patched image normalization

app.py

@@ -18,8 +18,6 @@ import numpy as np
 import PIL
 import SimpleITK as sitk
 
-MINVAL,MAXVAL = -1000,1000
-
 THIS_DIR = os.path.dirname(os.path.abspath(__file__))
 example_image_path = os.path.join(THIS_DIR,'files','promis12-test-Case00.nii.gz') # from promise12
 example_mask_path = os.path.join(THIS_DIR,'files','promis12-test-Case00-mask.nii.gz') # from promise12
@@ -32,27 +30,26 @@ def load_data(input1,input2):
     mydict['mask_path'] = input2.name
     img = sitk.GetArrayFromImage(sitk.ReadImage(mydict['image_path']))
     mask = sitk.GetArrayFromImage(sitk.ReadImage(mydict['mask_path']))
-    img = ((img-MINVAL)/(MAXVAL-MINVAL)).clip(0,1)*255
+    minval,maxval = np.min(img),np.max(img)
+    img = ((img-minval)/(maxval-minval)).clip(0,1)*255
     mydict['img'] = img.astype(np.uint8)
     mydict['mask'] = mask.astype(np.uint8)
     return f"Image and mask files uploaded, move the above slider to trigger rendering of below component."
 
 def render(x, state):
-    print(x,state)
     if len(mydict)==4:
         if x > mydict['img'].shape[0]-1:
             x = mydict['img'].shape[0]-1
         if x < 0:
             x = 0
-        img = mydict['img'][x,:,:]
+        image = mydict['img'][x,:,:]
         mask = mydict['mask'][x,:,:]
-        im = PIL.Image.fromarray(img)
-        value = (im,[(mask,"prostate")])
+        value = (image,[(mask,"prostate")])
         zmin, zmax = 0,mydict['img'].shape[0]-1
     else:
-        im = np.zeros(10,10)
+        image = np.zeros(10,10)
         zmin, zmax = None, None
-        value = (im,[])
+        value = (image,[])
 
     return value,f'z-value: {x}, (zmin: {zmin}, zmax: {zmax})'