RT-DETR-L_wireless_table_cell_det
Introduction
The Table Cell Detection Module is a key component of the table recognition task, responsible for locating and marking each cell region in table images. The performance of this module directly affects the accuracy and efficiency of the entire table recognition process. The Table Cell Detection Module typically outputs bounding boxes for each cell region, which are then passed as input to the table recognition pipeline for further processing.
Note: The accuracy of RT-DETR-L_wireless_table_cell_det comes from the results of joint testing with RT-DETR-L_wired_table_cell_det.
Model Usage
Install Dependencies
pip install -U paddleocr
pip install -U onnxruntime-gpu
CLI Usage
paddleocr table_cells_detection -i ./demo.jpg --model_name RT-DETR-L_wireless_table_cell_det --engine onnxruntime
Python API Usage
from paddleocr import TableCellsDetection
model = TableCellsDetection(
model_name="RT-DETR-L_wireless_table_cell_det",
engine="onnxruntime",
)
output = model.predict("./demo.jpg", batch_size=1)
for res in output:
res.print()
res.save_to_img(save_path="./output/")
res.save_to_json(save_path="./output/res.json")