Update app.py

app.py

@@ -5,25 +5,20 @@ import gradio as gr
 
 
 def detect_baseline_and_solvent_front(image):
-    """
-    Automatically 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)
         edges = cv2.Canny(blurred, 50, 150)
 
-        # Sum pixel intensities along each row to find horizontal lines
         row_sums = edges.sum(axis=1)
         baseline_y = None
         solvent_front_y = None
 
-        # Detect lines based on intensity peaks
         for i, value in enumerate(row_sums):
-            if value > 50:  # Threshold for detecting a line
+            if value > 50:
                 if baseline_y is None:
-                    baseline_y = i  # First line is the baseline
-                solvent_front_y = i  # Last detected line is the solvent front
+                    baseline_y = i
+                solvent_front_y = i
 
         return baseline_y, solvent_front_y
     except Exception as e:
@@ -32,9 +27,6 @@ def detect_baseline_and_solvent_front(image):
 
 
 def detect_spots(image):
-    """
-    Detect spots (compounds) on the TLC plate.
-    """
     try:
         gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
         blurred = cv2.GaussianBlur(gray, (5, 5), 0)
@@ -44,7 +36,7 @@ def detect_spots(image):
         spots = []
         for contour in contours:
             x, y, w, h = cv2.boundingRect(contour)
-            if w > 5 and h > 5:  # Filter small noise
+            if w > 5 and h > 5:
                 spots.append((x, y, w, h))
         return spots
     except Exception as e:
@@ -53,9 +45,6 @@ def detect_spots(image):
 
 
 def calculate_rf(spots, solvent_front_y, baseline_y):
-    """
-    Calculate the Rf values for detected spots.
-    """
     rf_values = []
     for _, y, _, _ in spots:
         distance_compound = y - baseline_y
@@ -66,29 +55,25 @@ def calculate_rf(spots, solvent_front_y, baseline_y):
 
 
 def annotate_image(image, spots, rf_values):
-    """
-    Annotate the image with detected spots and their Rf values.
-    """
-    annotated_image = image.copy()
     try:
+        annotated_image = image.copy()
         for (x, y, w, h), rf in zip(spots, rf_values):
-            cv2.putText(annotated_image, f"Rf={rf:.2f}", (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1)
+            cv2.putText(
+                annotated_image, f"Rf={rf:.2f}", (x, y - 10),
+                cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1
+            )
             cv2.rectangle(annotated_image, (x, y), (x + w, y + h), (0, 255, 0), 2)
         return annotated_image
     except Exception as e:
         print(f"Error in annotate_image: {e}")
-        return image
+        return None
 
 
 def process_tlc(image):
-    """
-    Process the TLC plate image to calculate Rf values and generate a report.
-    """
     try:
-        if image is None:
-            return "Error: No image uploaded.", None
+        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
@@ -100,6 +85,9 @@ def process_tlc(image):
         rf_values = calculate_rf(spots, solvent_front_y, baseline_y)
         annotated_image = annotate_image(image, spots, rf_values)
 
+        if annotated_image is None:
+            return "Error: Could not annotate the TLC plate image.", None
+
         report_data = {"Spot": list(range(1, len(spots) + 1)), "Rf Value": rf_values}
         report = pd.DataFrame(report_data).to_csv(index=False)
 
@@ -109,12 +97,11 @@ def process_tlc(image):
         return "Error: Processing failed. Check inputs and try again.", None
 
 
-# Gradio Interface
 interface = gr.Interface(
     fn=process_tlc,
     inputs=gr.Image(type="numpy", label="Upload TLC Plate Image"),
     outputs=[
-        gr.Image(label="Annotated TLC Plate"),
+        gr.Image(type="numpy", label="Annotated TLC Plate"),
         gr.File(label="Download Rf Report (CSV)"),
     ],
     title="TLC Analyzer",