ragavsachdeva/magi

The Manga Whisperer

Automatically Generating Transcriptions for Comics

Ragav Sachdeva and Andrew Zisserman

University of Oxford

 

Usage

from transformers import AutoModel
import numpy as np
from PIL import Image
import torch
import os

images = [
        "path_to_image1.jpg",
        "path_to_image2.png",
    ]

def read_image_as_np_array(image_path):
    with open(image_path, "rb") as file:
        image = Image.open(file).convert("L").convert("RGB")
        image = np.array(image)
    return image

images = [read_image_as_np_array(image) for image in images]

model = AutoModel.from_pretrained("ragavsachdeva/magi", trust_remote_code=True).cuda()
with torch.no_grad():
    results = model.predict_detections_and_associations(images)
    text_bboxes_for_all_images = [x["texts"] for x in results]
    ocr_results = model.predict_ocr(images, text_bboxes_for_all_images)

for i in range(len(images)):
    model.visualise_single_image_prediction(images[i], results[i], filename=f"image_{i}.png")
    model.generate_transcript_for_single_image(results[i], ocr_results[i], filename=f"transcript_{i}.txt")

License and Citation

The provided model and datasets are available for unrestricted use in personal, research, non-commercial, and not-for-profit endeavors. For any other usage scenarios, kindly contact me via email, providing a detailed description of your requirements, to establish a tailored licensing arrangement. My contact information can be found on my website: ragavsachdeva [dot] github [dot] io

@misc{sachdeva2024manga,
      title={The Manga Whisperer: Automatically Generating Transcriptions for Comics}, 
      author={Ragav Sachdeva and Andrew Zisserman},
      year={2024},
      eprint={2401.10224},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}