Update app.py

app.py

@@ -21,12 +21,19 @@ model_id = "SerdarHelli/Segmentation-of-Teeth-in-Panoramic-X-ray-Image-Using-U-N
 model=from_pretrained_keras(model_id)
 
 ## Si una imagen tiene más de un canal entonces se convierte a escala de grises (1 canal) 
-def convert_one_channel(img):
-    if len(img.shape)>1:
+def convertir_one_channel(img):
+    if len(img.shape)>2:
         img= cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
         return img
     else:
         return img
+    
+def convertir_rgb(img):
+    if len(img.shape)==2:
+        img= cv2.cvtColor(img,cv2.COLOR_GRAY2RGB)  
+        return img
+    else:
+        return img
 
     
 image_file = st.file_uploader("Sube aquí tu imagen.", type=["png","jpg","jpeg"])
@@ -36,12 +43,11 @@ if image_file is not None:
 
       img= Image.open(image_file)
       
-      st.text("Segmentando...")
       st.image(img,width=850)
       
       img=np.asarray(img)
   
-      img_cv=convert_one_channel(img)
+      img_cv=convertir_one_channel(img)
       img_cv=cv2.resize(img_cv,(512,512), interpolation=cv2.INTER_LANCZOS4)
       img_cv=np.float32(img_cv/255)
       
@@ -55,7 +61,7 @@ if image_file is not None:
       mask=cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel,iterations=1 )  
       mask=cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel,iterations=1 )
       cnts,hieararch=cv2.findContours(mask,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
-      output = cv2.drawContours(convert_one_channel(img), cnts, -1, (255, 0, 0) , 3)
+      output = cv2.drawContours(convertir_one_channel(img), cnts, -1, (255, 0, 0) , 3)
 
 
       if output is not None :