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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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---
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language:
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- en
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---
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<style>
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.title-container {
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display: flex;
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flex-direction: column; /* Stack elements vertically */
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justify-content: center;
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align-items: center;
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}
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.title {
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font-size: 2em;
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text-align: center;
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color: #333;
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font-family: 'Comic Sans MS', cursive; /* Use Comic Sans MS font */
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text-transform: uppercase;
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letter-spacing: 0.1em;
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padding: 0.5em 0 0.2em;
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background: transparent;
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}
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.title span {
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background: -webkit-linear-gradient(45deg, #6495ED, #4169E1); /* Blue gradient */
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-webkit-background-clip: text;
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-webkit-text-fill-color: transparent;
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}
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.subheading {
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font-size: 1.5em; /* Adjust the size as needed */
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text-align: center;
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color: #555; /* Adjust the color as needed */
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font-family: 'Comic Sans MS', cursive; /* Use Comic Sans MS font */
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}
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.authors {
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font-size: 1em; /* Adjust the size as needed */
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text-align: center;
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color: #777; /* Adjust the color as needed */
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font-family: 'Comic Sans MS', cursive; /* Use Comic Sans MS font */
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padding-top: 1em;
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}
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.affil {
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font-size: 1em; /* Adjust the size as needed */
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text-align: center;
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color: #777; /* Adjust the color as needed */
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font-family: 'Comic Sans MS', cursive; /* Use Comic Sans MS font */
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}
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</style>
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<div class="title-container">
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<div class="title">
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Ta<span>il</span>s Tell Ta<span>le</span>s
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</div>
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<div class="subheading">
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Chapter-Wide Manga Transcriptions With Character Names
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</div>
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<div class="authors">
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Ragav Sachdeva, Gyungin Shin and Andrew Zisserman
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</div>
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<div class="affil">
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University of Oxford
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</div>
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</div>
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# Usage
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```python
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from transformers import AutoModel
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import PIL
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import torch
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batch_of_images = [PIL.Image.open("image1.jpg"), PIL.Image.open("image2.jpg")]
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model = AutoModel.from_pretrained("ragavsachdeva/magiv2-crop-embedder", trust_remote_code=True).cuda().eval()
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with torch.no_grad():
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embeddings = model(batch_of_images)
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print(embeddings.shape)
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```
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# License and Citation
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The provided model is 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.
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My contact information can be found on my website: ragavsachdeva [dot] github [dot] io
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```
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@misc{magiv2,
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title={Tails Tell Tales: Chapter-Wide Manga Transcriptions with Character Names},
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author={Ragav Sachdeva and Gyungin Shin and Andrew Zisserman},
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year={2024},
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eprint={2408.00298},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2408.00298},
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}
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```
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