Upload Colony_Analyzer_AI2_HF.py

Colony_Analyzer_AI2_HF.py

@@ -12,14 +12,16 @@ import cv2
 #this is the huggingface version
 def cut_img(img):
     img_map = {}
-    i_num = img.shape[0]/512
-    j_num = img.shape[1]/512
+    width, height = img.size
+    i_num = height // 512
+    j_num = width // 512
     count = 1
-    for i in range(int(i_num)):
-        for j in range(int(j_num)):
-            img_map[count] = img[(512*i):(512*(i+1)), (512*j):(512*(j+1))]
-            count +=1
-    return(img_map)
+    for i in range(i_num):
+        for j in range(j_num):
+            cropped_img = img.crop((512*j, 512*i, 512*(j+1), 512*(i+1)))
+            img_map[count] = cropped_img
+            count += 1
+    return img_map
     
 import numpy as np
 
@@ -107,12 +109,6 @@ def eval_img(image):
 # num_necrosis/num_colony
 
 def find_colonies(mask, size_cutoff, circ_cutoff):
-        # Explicitly ensure mask is 2D
-    if mask.ndim == 3:
-        mask = mask[:, :, 0]  # if mask has multiple channels
-    elif mask.ndim == 4:
-        mask = mask[0, :, :, 0]  # if there's an extra batch/channel dimension
-
     binary_mask = np.where(mask == 1, 255, 0).astype(np.uint8)
     print(np.max(binary_mask))
     contours, _ = cv2.findContours(binary_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
@@ -134,11 +130,6 @@ def find_colonies(mask, size_cutoff, circ_cutoff):
     return(contoursf)
 
 def find_necrosis(mask):
-    # Explicitly ensure mask is 2D
-    if mask.ndim == 3:
-        mask = mask[:, :, 0]  # if mask has multiple channels
-    elif mask.ndim == 4:
-        mask = mask[0, :, :, 0]  # if there's an extra batch/channel dimension
     binary_mask = np.where(mask == 2, 255, 0).astype(np.uint8)
     print(np.max(binary_mask))
     contours, _ = cv2.findContours(binary_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)