Update app.py

app.py

@@ -5,6 +5,9 @@ import gradio as gr
 
 
 def detect_baseline_and_solvent_front(image):
+    """
+    Detect the baseline and solvent front in the TLC plate image.
+    """
     try:
         gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
         blurred = cv2.GaussianBlur(gray, (5, 5), 0)
@@ -15,11 +18,14 @@ def detect_baseline_and_solvent_front(image):
         solvent_front_y = None
 
         for i, value in enumerate(row_sums):
-            if value > 50:
+            if value > 50:  # Threshold for significant edge detection
                 if baseline_y is None:
                     baseline_y = i
                 solvent_front_y = i
 
+        if baseline_y is None or solvent_front_y is None:
+            raise ValueError("Could not detect baseline or solvent front.")
+
         return baseline_y, solvent_front_y
     except Exception as e:
         print(f"Error in detecting baseline and solvent front: {e}")
@@ -27,6 +33,9 @@ def detect_baseline_and_solvent_front(image):
 
 
 def detect_spots(image):
+    """
+    Detect spots on the TLC plate.
+    """
     try:
         gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
         blurred = cv2.GaussianBlur(gray, (5, 5), 0)
@@ -36,7 +45,7 @@ def detect_spots(image):
         spots = []
         for contour in contours:
             x, y, w, h = cv2.boundingRect(contour)
-            if w > 5 and h > 5:
+            if w > 5 and h > 5:  # Filter small noise
                 spots.append((x, y, w, h))
         return spots
     except Exception as e:
@@ -45,24 +54,42 @@ def detect_spots(image):
 
 
 def calculate_rf(spots, solvent_front_y, baseline_y):
-    rf_values = []
-    for _, y, _, _ in spots:
-        distance_compound = y - baseline_y
-        distance_solvent = solvent_front_y - baseline_y
-        rf = distance_compound / distance_solvent if distance_solvent > 0 else 0
-        rf_values.append(round(rf, 2))
-    return rf_values
+    """
+    Calculate the Rf values for detected spots.
+    """
+    try:
+        rf_values = []
+        for _, y, _, _ in spots:
+            distance_compound = y - baseline_y
+            distance_solvent = solvent_front_y - baseline_y
+            rf = distance_compound / distance_solvent if distance_solvent > 0 else 0
+            rf_values.append(round(rf, 2))
+        return rf_values
+    except Exception as e:
+        print(f"Error in calculate_rf: {e}")
+        return []
 
 
 def annotate_image(image, spots, rf_values):
+    """
+    Annotate the image with detected spots and their Rf values.
+    """
     try:
         annotated_image = image.copy()
         for (x, y, w, h), rf in zip(spots, rf_values):
+            if x < 0 or y < 0 or x + w > image.shape[1] or y + h > image.shape[0]:
+                continue  # Skip invalid spots
+
+            # Annotate with Rf value
             cv2.putText(
                 annotated_image, f"Rf={rf:.2f}", (x, y - 10),
                 cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1
             )
+            # Draw rectangle around the spot
             cv2.rectangle(annotated_image, (x, y), (x + w, y + h), (0, 255, 0), 2)
+
+        # Convert to RGB for Gradio compatibility
+        annotated_image = cv2.cvtColor(annotated_image, cv2.COLOR_BGR2RGB)
         return annotated_image
     except Exception as e:
         print(f"Error in annotate_image: {e}")
@@ -70,24 +97,32 @@ def annotate_image(image, spots, rf_values):
 
 
 def process_tlc(image):
+    """
+    Process the TLC plate image and calculate Rf values.
+    """
     try:
         if image is None or not isinstance(image, np.ndarray):
             return "Error: Invalid image uploaded. Please try again with a valid image.", None
 
+        # Detect baseline and solvent front
         baseline_y, solvent_front_y = detect_baseline_and_solvent_front(image)
         if baseline_y is None or solvent_front_y is None:
             return "Error: Unable to detect baseline or solvent front.", None
 
+        # Detect spots on the TLC plate
         spots = detect_spots(image)
         if not spots:
             return "Error: No spots detected on the TLC plate.", None
 
+        # Calculate Rf values
         rf_values = calculate_rf(spots, solvent_front_y, baseline_y)
-        annotated_image = annotate_image(image, spots, rf_values)
 
+        # Annotate the image with detected spots and Rf values
+        annotated_image = annotate_image(image, spots, rf_values)
         if annotated_image is None:
             return "Error: Could not annotate the TLC plate image.", None
 
+        # Generate a CSV report of Rf values
         report_data = {"Spot": list(range(1, len(spots) + 1)), "Rf Value": rf_values}
         report = pd.DataFrame(report_data).to_csv(index=False)
 
@@ -97,6 +132,7 @@ def process_tlc(image):
         return "Error: Processing failed. Check inputs and try again.", None
 
 
+# Define Gradio Interface
 interface = gr.Interface(
     fn=process_tlc,
     inputs=gr.Image(type="numpy", label="Upload TLC Plate Image"),
@@ -105,7 +141,8 @@ interface = gr.Interface(
         gr.File(label="Download Rf Report (CSV)"),
     ],
     title="TLC Analyzer",
-    description="Upload a TLC plate image to automatically calculate Rf values. The application detects the solvent front and baseline automatically.",
+    description="Upload a TLC plate image to automatically calculate Rf values. "
+                "The application detects the solvent front and baseline automatically.",
 )
 
 if __name__ == "__main__":