| --- |
| license: cc-by-nc-sa-4.0 |
| base_model: |
| - Ultralytics/YOLO26 |
| tags: |
| - chemistry |
| --- |
| |
| # MolDetv2 (YOLO26 Version) |
|
|
| This repository provides the **YOLO26-based version** of [MolDetv2](https://huggingface.co/UniParser/MolDetv2) model. |
|
|
|
|
| ## 💻 Usage |
|
|
| Detect molecules in an image: |
| ``` |
| from ultralytics import YOLO |
| model = YOLO("/path/to/moldet_v2_yolo26n_640_general.pt") # for cpu only inference: using `moldet_v2_yolo26n_640_general.onnx` for faster speed |
| model.predict("path/to/image.png", save=True, imgsz=640, conf=0.5) |
| ``` |
|
|
| Detect molecules in a PDF document: |
| ``` |
| from ultralytics import YOLO |
| import fitz # MuPDF |
| pdf = fitz.open("doc.pdf") |
| model = YOLO("/path/to/moldet_v2_yolo26n_960_doc.pt") # for cpu only inference: using `moldet_v2_yolo26n_960_doc.onnx` for faster speed |
| bboxes = [] |
| for i, p in enumerate(pdf): |
| img = f"page_{i}.png"; p.get_pixmap().save(img) |
| for r in model.predict(img, imgsz=960, conf=0.5): |
| for box in r.boxes: |
| bboxes.append({"page":img, "conf":float(box.conf), "bbox":box.xyxy[0].tolist()}) |
| |
| ``` |
|
|
| ## 📜 License |
|
|
| MolDet & MolDetv2 model weights are provided for **non-commercial use only**. |
|
|
| For commercial use, please contact: [fangxi@dp.tech](mailto:fangxi@dp.tech) or add a discussion in HuggingFace. |
|
|
|
|
| ## 📖 Citation |
|
|
| If you use this model in your work, please cite: |
|
|
| ``` |
| Comming soon! |
| ``` |
