sequence diagram

Author: mtzamanpk

README.md

@@ -58,6 +58,51 @@ CEC_2025_dataset/
 - The `no` folder contains MRI images without tumors
 - The `CEC_test` folder contains test images for prediction
 
+## Workflow Sequence Diagram
+
+The following sequence diagram illustrates the workflow of the tumor detection system:
+
+```mermaid
+sequenceDiagram
+    participant User
+    participant train.py
+    participant run.py
+    participant test.py
+    participant Model
+    participant Dataset
+
+    User->>Dataset: Prepare dataset with yes/no folders
+    User->>train.py: Execute train.py
+    train.py->>Dataset: Load training images
+    train.py->>Model: Initialize EfficientNetV2
+    loop Training Process
+        train.py->>Model: Forward pass
+        Model-->>train.py: Loss calculation
+        train.py->>Model: Backward pass & update weights
+    end
+    train.py->>Model: Save trained model (final_model.pth)
+    train.py-->>User: Training complete
+
+    User->>run.py: Execute run.py
+    run.py->>Model: Load trained model
+    run.py->>Dataset: Load test images from CEC_test
+    loop For each test image
+        run.py->>Model: Predict image
+        Model-->>run.py: Return prediction & confidence
+        run.py->>run.py: Classify probability
+    end
+    run.py->>User: Save results to output.csv
+
+    User->>test.py: Execute test.py (optional)
+    test.py->>Model: Load trained model
+    test.py->>Dataset: Load random test images
+    loop For each test image
+        test.py->>Model: Predict image
+        Model-->>test.py: Return prediction
+    end
+    test.py->>User: Display accuracy statistics
+```
+
 ## Running the Model
 
 To run the model on the CEC_test dataset: