Update app.py

app.py

@@ -397,19 +397,19 @@ def seg_track_app():
                     <li>8. Download the video with segmentation results</li>
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                 We designed this API and <a href="https://github.com/bowang-lab/MedSAMSlicer/tree/SAM2" target="_blank">3D Slicer Plugin</a> for medical image and video segmentation where the checkpoints are based on the original SAM2 models (<a href="https://github.com/facebookresearch/segment-anything-2" target="_blank">https://github.com/facebookresearch/segment-anything-2</a>). The image segmentation fine-tune code has been released on <a href="https://github.com/bowang-lab/MedSAM/tree/MedSAM2?tab=readme-ov-file#fine-tune-sam2-on-the-abdomen-ct-dataset" target="_blank">GitHub</a>. The video fine-tuning code is under active development and will be released as well.  
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                 If you find these tools useful, please consider citing the following papers:
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                 Ravi, N., Gabeur, V., Hu, Y.T., Hu, R., Ryali, C., Ma, T., Khedr, H., Rädle, R., Rolland, C., Gustafson, L., Mintun, E., Pan, J., Alwala, K.V., Carion, N., Wu, C.Y., Girshick, R., Dollár, P., Feichtenhofer, C.: SAM 2: Segment Anything in Images and Videos. arXiv:2408.00714 (2024)
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                 Ma, J., Kim, S., Li, F., Baharoon, M., Asakereh, R., Lyu, H., Wang, B.: Segment Anything in Medical Images and Videos: Benchmark and Deployment. arXiv preprint arXiv:2408.03322 (2024)
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                 Other useful resources: 
                 <a href="https://ai.meta.com/sam2" target="_blank">Official demo</a> from MetaAI, 
                 <a href="https://www.youtube.com/watch?v=Dv003fTyO-Y" target="_blank">Video tutorial</a> from Piotr Skalski.