Update app.py

app.py

@@ -68,29 +68,90 @@ def process_zip(zip_file):
     shutil.rmtree(temp_dir)
     return evaluate_model(labels, preds)
 
-def evaluate_model(labels, preds):
-    cm = confusion_matrix(labels, preds)
-    accuracy = accuracy_score(labels, preds)
-    roc_score = roc_auc_score(labels, preds)
-    
-    # Generate classification report as a dictionary
+def format_classification_report(labels, preds):
+    # Convert the report string to a dictionary
     report_dict = classification_report(labels, preds, output_dict=True)
     
-    # Formatting the report as an HTML string for cleaner display
-    report_html = "<h4>Classification Report</h4>"
-    report_html += "<table><tr><th>Class</th><th>Precision</th><th>Recall</th><th>F1-Score</th></tr>"
+    # Create an HTML table
+    html = """
+    <style>
+        .report-table {
+            border-collapse: collapse;
+            width: 100%;
+            font-family: Arial, sans-serif;
+        }
+        .report-table th, .report-table td {
+            border: 1px solid #ddd;
+            padding: 8px;
+            text-align: center;
+        }
+        .report-table th {
+            background-color: #f2f2f2;
+            font-weight: bold;
+        }
+        .report-table tr:nth-child(even) {
+            background-color: #f9f9f9;
+        }
+        .report-table tr:hover {
+            background-color: #f5f5f5;
+        }
+    </style>
+    <table class="report-table">
+        <tr>
+            <th>Class</th>
+            <th>Precision</th>
+            <th>Recall</th>
+            <th>F1-Score</th>
+            <th>Support</th>
+        </tr>
+    """
     
-    for key, value in report_dict.items():
-        if isinstance(value, dict):
-            report_html += f"<tr><td>{key}</td><td>{value['precision']:.2f}</td><td>{value['recall']:.2f}</td><td>{value['f1-score']:.2f}</td></tr>"
+    # Add rows for each class
+    for class_name in ['0', '1']:
+        html += f"""
+        <tr>
+            <td>{class_name}</td>
+            <td>{report_dict[class_name]['precision']:.2f}</td>
+            <td>{report_dict[class_name]['recall']:.2f}</td>
+            <td>{report_dict[class_name]['f1-score']:.2f}</td>
+            <td>{report_dict[class_name]['support']}</td>
+        </tr>
+        """
     
-    report_html += "</table>"
+    # Add summary rows
+    html += f"""
+        <tr>
+            <td>Accuracy</td>
+            <td colspan="3">{report_dict['accuracy']:.2f}</td>
+            <td>{report_dict['macro avg']['support']}</td>
+        </tr>
+        <tr>
+            <td>Macro Avg</td>
+            <td>{report_dict['macro avg']['precision']:.2f}</td>
+            <td>{report_dict['macro avg']['recall']:.2f}</td>
+            <td>{report_dict['macro avg']['f1-score']:.2f}</td>
+            <td>{report_dict['macro avg']['support']}</td>
+        </tr>
+        <tr>
+            <td>Weighted Avg</td>
+            <td>{report_dict['weighted avg']['precision']:.2f}</td>
+            <td>{report_dict['weighted avg']['recall']:.2f}</td>
+            <td>{report_dict['weighted avg']['f1-score']:.2f}</td>
+            <td>{report_dict['weighted avg']['support']}</td>
+        </tr>
+    </table>
+    """
     
-    # Compute ROC Curve
+    return html
+
+def evaluate_model(labels, preds):
+    cm = confusion_matrix(labels, preds)
+    accuracy = accuracy_score(labels, preds)
+    roc_score = roc_auc_score(labels, preds)
+    report_html = format_classification_report(labels, preds)
     fpr, tpr, _ = roc_curve(labels, preds)
     roc_auc = auc(fpr, tpr)
 
-    # Plot Confusion Matrix and ROC Curve
     fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 6))
     
     ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=LABELS).plot(cmap=plt.cm.Blues, ax=ax1)
@@ -149,7 +210,7 @@ def create_gradio_interface():
                     gr.Markdown(f"### Results for {MODEL_NAME}")
                     output_acc = gr.Label(label="Accuracy")
                     output_roc = gr.Label(label="ROC Score")
-                    output_report = gr.HTML(label="Classification Report")  # Changed to gr.HTML for formatted display
+                    output_report = gr.HTML(label="Classification Report")
                     output_plots = gr.Plot(label="Confusion Matrix and ROC Curve")
 
         load_btn.click(load_url, in_url, [inp, message])
@@ -169,4 +230,4 @@ def create_gradio_interface():
 
 if __name__ == "__main__":
     app = create_gradio_interface()
-    app.launch(show_api=False, max_threads=24)
+    app.launch(show_api=False, max_threads=24)