Upload Colony_Analyzer_AI_zstack2_HF.py

Colony_Analyzer_AI_zstack2_HF.py

@@ -154,17 +154,20 @@ def contours_overlap_using_mask(contour1, contour2, image_shape=(1536, 2048)):
     
     return np.any(overlap)
 
-def analyze_colonies(mask, size_cutoff, circ_cutoff):
-    colonies,areas = find_colonies(mask, size_cutoff, circ_cutoff)
+def analyze_colonies(mask, size_cutoff, circ_cutoff, img):
+    colonies = find_colonies(mask, size_cutoff, circ_cutoff)
     necrosis = find_necrosis(mask)
     
     data = []
     
-    for x in range(len(colonies)):
-        colony = colonies[x]
-        colony_area = areas[x]
+    for colony in colonies:
+        colony_area = cv2.contourArea(colony)
         centroid = compute_centroid(colony)
-
+        if colony_area <= 50:
+            continue
+        mask = np.zeros(img.shape, np.uint8)
+        cv2.drawContours(mask, [colony], -1, 255, cv2.FILLED)
+        pix = img[mask == 255]
         # Check if any necrosis contour is inside the colony
         necrosis_area = 0
         nec_list =[]
@@ -181,7 +184,8 @@ def analyze_colonies(mask, size_cutoff, circ_cutoff):
             "centroid": centroid,
             "percent_necrotic": necrosis_area/colony_area,
             "contour": colony,
-            "nec_contours": nec_list
+            "nec_contours": nec_list,
+            'mean_pixel_value':np.mean(pix)
         })
 
     # Convert results to a DataFrame
@@ -256,7 +260,7 @@ def main(args):
             img_map[z] = eval_img(img_map[z])
         del z
         p = stitch(img_map)
-        frame = analyze_colonies(p, min_size, min_circ)
+        frame = analyze_colonies(p, min_size, min_circ, files[idx])
         frame["source"] = idx
         frame["exclude"] = False
         if isinstance(colonies, dict):