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license: apache-2.0 |
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tags: |
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- vision |
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- image-classification |
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# Surgicare |
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> Surgicare (Surgical + Care) |
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<img src="https://i.imgur.com/nOi95Cj.png" width="250"> |
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SurgiCare is an AI system designed to support post-surgery patient recovery. In this repository, we focus on a wound classification model trained on an open-source dataset. Our objective is to improve the accuracy of wound detection and guide patients in managing their wound recovery efficiently. |
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- **Online Demo**: [https://surgicare-demo.streamlit.app/](https://surgicare-demo.streamlit.app/) |
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- Wound dataset: [https://www.kaggle.com/datasets/ibrahimfateen/wound-classification](https://www.kaggle.com/datasets/ibrahimfateen/wound-classification) |
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- Github Repo: [https://github.com/PogusTheWhisper/SurgiCare.git](https://github.com/PogusTheWhisper/SurgiCare.git) |
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- Pretrained Models: |
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* Surgicare-V1-large-turbo: [https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-large-turbo.keras](https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-large-turbo.keras) |
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* Surgicare-V1-large: [https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-large.keras](https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-large.keras) |
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* Surgicare-V1-medium: [https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-medium.keras](https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-medium.keras) |
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* Surgicare-V1-small: [https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-small.keras](https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-small.keras) |
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## Result of standard models |
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### EfficientnetV2 B3 |
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* Accuracy: 0.6884 |
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<img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/EfficientNetV2B3-standard.png?raw=true" width="800"> |
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### Efficientnet B3 |
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* Accuracy: 0.7436 |
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<img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/EfficientNetB3-standard.png?raw=true" width="800"> |
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### MobileNetV3Large |
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* Accuracy: 0.6164 |
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<img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/MobileNetV3Large-standard.png?raw=true" width="800"> |
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### MobileNetV3Small |
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* Accuracy: 0.6199 |
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<img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/MobileNetV3Small-standard.png?raw=true" width="800"> |
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## Result of our models!! |
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### EfficientnetV2 B3 |
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* Accuracy: 0.9127 |
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* Training Details: I used EfficientNet-B3 to train for 50 epochs, monitoring the validation loss. |
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<img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-large-turbo.png?raw=true" width="800"> |
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### Efficientnet B3 |
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* Accuracy: 0.9062 |
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* Training Details: I used EfficientNet-B3 to train for 25 epochs, monitoring the validation loss. |
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<img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-large.png?raw=true" width="800"> |
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### MobileNetV3Large |
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* Accuracy: 0.7969 |
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* Training Details: I used MobileNetV3Large to train for 50 epochs, monitoring the validation loss. |
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<img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-medium.png?raw=true" width="800"> |
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### MobileNetV3Small |
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* Accuracy: 0.7812 |
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* Training Details: I used MobileNetV3Small to train for 50 epochs, monitoring the validation loss. |
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<img src="https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-small.png?raw=true" width="800"> |
