Update README.md

README.md

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 [Github Repo](https://github.com/PogusTheWhisper/SurgiCare.git)
-[Train from this data](https://www.kaggle.com/datasets/ibrahimfateen/wound-classification)
-# SurgiCare_V1_best
-I used EfficientNet-B3 to train for 25 epochs, monitoring the validation loss.
+
+# Surgicare
+
+> Surgicare (Surgical + Care) 
+![](https://imgur.com/a/uteaCTW)
+
+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.
+
+- **Online Demo**: [https://surgicare-demo.streamlit.app/](https://surgicare-demo.streamlit.app/)
+- Wound dataset: [https://www.kaggle.com/datasets/ibrahimfateen/wound-classification](https://www.kaggle.com/datasets/ibrahimfateen/wound-classification))
+
+- Github Repo: [https://github.com/PogusTheWhisper/SurgiCare.git](https://github.com/PogusTheWhisper/SurgiCare.git)
+- Pretrained Models:
+    * Surgicare-V1-best: [https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-best.keras](https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-best.keras)
+    * Surgicare-V1-fast: [https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-mini-best-model.keras](https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-mini-best-model.keras)
+    * Surgicare-V1-mini: [https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-mini-best-model.keras](https://huggingface.co/PogusTheWhisper/SurgiCare/resolve/main/SurgiCare-V1-mini-best-model.keras)
+
+## Result of training!!
+### Efficientnet B3
 * Accuracy: 0.9062 Approximately 11 seconds per image.
+* I used EfficientNet-B3 to train for 25 epochs, monitoring the validation loss.
 
 ![alt text](https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-best.png)
 
-# SurgiCare_V1_fast
-I used MobileNetV3Large to train for 50 epochs, monitoring the validation loss.
+### MobileNetV3Large
 * Accuracy: 0.7969 Approximately 5 seconds per image.
-
+* I used MobileNetV3Large to train for 50 epochs, monitoring the validation loss.
+  
 ![alt text](https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-fast.png)
 
-# SurgiCare_V1_mini
-I used MobileNetV3Small to train for 50 epochs, monitoring the validation loss.
+### MobileNetV3Small
 * Accuracy: 0.7812 Approximately 4 seconds per image.
-
+* I used MobileNetV3Small to train for 50 epochs, monitoring the validation loss.
+  
 ![alt text](https://raw.githubusercontent.com/PogusTheWhisper/SurgiCare/main/wound_classify_train/SurgiCare-V1-mini.png)