Merge pull request jwyang#35 from cclauss/modernize-python2-code

Modernize Python 2 code to get ready for Python 3

demo.py

@@ -37,14 +37,20 @@
 from model.faster_rcnn.resnet import resnet
 import pdb
 
+try:
+    xrange          # Python 2
+except NameError:
+    xrange = range  # Python 3
+
+
 def parse_args():
   """
   Parse input arguments
   """
   parser = argparse.ArgumentParser(description='Train a Fast R-CNN network')
   parser.add_argument('--dataset', dest='dataset',
                       help='training dataset',
-                      default='pascal_voc', type=str)  
+                      default='pascal_voc', type=str)
   parser.add_argument('--cfg', dest='cfg_file',
                       help='optional config file',
                       default='cfgs/vgg16.yml', type=str)
@@ -59,7 +65,7 @@ def parse_args():
                       nargs=argparse.REMAINDER)
   parser.add_argument('--image_dir', dest='image_dir',
                       help='directory to load images for demo', default="images",
-                      nargs=argparse.REMAINDER)                      
+                      nargs=argparse.REMAINDER)
   parser.add_argument('--cuda', dest='cuda',
                       help='whether use CUDA',
                       action='store_true')
@@ -68,7 +74,7 @@ def parse_args():
                       action='store_true')
   parser.add_argument('--cag', dest='class_agnostic',
                       help='whether perform class_agnostic bbox regression',
-                      action='store_true')                      
+                      action='store_true')
   parser.add_argument('--parallel_type', dest='parallel_type',
                       help='which part of model to parallel, 0: all, 1: model before roi pooling',
                       default=0, type=int)
@@ -86,7 +92,7 @@ def parse_args():
                       default=1, type=int)
   parser.add_argument('--vis', dest='vis',
                       help='visualization mode',
-                      action='store_true')  
+                      action='store_true')
   args = parser.parse_args()
   return args
 
@@ -174,7 +180,7 @@ def _get_image_blob(im):
     pdb.set_trace()
 
   fasterRCNN.create_architecture()
-  
+
   print("load checkpoint %s" % (load_name))
   checkpoint = torch.load(load_name)
   fasterRCNN.load_state_dict(checkpoint['model'])
@@ -259,7 +265,7 @@ def _get_image_blob(im):
       rpn_loss_cls, rpn_loss_box, \
       RCNN_loss_cls, RCNN_loss_bbox, \
       rois_label = fasterRCNN(im_data, im_info, gt_boxes, num_boxes)
-      
+
       scores = cls_prob.data
       boxes = rois.data[:, :, 1:5]
 
@@ -285,7 +291,7 @@ def _get_image_blob(im):
 
       pred_boxes /= im_scales[0]
 
-      scores = scores.squeeze()    
+      scores = scores.squeeze()
       pred_boxes = pred_boxes.squeeze()
       det_toc = time.time()
       detect_time = det_toc - det_tic

lib/datasets/imagenet.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 # --------------------------------------------------------
 # Fast R-CNN
 # Copyright (c) 2015 Microsoft
@@ -17,6 +18,12 @@
 import subprocess
 import pdb
 
+try:
+    xrange          # Python 2
+except NameError:
+    xrange = range  # Python 3
+
+
 class imagenet(imdb):
     def __init__(self, image_set, devkit_path, data_path):
         imdb.__init__(self, image_set)
@@ -151,14 +158,14 @@ def gt_roidb(self):
         if os.path.exists(cache_file):
             with open(cache_file, 'rb') as fid:
                 roidb = cPickle.load(fid)
-            print '{} gt roidb loaded from {}'.format(self.name, cache_file)
+            print('{} gt roidb loaded from {}'.format(self.name, cache_file))
             return roidb
 
         gt_roidb = [self._load_imagenet_annotation(index)
                     for index in self.image_index]
         with open(cache_file, 'wb') as fid:
             cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
-        print 'wrote gt roidb to {}'.format(cache_file)
+        print('wrote gt roidb to {}'.format(cache_file))
 
         return gt_roidb
 

lib/datasets/pascal_voc.py

@@ -1,3 +1,5 @@
+from __future__ import print_function
+from __future__ import absolute_import
 # --------------------------------------------------------
 # Fast R-CNN
 # Copyright (c) 2015 Microsoft
@@ -21,13 +23,17 @@
 
 from .imdb import imdb
 from .imdb import ROOT_DIR
-import ds_utils
+from . import ds_utils
 from .voc_eval import voc_eval
 
 # TODO: make fast_rcnn irrelevant
 # >>>> obsolete, because it depends on sth outside of this project
 from model.utils.config import cfg
 
+try:
+    xrange          # Python 2
+except NameError:
+    xrange = range  # Python 3
 
 # <<<< obsolete
 
@@ -120,14 +126,14 @@ def gt_roidb(self):
         if os.path.exists(cache_file):
             with open(cache_file, 'rb') as fid:
                 roidb = cPickle.load(fid)
-            print '{} gt roidb loaded from {}'.format(self.name, cache_file)
+            print('{} gt roidb loaded from {}'.format(self.name, cache_file))
             return roidb
 
         gt_roidb = [self._load_pascal_annotation(index)
                     for index in self.image_index]
         with open(cache_file, 'wb') as fid:
             cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
-        print 'wrote gt roidb to {}'.format(cache_file)
+        print('wrote gt roidb to {}'.format(cache_file))
 
         return gt_roidb
 
@@ -144,7 +150,7 @@ def selective_search_roidb(self):
         if os.path.exists(cache_file):
             with open(cache_file, 'rb') as fid:
                 roidb = cPickle.load(fid)
-            print '{} ss roidb loaded from {}'.format(self.name, cache_file)
+            print('{} ss roidb loaded from {}'.format(self.name, cache_file))
             return roidb
 
         if int(self._year) == 2007 or self._image_set != 'test':
@@ -155,7 +161,7 @@ def selective_search_roidb(self):
             roidb = self._load_selective_search_roidb(None)
         with open(cache_file, 'wb') as fid:
             cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
-        print 'wrote ss roidb to {}'.format(cache_file)
+        print('wrote ss roidb to {}'.format(cache_file))
 
         return roidb
 
@@ -171,7 +177,7 @@ def rpn_roidb(self):
 
     def _load_rpn_roidb(self, gt_roidb):
         filename = self.config['rpn_file']
-        print 'loading {}'.format(filename)
+        print('loading {}'.format(filename))
         assert os.path.exists(filename), \
             'rpn data not found at: {}'.format(filename)
         with open(filename, 'rb') as f:
@@ -268,7 +274,7 @@ def _write_voc_results_file(self, all_boxes):
         for cls_ind, cls in enumerate(self.classes):
             if cls == '__background__':
                 continue
-            print 'Writing {} VOC results file'.format(cls)
+            print('Writing {} VOC results file'.format(cls))
             filename = self._get_voc_results_file_template().format(cls)
             with open(filename, 'wt') as f:
                 for im_ind, index in enumerate(self.image_index):
@@ -298,7 +304,7 @@ def _do_python_eval(self, output_dir='output'):
         aps = []
         # The PASCAL VOC metric changed in 2010
         use_07_metric = True if int(self._year) < 2010 else False
-        print 'VOC07 metric? ' + ('Yes' if use_07_metric else 'No')
+        print('VOC07 metric? ' + ('Yes' if use_07_metric else 'No'))
         if not os.path.isdir(output_dir):
             os.mkdir(output_dir)
         for i, cls in enumerate(self._classes):
@@ -328,9 +334,9 @@ def _do_python_eval(self, output_dir='output'):
         print('--------------------------------------------------------------')
 
     def _do_matlab_eval(self, output_dir='output'):
-        print '-----------------------------------------------------'
-        print 'Computing results with the official MATLAB eval code.'
-        print '-----------------------------------------------------'
+        print('-----------------------------------------------------')
+        print('Computing results with the official MATLAB eval code.')
+        print('-----------------------------------------------------')
         path = os.path.join(cfg.ROOT_DIR, 'lib', 'datasets',
                             'VOCdevkit-matlab-wrapper')
         cmd = 'cd {} && '.format(path)

lib/datasets/tools/mcg_munge.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 import os
 import sys
 
@@ -28,7 +29,7 @@ def munge(src_dir):
             os.makedirs(dst_dir)
         src = os.path.join(src_dir, fn)
         dst = os.path.join(dst_dir, fn)
-        print 'MV: {} -> {}'.format(src, dst)
+        print('MV: {} -> {}'.format(src, dst))
         os.rename(src, dst)
 
 if __name__ == '__main__':

lib/datasets/vg.py

@@ -1,3 +1,5 @@
+from __future__ import print_function
+from __future__ import absolute_import
 # --------------------------------------------------------
 # Fast R-CNN
 # Copyright (c) 2015 Microsoft
@@ -15,11 +17,17 @@
 import gzip
 import PIL
 import json
-from vg_eval import vg_eval
+from .vg_eval import vg_eval
 from model.utils.config import cfg
 import pickle
 import pdb
 
+try:
+    xrange          # Python 2
+except NameError:
+    xrange = range  # Python 3
+
+
 class vg(imdb):
     def __init__(self, version, image_set, ):
         imdb.__init__(self, 'vg_' + version + '_' + image_set)
@@ -121,11 +129,11 @@ def _image_split_path(self):
         if self._image_set == "minitrain":
           return os.path.join(self._data_path, 'train.txt')
         if self._image_set == "smalltrain":
-          return os.path.join(self._data_path, 'train.txt')          
+          return os.path.join(self._data_path, 'train.txt')
         if self._image_set == "minival":
           return os.path.join(self._data_path, 'val.txt')
         if self._image_set == "smallval":
-          return os.path.join(self._data_path, 'val.txt')          
+          return os.path.join(self._data_path, 'val.txt')
         else:
           return os.path.join(self._data_path, self._image_set+'.txt')
 
@@ -141,7 +149,7 @@ def _load_image_set_index(self):
           if self._image_set == "minitrain":
             metadata = metadata[:1000]
           elif self._image_set == "smalltrain":
-            metadata = metadata[:20000]            
+            metadata = metadata[:20000]
           elif self._image_set == "minival":
             metadata = metadata[:100]
           elif self._image_set == "smallval":
@@ -172,21 +180,21 @@ def gt_roidb(self):
         Return the database of ground-truth regions of interest.
 
         This function loads/saves from/to a cache file to speed up future calls.
-        """        
+        """
         cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')
         if os.path.exists(cache_file):
             fid = gzip.open(cache_file,'rb')
             roidb = cPickle.load(fid)
             fid.close()
-            print '{} gt roidb loaded from {}'.format(self.name, cache_file)
+            print('{} gt roidb loaded from {}'.format(self.name, cache_file))
             return roidb
 
         gt_roidb = [self._load_vg_annotation(index)
                     for index in self.image_index]
         fid = gzip.open(cache_file,'wb')
         cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
         fid.close()
-        print 'wrote gt roidb to {}'.format(cache_file)
+        print('wrote gt roidb to {}'.format(cache_file))
         return gt_roidb
 
     def _get_size(self, index):
@@ -227,7 +235,7 @@ def _load_vg_annotation(self, index):
                 y2 = min(height-1,float(bbox.find('ymax').text))
                 # If bboxes are not positive, just give whole image coords (there are a few examples)
                 if x2 < x1 or y2 < y1:
-                    print 'Failed bbox in %s, object %s' % (filename, obj_name)
+                    print('Failed bbox in %s, object %s' % (filename, obj_name))
                     x1 = 0
                     y1 = 0
                     x2 = width-1
@@ -312,7 +320,7 @@ def _write_voc_results_file(self, classes, all_boxes, output_dir):
         for cls_ind, cls in enumerate(classes):
             if cls == '__background__':
                 continue
-            print 'Writing "{}" vg results file'.format(cls)
+            print('Writing "{}" vg results file'.format(cls))
             filename = self._get_vg_results_file_template(output_dir).format(cls)
             with open(filename, 'wt') as f:
                 for im_ind, index in enumerate(self.image_index):
@@ -334,7 +342,7 @@ def _do_python_eval(self, output_dir, pickle=True, eval_attributes = False):
         thresh = []
         # The PASCAL VOC metric changed in 2010
         use_07_metric = False
-        print 'VOC07 metric? ' + ('Yes' if use_07_metric else 'No')
+        print('VOC07 metric? ' + ('Yes' if use_07_metric else 'No'))
         if not os.path.isdir(output_dir):
             os.mkdir(output_dir)
         # Load ground truth

lib/datasets/vg_eval.py

@@ -1,3 +1,4 @@
+from __future__ import absolute_import
 # --------------------------------------------------------
 # Fast/er R-CNN
 # Licensed under The MIT License [see LICENSE for details]
@@ -8,7 +9,7 @@
 import os
 import cPickle
 import numpy as np
-from voc_eval import voc_ap
+from .voc_eval import voc_ap
 
 
 

lib/model/nms/build.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 import os
 import torch
 from torch.utils.ffi import create_extension

lib/model/nms/nms_gpu.py

@@ -1,6 +1,7 @@
+from __future__ import absolute_import
 import torch
 import numpy as np
-from _ext import nms
+from ._ext import nms
 import pdb
 
 def nms_gpu(dets, thresh):

lib/model/roi_align/build.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 import os
 import torch
 from torch.utils.ffi import create_extension

lib/model/roi_crop/build.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 import os
 import torch
 from torch.utils.ffi import create_extension

lib/model/roi_pooling/build.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 import os
 import torch
 from torch.utils.ffi import create_extension