Update app.py

app.py

@@ -69,6 +69,8 @@ def load_model(model_path):
 
 model = load_model("segmentation_model_final.pth")
 
+csv_output_path = "measurement_summary.csv"
+
 def fig_to_image(fig):
     buf = BytesIO()
     canvas = FigureCanvas(fig)
@@ -134,7 +136,7 @@ def analyze(image):
         elif length <= thresholds[2]: color = colors[2]
         elif length <= thresholds[3]: color = colors[3]
         else: color = colors[4]
-        cv2.drawContours(color_mask, [box], 0, color, 3)
+        cv2.drawContours(color_mask, [box], 0, color, 5)
 
     fig2 = plt.figure(figsize=(6, 6))
     plt.imshow(cv2.cvtColor(color_mask, cv2.COLOR_BGR2RGB))
@@ -159,8 +161,6 @@ def analyze(image):
                 dist_px = np.linalg.norm(pt1 - pt2)
                 dist_mm = dist_px * pixel_length_mm
                 edge_lengths.append(dist_mm)
-                midpoint = (pt1 + pt2) / 2
-                plt.text(midpoint[1], midpoint[0], f"{dist_mm:.1f}", color="blue", fontsize=6, ha="center")
         plt.title("Delaunay Triangulation")
     else:
         plt.title("Not Enough Aggregates for Triangulation")
@@ -181,6 +181,21 @@ def analyze(image):
     else:
         avg_feret_length_mm = avg_feret_width_mm = max_feret_length_mm = roundness_aggregate = 0
 
+    # Save to CSV
+    data = {
+        "Pixel_Size_mm_per_pixel": [pixel_length_mm],
+        "Aggregate_Area_mm2": [aggregate_area_mm2],
+        "Aggregate_Ratio": [aggregate_ratio],
+        "Avg_Length_mm": [avg_feret_length_mm],
+        "Avg_Width_mm": [avg_feret_width_mm],
+        "Max_Length_mm": [max_feret_length_mm],
+        "Roundness": [roundness_aggregate],
+        "Avg_Dist_mm": [np.mean(edge_lengths) if edge_lengths else 0],
+        "Max_Dist_mm": [np.max(edge_lengths) if edge_lengths else 0]
+    }
+    df = pd.DataFrame(data)
+    df.to_csv(csv_output_path, index=False)
+
     summary = f"""📏 **Measurements Summary**:
 - Pixel Size: `{pixel_length_mm:.4f}` mm/pixel
 - Aggregate Area: `{aggregate_area_mm2:.2f}` mm²