update

app.py

@@ -115,6 +115,19 @@ def update_displayed_quadrilateral(index, point_combinations, base_image_path):
     # Display the image with the selected quadrilateral
     display_image_with_quadrilateral(base_image, quad_points)
 
+def is_valid_quadrilateral(centroids):
+    if len(centroids) != 4:
+        return False
+
+    def ccw(A, B, C):
+        return (C[1] - A[1]) * (B[0] - A[0]) > (B[1] - A[1]) * (C[0] - A[0])
+
+    def intersect(A, B, C, D):
+        return ccw(A, C, D) != ccw(B, C, D) and ccw(A, B, C) != ccw(A, B, D)
+
+    A, B, C, D = centroids
+    return not (intersect(A, B, C, D) or intersect(A, D, B, C))
+
 def process_image(image_path, flag_lower, flag_upper, plant_lower, plant_upper, loc, file_name, file_exists, selected_img, headers, base_name):
     with loc:
         btn_back, btn_next = st.columns([2,2])
@@ -167,15 +180,24 @@ def process_image(image_path, flag_lower, flag_upper, plant_lower, plant_upper,
         with loc:
             st.warning("Cycle until correct plot bounds are found")
         # Create all possible combinations of four points
-        point_combinations = list(itertools.combinations(significant_contours, 4))
-        
+        if len(significant_contours) >= 4:
+            # Generate all permutations of four points from the significant contours
+            permutations_of_four = list(itertools.permutations(significant_contours, 4))
+
+            # Filter out invalid quadrilaterals
+            valid_permutations = [perm for perm in permutations_of_four if is_valid_quadrilateral(get_points_from_contours(perm))]
+
+            if not valid_permutations:
+                st.error("No valid quadrilaterals found.")
+                return None, None, None, None, None, None, None, None, None, None
+
         # Placeholder for quadrilateral indices
         selected_quad_index = 0
 
         # Function to update displayed quadrilateral based on selected index
         def update_displayed_quadrilateral(index):
             # Extract the four points of the current quadrilateral
-            centroids = get_points_from_contours(point_combinations[index])
+            centroids = get_points_from_contours(valid_permutations[index])
             return centroids
 
         # Show initial quadrilateral
@@ -184,13 +206,17 @@ def process_image(image_path, flag_lower, flag_upper, plant_lower, plant_upper,
         with btn_back:
             # Button to go to the previous quadrilateral
             if st.button('Previous'):
-                selected_quad_index = max(selected_quad_index - 1, 0)
-                centroids = update_displayed_quadrilateral(selected_quad_index)
+                st.session_state.quad_index = (st.session_state.quad_index - 1) % len(valid_permutations)
+                centroids = update_displayed_quadrilateral(st.session_state.quad_index)
+
+            if st.button('Previous'):
+                st.session_state.quad_index = (st.session_state.quad_index + 1) % len(valid_permutations)
+                centroids = update_displayed_quadrilateral(st.session_state.quad_index)
 
         with btn_next:
             # Button to go to the next quadrilateral
             if st.button('Next'):
-                selected_quad_index = min(selected_quad_index + 1, len(point_combinations) - 1)
+                selected_quad_index = min(selected_quad_index + 1, len(valid_permutations) - 1)
                 centroids = update_displayed_quadrilateral(selected_quad_index)
         
         with loc:
@@ -560,6 +586,9 @@ if 'dir_uploaded_images_small' not in st.session_state:
 if 'keep_quad' not in st.session_state:
     st.session_state['keep_quad'] = False
 
+if 'quad_index' not in st.session_state:
+    st.session_state['quad_index'] = 0
+
 st.title("GreenSight")
 st.write("Simple color segmentation app to estimate the vegetation coverage in a plot. Corners of the plot need to be marked with solid, uniforly colored flags.")
 st.write("If you exit the session before completing the segmentation of all images, all progress will be lost!")