5.load(models_id)

model.overrides['conf'] = 0.25  # NMS confidence threshold
model.overrides['iou'] = 0.45  # NMS IoU threshold
model.overrides['max_det'] = 1000  # maximum number of detections per image

# set image
image = 'https://huggingface.co./spaces/hermanshid/yolo-layout-detector-space/raw/main/test_images/example1.jpg'

# perform inference
results = model.predict(image)

# observe results
print(results[0].boxes)
render = render_result(model=model, image=image, result=results[0])
render.show()