Update app.py

app.py

@@ -103,6 +103,16 @@ def CCA_Analysis(orig_image,predict_image,erode_iteration,open_iteration):
     teeth_count=count2
     return image2,teeth_count    
     
+def detect_decays_static_th(images, dental_masks=None, threshhold=0.9):
+    decay_masks = []
+    for image, dental_mask in zip(images, dental_masks):
+        decay_mask = np.zeros_like(dental_mask)
+        image_masked_with_dental_mask = image * dental_mask
+        decay_mask[image_masked_with_dental_mask > threshhold*255] = 1
+        decay_masks.append(decay_mask)
+    decay_masks = np.array(decay_masks)
+    return decay_masks    
+    
     
 st.subheader("Upload Dental Panoramic X-ray Image")
 image_file = st.file_uploader("Upload Images", type=["png","jpg","jpeg"])
@@ -158,10 +168,16 @@ if image_file is not None:
     mask = np.uint8(predict1 * 255)
     _, mask = cv2.threshold(mask, thresh=255/2, maxval=255, type=cv2.THRESH_BINARY)
     cnts, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
-    img = cv2.drawContours(img, cnts, -1, (255, 0, 0), 2)
+    img = cv2.drawContours(img, cnts, -1, (0, 0, 255), 2)
+    
+    decay_masks = detect_decays_static_th(img, mask)
+    mask = np.uint8(decay_mask * 255)
+    _, mask = cv2.threshold(mask, thresh=255/2, maxval=255, type=cv2.THRESH_BINARY)
+    cnts, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+    img = cv2.fillPoly(img, cnts, (255, 0, 0))
     
     if img is not None :      
-        st.subheader("Predicted teeth shape")  
+        st.subheader("Predicted teeth shape + caries zones")  
         st.write(img.shape)
         st.image(img,width=1100)