fix upsample

examples/FasterRCNN/config.py

@@ -25,7 +25,7 @@ WARMUP = 1000    # in steps
 STEPS_PER_EPOCH = 500
 LR_SCHEDULE = [150000, 230000, 280000]
 LR_SCHEDULE = [120000, 160000, 180000]    # "1x" schedule in detectron
-# LR_SCHEDULE = [240000, 320000, 360000]    # "2x" schedule in detectron
+#LR_SCHEDULE = [240000, 320000, 360000]    # "2x" schedule in detectron
 
 # image resolution --------------------
 SHORT_EDGE_SIZE = 800
@@ -75,5 +75,5 @@ MODE_FPN = True
 FPN_NUM_CHANNEL = 256
 FASTRCNN_FC_HEAD_DIM = 1024
 FPN_RESOLUTION_REQUIREMENT = 32
-TRAIN_FPN_NMS_TOPK = 2048
-TEST_FPN_NMS_TOPK = 1024
+TRAIN_FPN_NMS_TOPK = 2000
+TEST_FPN_NMS_TOPK = 1000

examples/FasterRCNN/data.py

@@ -8,7 +8,7 @@ import itertools
 
 from tensorpack.utils.argtools import memoized, log_once
 from tensorpack.dataflow import (
-    imgaug, TestDataSpeed, PrefetchDataZMQ, MapData,
+    imgaug, TestDataSpeed, PrefetchDataZMQ, MapData, MultiProcessMapDataZMQ,
     MapDataComponent, DataFromList)
 # import tensorpack.utils.viz as tpviz
 
@@ -341,8 +341,8 @@ def get_train_dataflow(add_mask=False):
             # tpviz.interactive_imshow(viz)
         return ret
 
-    ds = MapData(ds, preprocess)
-    ds = PrefetchDataZMQ(ds, 3)
+    ds = MultiProcessMapDataZMQ(ds, 5, preprocess)
+    #ds = PrefetchDataZMQ(ds, 3)
     return ds
 
 

examples/FasterRCNN/model.py

@@ -578,7 +578,12 @@ def fpn_model(features):
 
     def upsample2x(name, x):
         # TODO may not be optimal in speed or math
-        return FixedUnPooling(name, x, 2, data_format='channels_first')
+        with tf.name_scope(name):
+            shape2d = tf.shape(x)[2:]
+            x = tf.transpose(x, [0, 2, 3, 1])
+            x = tf.image.resize_nearest_neighbor(x, shape2d * 2, align_corners=True)
+            x = tf.transpose(x, [0, 3, 1, 2])
+            return x
 
     with argscope(Conv2D, data_format='channels_first',
                   nl=tf.identity, use_bias=True,
@@ -590,7 +595,7 @@ def fpn_model(features):
             if idx == 0:
                 lat_sum_5432.append(lat)
             else:
-                lat = lat + upsample2x('upsample_c{}'.format(5 - idx), lat_sum_5432[-1])
+                lat = lat + upsample2x('upsample_lat{}'.format(6 - idx), lat_sum_5432[-1])
                 lat_sum_5432.append(lat)
         p2345 = [Conv2D('posthoc_3x3_p{}'.format(i + 2), c, num_channel, 3)
                  for i, c in enumerate(lat_sum_5432[::-1])]