simple fix for python3 support in caffe original python scripts

Author: vera121

data/ILSVRC2016/create_list.py

@@ -48,7 +48,7 @@
                 img_files.append(img_file)
                 anno_files.append(anno_file)
     # Shuffle the images.
-    idx = [i for i in xrange(len(img_files))]
+    idx = [i for i in range(len(img_files))]
     shuffle(idx)
     with open(train_list_file, "w") as f:
         for i in idx:
@@ -71,15 +71,15 @@
                 img_files.append(img_file)
                 anno_files.append(anno_file)
     with open(val_list_file, "w") as f:
-        for i in xrange(len(img_files)):
+        for i in range(len(img_files)):
             f.write("{} {}\n".format(img_files[i], anno_files[i]))
 
 if redo or not os.path.exists(val_name_size_file):
     dataset = 'val2'
     imgset_file = "{}/{}/{}.txt".format(data_dir, imgset_dir, dataset)
     cmd = "{}/../../build/tools/get_image_size --name_id_file={} {} {} {}".format(
             CURDIR, imgset_file, data_dir, val_list_file, val_name_size_file)
-    print cmd
+    print(cmd)
     process = subprocess.Popen(cmd.split(), stdout=subprocess.PIPE)
     output = process.communicate()[0]
 
@@ -96,14 +96,14 @@
                 assert os.path.exists("{}/{}".format(data_dir, img_file))
                 img_files.append(img_file)
     with open(test_list_file, "w") as f:
-        for i in xrange(len(img_files)):
+        for i in range(len(img_files)):
             f.write("{} 0\n".format(img_files[i]))
 
 if redo or not os.path.exists(test_name_size_file):
     dataset = 'test'
     imgset_file = "{}/{}/{}.txt".format(data_dir, imgset_dir, dataset)
     cmd = "{}/../../build/tools/get_image_size --name_id_file={} {} {} {}".format(
             CURDIR, imgset_file, data_dir, test_list_file, test_name_size_file)
-    print cmd
+    print(cmd)
     process = subprocess.Popen(cmd.split(), stdout=subprocess.PIPE)
     output = process.communicate()[0]

examples/pycaffe/layers/pascal_multilabel_datalayers.py

@@ -100,8 +100,8 @@ def __init__(self, params, result):
         # this class does some simple data-manipulations
         self.transformer = SimpleTransformer()
 
-        print "BatchLoader initialized with {} images".format(
-            len(self.indexlist))
+        print("BatchLoader initialized with {} images".format(
+            len(self.indexlist)))
 
     def load_next_image(self):
         """
@@ -153,7 +153,7 @@ def load_pascal_annotation(index, pascal_root):
                          'cow', 'diningtable', 'dog', 'horse',
                          'motorbike', 'person', 'pottedplant',
                          'sheep', 'sofa', 'train', 'tvmonitor')
-    class_to_ind = dict(zip(classes, xrange(21)))
+    class_to_ind = dict(zip(classes, range(21)))
 
     filename = osp.join(pascal_root, 'Annotations', index + '.xml')
     # print 'Loading: {}'.format(filename)
@@ -209,8 +209,8 @@ def print_info(name, params):
     """
     Output some info regarding the class
     """
-    print "{} initialized for split: {}, with bs: {}, im_shape: {}.".format(
+    print("{} initialized for split: {}, with bs: {}, im_shape: {}.".format(
         name,
         params['split'],
         params['batch_size'],
-        params['im_shape'])
+        params['im_shape']))

examples/ssd/plot_detections.py

@@ -24,7 +24,7 @@ def get_labelname(labelmap, labels):
         labels = [labels]
     for label in labels:
         found = False
-        for i in xrange(0, num_labels):
+        for i in range(0, num_labels):
             if label == labelmap.item[i].label:
                 found = True
                 labelnames.append(labelmap.item[i].display_name)
@@ -34,7 +34,7 @@ def get_labelname(labelmap, labels):
 
 def showResults(img_file, results, labelmap=None, threshold=None, display=None):
     if not os.path.exists(img_file):
-        print "{} does not exist".format(img_file)
+        print("{} does not exist".format(img_file))
         return
     img = io.imread(img_file)
     plt.clf()
@@ -90,7 +90,7 @@ def showResults(img_file, results, labelmap=None, threshold=None, display=None):
     result_file = args.resultfile
     img_dir = args.imgdir
     if not os.path.exists(img_dir):
-        print "{} does not exist".format(img_dir)
+        print("{} does not exist".format(img_dir))
         sys.exit()
     labelmap_file = args.labelmap_file
     labelmap = None
@@ -120,5 +120,5 @@ def showResults(img_file, results, labelmap=None, threshold=None, display=None):
                 img_results[img_file] = [result]
             else:
                 img_results[img_file].append(result)
-    for img_file, results in img_results.iteritems():
+    for img_file, results in img_results.items():
         showResults(img_file, results, labelmap, visualize_threshold, display_classes)

examples/ssd/score_ssd_coco.py

@@ -323,7 +323,7 @@ def AddExtraLayers(net, use_batchnorm=True, lr_mult=1):
 step = int(math.floor((max_ratio - min_ratio) / (len(mbox_source_layers) - 2)))
 min_sizes = []
 max_sizes = []
-for ratio in xrange(min_ratio, max_ratio + 1, step):
+for ratio in range(min_ratio, max_ratio + 1, step):
   min_sizes.append(min_dim * ratio / 100.)
   max_sizes.append(min_dim * (ratio + step) / 100.)
 min_sizes = [min_dim * 7 / 100.] + min_sizes

examples/ssd/score_ssd_pascal.py

@@ -321,7 +321,7 @@ def AddExtraLayers(net, use_batchnorm=True, lr_mult=1):
 step = int(math.floor((max_ratio - min_ratio) / (len(mbox_source_layers) - 2)))
 min_sizes = []
 max_sizes = []
-for ratio in xrange(min_ratio, max_ratio + 1, step):
+for ratio in range(min_ratio, max_ratio + 1, step):
   min_sizes.append(min_dim * ratio / 100.)
   max_sizes.append(min_dim * (ratio + step) / 100.)
 min_sizes = [min_dim * 10 / 100.] + min_sizes

examples/ssd/ssd_coco.py

@@ -312,7 +312,7 @@ def AddExtraLayers(net, use_batchnorm=True, lr_mult=1):
 step = int(math.floor((max_ratio - min_ratio) / (len(mbox_source_layers) - 2)))
 min_sizes = []
 max_sizes = []
-for ratio in xrange(min_ratio, max_ratio + 1, step):
+for ratio in range(min_ratio, max_ratio + 1, step):
   min_sizes.append(min_dim * ratio / 100.)
   max_sizes.append(min_dim * (ratio + step) / 100.)
 min_sizes = [min_dim * 7 / 100.] + min_sizes

examples/ssd/ssd_detect.py

@@ -26,7 +26,7 @@ def get_labelname(labelmap, labels):
         labels = [labels]
     for label in labels:
         found = False
-        for i in xrange(0, num_labels):
+        for i in range(0, num_labels):
             if label == labelmap.item[i].label:
                 found = True
                 labelnames.append(labelmap.item[i].display_name)
@@ -94,7 +94,7 @@ def detect(self, image_file, conf_thresh=0.5, topn=5):
         top_ymax = det_ymax[top_indices]
 
         result = []
-        for i in xrange(min(topn, top_conf.shape[0])):
+        for i in range(min(topn, top_conf.shape[0])):
             xmin = top_xmin[i] # xmin = int(round(top_xmin[i] * image.shape[1]))
             ymin = top_ymin[i] # ymin = int(round(top_ymin[i] * image.shape[0]))
             xmax = top_xmax[i] # xmax = int(round(top_xmax[i] * image.shape[1]))
@@ -111,22 +111,22 @@ def main(args):
                                args.model_def, args.model_weights,
                                args.image_resize, args.labelmap_file)
     result = detection.detect(args.image_file)
-    print result
+    print(result)
 
     img = Image.open(args.image_file)
     draw = ImageDraw.Draw(img)
     width, height = img.size
-    print width, height
+    print(width, height)
     for item in result:
         xmin = int(round(item[0] * width))
         ymin = int(round(item[1] * height))
         xmax = int(round(item[2] * width))
         ymax = int(round(item[3] * height))
         draw.rectangle([xmin, ymin, xmax, ymax], outline=(255, 0, 0))
         draw.text([xmin, ymin], item[-1] + str(item[-2]), (0, 0, 255))
-        print item
-        print [xmin, ymin, xmax, ymax]
-        print [xmin, ymin], item[-1]
+        print(item)
+        print([xmin, ymin, xmax, ymax])
+        print([xmin, ymin], item[-1])
     img.save('detect_result.jpg')
 
 

examples/ssd/ssd_ilsvrc.py

@@ -312,7 +312,7 @@ def AddExtraLayers(net, use_batchnorm=True, lr_mult=1):
 step = int(math.floor((max_ratio - min_ratio) / (len(mbox_source_layers) - 2)))
 min_sizes = []
 max_sizes = []
-for ratio in xrange(min_ratio, max_ratio + 1, step):
+for ratio in range(min_ratio, max_ratio + 1, step):
   min_sizes.append(min_dim * ratio / 100.)
   max_sizes.append(min_dim * (ratio + step) / 100.)
 min_sizes = [min_dim * 10 / 100.] + min_sizes

examples/ssd/ssd_pascal.py

@@ -310,7 +310,7 @@ def AddExtraLayers(net, use_batchnorm=True, lr_mult=1):
 step = int(math.floor((max_ratio - min_ratio) / (len(mbox_source_layers) - 2)))
 min_sizes = []
 max_sizes = []
-for ratio in xrange(min_ratio, max_ratio + 1, step):
+for ratio in range(min_ratio, max_ratio + 1, step):
   min_sizes.append(min_dim * ratio / 100.)
   max_sizes.append(min_dim * (ratio + step) / 100.)
 min_sizes = [min_dim * 10 / 100.] + min_sizes

examples/ssd/ssd_pascal_orig.py

@@ -315,7 +315,7 @@ def AddExtraLayers(net, use_batchnorm=True, lr_mult=1):
 step = int(math.floor((max_ratio - min_ratio) / (len(mbox_source_layers) - 2)))
 min_sizes = []
 max_sizes = []
-for ratio in xrange(min_ratio, max_ratio + 1, step):
+for ratio in range(min_ratio, max_ratio + 1, step):
   min_sizes.append(min_dim * ratio / 100.)
   max_sizes.append(min_dim * (ratio + step) / 100.)
 min_sizes = [min_dim * 10 / 100.] + min_sizes