mirror of
https://github.com/VikParuchuri/surya.git
synced 2026-06-04 21:03:53 +08:00
67 lines
3.0 KiB
Python
67 lines
3.0 KiB
Python
import argparse
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import copy
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import json
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from collections import defaultdict
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from surya.detection import batch_text_detection
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from surya.input.load import load_from_folder, load_from_file
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from surya.layout import batch_layout_detection
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from surya.model.detection.model import load_model, load_processor
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from surya.postprocessing.heatmap import draw_polys_on_image
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from surya.settings import settings
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import os
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def main():
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parser = argparse.ArgumentParser(description="Detect layout of an input file or folder (PDFs or image).")
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parser.add_argument("input_path", type=str, help="Path to pdf or image file or folder to detect layout in.")
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parser.add_argument("--results_dir", type=str, help="Path to JSON file with layout results.", default=os.path.join(settings.RESULT_DIR, "surya"))
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parser.add_argument("--max", type=int, help="Maximum number of pages to process.", default=None)
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parser.add_argument("--images", action="store_true", help="Save images of detected layout bboxes.", default=False)
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parser.add_argument("--debug", action="store_true", help="Run in debug mode.", default=False)
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args = parser.parse_args()
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model = load_model(checkpoint=settings.LAYOUT_MODEL_CHECKPOINT)
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processor = load_processor(checkpoint=settings.LAYOUT_MODEL_CHECKPOINT)
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det_model = load_model()
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det_processor = load_processor()
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if os.path.isdir(args.input_path):
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images, names = load_from_folder(args.input_path, args.max)
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folder_name = os.path.basename(args.input_path)
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else:
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images, names = load_from_file(args.input_path, args.max)
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folder_name = os.path.basename(args.input_path).split(".")[0]
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line_predictions = batch_text_detection(images, det_model, det_processor)
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layout_predictions = batch_layout_detection(images, model, processor, line_predictions)
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result_path = os.path.join(args.results_dir, folder_name)
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os.makedirs(result_path, exist_ok=True)
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if args.images:
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for idx, (image, layout_pred, name) in enumerate(zip(images, layout_predictions, names)):
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polygons = [p.polygon for p in layout_pred.bboxes]
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labels = [p.label for p in layout_pred.bboxes]
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bbox_image = draw_polys_on_image(polygons, copy.deepcopy(image), labels=labels)
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bbox_image.save(os.path.join(result_path, f"{name}_{idx}_layout.png"))
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if args.debug:
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heatmap = layout_pred.segmentation_map
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heatmap.save(os.path.join(result_path, f"{name}_{idx}_segmentation.png"))
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predictions_by_page = defaultdict(list)
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for idx, (pred, name, image) in enumerate(zip(layout_predictions, names, images)):
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out_pred = pred.model_dump(exclude=["segmentation_map"])
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out_pred["page"] = len(predictions_by_page[name]) + 1
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predictions_by_page[name].append(out_pred)
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with open(os.path.join(result_path, "results.json"), "w+", encoding="utf-8") as f:
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json.dump(predictions_by_page, f, ensure_ascii=False)
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print(f"Wrote results to {result_path}")
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if __name__ == "__main__":
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main()
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