fix decoding

examples/SuperResolution/data_sampler.py

@@ -35,6 +35,7 @@ class ImageDataFromZIPFile(RNGDataFlow):
         self.archivefiles = random.sample(self.archivefiles, self.max)
         for archive in self.archivefiles:
             im_data = archive[0].read(archive[1])
+            im_data = np.asarray(bytearray(im_data), dtype='uint8')
             yield [im_data]
 
 
@@ -47,7 +48,7 @@ class ImageEncode(MapDataComponent):
 
 
 class ImageDecode(MapDataComponent):
-    def __init__(self, ds, mode='.jpg', index=0):
+    def __init__(self, ds, index=0):
         def func(im_data):
             img = cv2.imdecode(im_data, cv2.IMREAD_COLOR)
             return img

examples/load-vgg16.py

@@ -83,9 +83,7 @@ def run_test(path, input):
 
     # VGG16 requires channelwise mean substraction
     VGG_MEAN = [103.939, 116.779, 123.68]
-    im[:, :, :, 0] -= VGG_MEAN[2]
-    im[:, :, :, 1] -= VGG_MEAN[1]
-    im[:, :, :, 2] -= VGG_MEAN[0]
+    im -= VGG_MEAN[::-1]
 
     outputs = predict_func(im)[0]
     prob = outputs[0]

examples/load-vgg19.py

@@ -79,9 +79,7 @@ def run_test(path, input):
 
     # VGG19 requires channelwise mean substraction
     VGG_MEAN = [103.939, 116.779, 123.68]
-    im[:, :, :, 0] -= VGG_MEAN[2]
-    im[:, :, :, 1] -= VGG_MEAN[1]
-    im[:, :, :, 2] -= VGG_MEAN[0]
+    im -= VGG_MEAN[::-1]
     outputs = predict_func(im)[0]
     prob = outputs[0]
     ret = prob.argsort()[-10:][::-1]