VikParuchuri / surya

OCR, layout analysis, reading order, table recognition in 90+ languages
https://www.datalab.to
GNU General Public License v3.0
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[Question] about Layout #174

Open phamkhactu opened 2 months ago

phamkhactu commented 2 months ago

Thanks for your working

I want to get boundingbox each block likes this. I ran detect_layout.py and drew polygons in image. I got only boundingbox for each row not block of layout.

If I don't make it correctly. Please guide me or give me some code example.

Thank you.

sky-2002 commented 2 months ago

I answered this here - https://github.com/VikParuchuri/surya/issues/173#issuecomment-2288412937

phamkhactu commented 2 months ago

Hi @VikParuchuri

I tested image which is in PubLayNet. With your benchmark, I saw that layout analysis is great. However, in my test, model can not detect block of image, just only one boundingbox per row.

Here is my code I used. I ran detect_layout.py

import argparse
import copy
import json
from collections import defaultdict

from surya.detection import batch_text_detection
from surya.input.load import load_from_folder, load_from_file
from surya.layout import batch_layout_detection
from surya.model.detection.model import load_model, load_processor
from surya.postprocessing.heatmap import draw_polys_on_image
from surya.settings import settings
import os

def main():
    parser = argparse.ArgumentParser(description="Detect layout of an input file or folder (PDFs or image).")
    parser.add_argument("--input_path", default='PMC3576793_00004.jpg', type=str, help="Path to pdf or image file or folder to detect layout in.")
    parser.add_argument("--results_dir", type=str, help="Path to JSON file with layout results.", default=os.path.join(settings.RESULT_DIR, "surya"))
    parser.add_argument("--max", type=int, help="Maximum number of pages to process.", default=None)
    parser.add_argument("--images", action="store_true", help="Save images of detected layout bboxes.", default=True)
    parser.add_argument("--debug", action="store_true", help="Run in debug mode.", default=False)
    args = parser.parse_args()

    model = load_model(checkpoint=settings.LAYOUT_MODEL_CHECKPOINT)
    processor = load_processor(checkpoint=settings.LAYOUT_MODEL_CHECKPOINT)
    det_model = load_model()
    det_processor = load_processor()

    if os.path.isdir(args.input_path):
        images, names = load_from_folder(args.input_path, args.max)
        folder_name = os.path.basename(args.input_path)
    else:
        images, names = load_from_file(args.input_path, args.max)
        folder_name = os.path.basename(args.input_path).split(".")[0]

    line_predictions = batch_text_detection(images, det_model, det_processor)

    layout_predictions = batch_layout_detection(images, model, processor, line_predictions)
    result_path = os.path.join(args.results_dir, folder_name)
    os.makedirs(result_path, exist_ok=True)

    if args.images:
        for idx, (image, layout_pred, name) in enumerate(zip(images, layout_predictions, names)):
            polygons = [p.polygon for p in layout_pred.bboxes]
            labels = [p.label for p in layout_pred.bboxes]
            bbox_image = draw_polys_on_image(polygons, copy.deepcopy(image), labels=labels)
            bbox_image.save(os.path.join(result_path, f"{name}_{idx}_layout.png"))

            if args.debug:
                heatmap = layout_pred.segmentation_map
                heatmap.save(os.path.join(result_path, f"{name}_{idx}_segmentation.png"))

    predictions_by_page = defaultdict(list)
    for idx, (pred, name, image) in enumerate(zip(layout_predictions, names, images)):
        out_pred = pred.model_dump(exclude=["segmentation_map"])
        out_pred["page"] = len(predictions_by_page[name]) + 1
        predictions_by_page[name].append(out_pred)

    with open(os.path.join(result_path, "results.json"), "w+", encoding="utf-8") as f:
        json.dump(predictions_by_page, f, ensure_ascii=False)

    print(f"Wrote results to {result_path}")

if __name__ == "__main__":
    main()

Could you check it again. if I am wrong, please give me some code example