Fixes bases on updates to numpy and scikit-image

examples/generatedata.py

@@ -47,7 +47,7 @@ def generate():
     while i<nit:
         found=False
         while found==False:
-            x, y = (np.random.random(2)*(n-sz)).astype(np.int)
+            x, y = (np.random.random(2)*(n-sz)).astype(int)
             if l[x:x+sz,y:y+sz].max()==0:
                 found=True
         vl = np.random.random()*0.8+0.2

msdnet/data.py

@@ -91,7 +91,7 @@ def __init__(self, dlist, batchsize, seed=None):
         self.d = dlist
         self.nd = len(self.d)
         self.rndm = np.random.RandomState(seed)
-        self.idx = np.arange(self.nd,dtype=np.int)
+        self.idx = np.arange(self.nd,dtype=int)
         self.rndm.shuffle(self.idx)
         self.bsize = batchsize
         self.i = 0

msdnet/loggers.py

@@ -89,7 +89,7 @@ def getheaderimage(width):
         header_dict[header_image.shape[1]] = header_image
         if width == header_image.shape[1]:
             return header_image
-    res_image = skt.rescale(header_image, width/1536, preserve_range=True, mode='constant', anti_aliasing=True, multichannel=False)
+    res_image = skt.rescale(header_image, width/1536, preserve_range=True, mode='constant', anti_aliasing=True)
     header_dict[width] = res_image
     return res_image
 

msdnet/validate.py

@@ -81,7 +81,7 @@ class LossValidation(Validation):
     def __init__(self, data, loss=None, keep=True):
         self.d = data
         self.keep = keep
-        self.best = np.Inf
+        self.best = np.inf
         self.loss = loss
 
     def errorfunc(self, output, target, msk):
@@ -151,8 +151,8 @@ def validate(self, n):
         errs = np.zeros(len(self.d))
         if self.keep:
             self.outputs = [0,0,0]
-        low = np.Inf
-        high = -np.Inf
+        low = np.inf
+        high = -np.inf
         self.idx = [0,0,0]
         for i,d in enumerate(self.d):
             out = self.n.forward(d.input)

requirements.txt

@@ -0,0 +1,7 @@
+scikit-build
+numpy
+h5py
+tqdm
+imageio
+scikit-image
+numba