windows support for Image2Image (fix #1413)

examples/GAN/Image2Image.py

@@ -4,6 +4,7 @@
 # Author: Yuxin Wu
 
 import argparse
+import functools
 import glob
 import numpy as np
 import os
@@ -146,7 +147,7 @@ class Model(GANModelDesc):
         return tf.train.AdamOptimizer(lr, beta1=0.5, epsilon=1e-3)
 
 
-def split_input(dp):
+def split_input(mode, dp):
     """
     dp: the datapoint. first component is an RGB image of shape (s, 2s, 3).
     :return: [input, output]
@@ -156,7 +157,7 @@ def split_input(dp):
     s = img.shape[0]
     assert img.shape[1] == 2 * s
     input, output = img[:, :s, :], img[:, s:, :]
-    if args.mode == 'BtoA':
+    if mode == 'BtoA':
         input, output = output, input
     if IN_CH == 1:
         input = cv2.cvtColor(input, cv2.COLOR_RGB2GRAY)[:, :, np.newaxis]
@@ -165,12 +166,12 @@ def split_input(dp):
     return [input, output]
 
 
-def get_data():
+def get_data(args):
     datadir = args.data
     imgs = glob.glob(os.path.join(datadir, '*.jpg'))
     ds = ImageFromFile(imgs, channel=3, shuffle=True)
 
-    ds = MapData(ds, split_input)
+    ds = MapData(ds, functools.partial(split_input, args.mode))
     augs = [imgaug.Resize(286), imgaug.RandomCrop(256)]
     ds = AugmentImageComponents(ds, augs, (0, 1))
     ds = BatchData(ds, BATCH)
@@ -217,7 +218,7 @@ if __name__ == '__main__':
     else:
         logger.auto_set_dir()
 
-        data = QueueInput(get_data())
+        data = QueueInput(get_data(args))
         trainer = GANTrainer(data, Model(), get_num_gpu())
 
         trainer.train_with_defaults(

tensorpack/dataflow/image.py

@@ -196,33 +196,35 @@ class AugmentImageComponents(MapData):
         else:
             self.augs = AugmentorList(augmentors)
         self.ds = ds
+        self._exception_handler = ExceptionHandler(catch_exceptions)
+        self._copy = copy
+        self._index = index
+        self._coords_index = coords_index
 
-        exception_handler = ExceptionHandler(catch_exceptions)
-
-        def func(dp):
-            dp = copy_mod.copy(dp)  # always do a shallow copy, make sure the list is intact
-            copy_func = copy_mod.deepcopy if copy else lambda x: x  # noqa
-            with exception_handler.catch():
-                major_image = index[0]  # image to be used to get params. TODO better design?
-                im = copy_func(dp[major_image])
-                check_dtype(im)
-                tfms = self.augs.get_transform(im)
-                dp[major_image] = tfms.apply_image(im)
-                for idx in index[1:]:
-                    check_dtype(dp[idx])
-                    dp[idx] = tfms.apply_image(copy_func(dp[idx]))
-                for idx in coords_index:
-                    coords = copy_func(dp[idx])
-                    validate_coords(coords)
-                    dp[idx] = tfms.apply_coords(coords)
-                return dp
-
-        super(AugmentImageComponents, self).__init__(ds, func)
+        super(AugmentImageComponents, self).__init__(ds, self._aug_mapper)
 
     def reset_state(self):
         self.ds.reset_state()
         self.augs.reset_state()
 
+    def _aug_mapper(self, dp):
+        dp = copy_mod.copy(dp)  # always do a shallow copy, make sure the list is intact
+        copy_func = copy_mod.deepcopy if self._copy else lambda x: x  # noqa
+        with self._exception_handler.catch():
+            major_image = self._index[0]  # image to be used to get params. TODO better design?
+            im = copy_func(dp[major_image])
+            check_dtype(im)
+            tfms = self.augs.get_transform(im)
+            dp[major_image] = tfms.apply_image(im)
+            for idx in self._index[1:]:
+                check_dtype(dp[idx])
+                dp[idx] = tfms.apply_image(copy_func(dp[idx]))
+            for idx in self._coords_index:
+                coords = copy_func(dp[idx])
+                validate_coords(coords)
+                dp[idx] = tfms.apply_coords(coords)
+            return dp
+
 
 try:
     import cv2