medpmc-multi-fig-separation-yolov10 huggingface.co api & Yale-BIDS-Chen medpmc-multi-fig-separation-yolov10 github AI Model

Introduction of medpmc-multi-fig-separation-yolov10

Model Details of medpmc-multi-fig-separation-yolov10

MedPMC Multi-Panel Figure Separation Model

This repository provides the multi-panel figure separation model used in the MedPMC data curation pipeline.

The model is a YOLOv10-based object detection model trained to detect individual panels within multi-panel biomedical figures. It is intended for processing figures from biomedical literature, especially figures from PubMed Central (PMC) articles.

Model

The released checkpoint is:

model.pt

The model can be loaded with the Ultralytics interface.

Installation

See requirements.txt . Install PyTorch following the instructions for your CUDA version from the official PyTorch website.

Usage

from ultralytics import YOLOv10

# Load model
model = YOLOv10("model.pt")

# Run prediction
results = model.predict(
    "sample",
    save=True,
    save_crop=True,
    save_txt=True,
    batch=1,
    conf=0.5,
)

The input path can be a single image, a directory of images, or another path supported by Ultralytics.

Example:

results = model.predict(
    "path/to/images",
    save=True,
    save_crop=True,
    save_txt=True,
    batch=1,
    conf=0.5,
)

The outputs include predicted panel bounding boxes and cropped panel images.

Citation

Citation information will be updated soon.

Runs of Yale-BIDS-Chen medpmc-multi-fig-separation-yolov10 on huggingface.co

Total runs

-3

24-hour runs

3-day runs

7-day runs

30-day runs

More Information About medpmc-multi-fig-separation-yolov10 huggingface.co Model

More medpmc-multi-fig-separation-yolov10 license Visit here:

https://choosealicense.com/licenses/cc-by-nc-sa-4.0

medpmc-multi-fig-separation-yolov10 huggingface.co

medpmc-multi-fig-separation-yolov10 huggingface.co is an AI model on huggingface.co that provides medpmc-multi-fig-separation-yolov10's model effect (), which can be used instantly with this Yale-BIDS-Chen medpmc-multi-fig-separation-yolov10 model. huggingface.co supports a free trial of the medpmc-multi-fig-separation-yolov10 model, and also provides paid use of the medpmc-multi-fig-separation-yolov10. Support call medpmc-multi-fig-separation-yolov10 model through api, including Node.js, Python, http.

medpmc-multi-fig-separation-yolov10 huggingface.co Url

https://huggingface.co/Yale-BIDS-Chen/medpmc-multi-fig-separation-yolov10

Yale-BIDS-Chen medpmc-multi-fig-separation-yolov10 online free

medpmc-multi-fig-separation-yolov10 huggingface.co is an online trial and call api platform, which integrates medpmc-multi-fig-separation-yolov10's modeling effects, including api services, and provides a free online trial of medpmc-multi-fig-separation-yolov10, you can try medpmc-multi-fig-separation-yolov10 online for free by clicking the link below.

Yale-BIDS-Chen medpmc-multi-fig-separation-yolov10 online free url in huggingface.co:

https://huggingface.co/Yale-BIDS-Chen/medpmc-multi-fig-separation-yolov10

medpmc-multi-fig-separation-yolov10 install

medpmc-multi-fig-separation-yolov10 is an open source model from GitHub that offers a free installation service, and any user can find medpmc-multi-fig-separation-yolov10 on GitHub to install. At the same time, huggingface.co provides the effect of medpmc-multi-fig-separation-yolov10 install, users can directly use medpmc-multi-fig-separation-yolov10 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.