push to fix the code on python3 and opencv3

.gitignore

@@ -1,2 +1,6 @@
 *.pyc
 *.swp
+
+#folder
+*/__pycache__
+data

README.md

@@ -1,3 +1,6 @@
+* Add *:
+`Modify the code to make it run sucessfully on Windows10 (python3.5+,tenforflow,opencv3)`
+
 ## YOLO_tensorflow
 
 Tensorflow implementation of [YOLO](https://arxiv.org/pdf/1506.02640.pdf), including training and test phase.

test.py

@@ -27,7 +27,7 @@ def __init__(self, net, weight_file):
         self.sess = tf.Session()
         self.sess.run(tf.global_variables_initializer())
 
-        print 'Restoring weights from: ' + self.weights_file
+        print ('Restoring weights from: ' + self.weights_file)
         self.saver = tf.train.Saver()
         self.saver.restore(self.sess, self.weights_file)
 
@@ -40,7 +40,7 @@ def draw_result(self, img, result):
             cv2.rectangle(img, (x - w, y - h), (x + w, y + h), (0, 255, 0), 2)
             cv2.rectangle(img, (x - w, y - h - 20),
                           (x + w, y - h), (125, 125, 125), -1)
-            cv2.putText(img, result[i][0] + ' : %.2f' % result[i][5], (x - w + 5, y - h - 7), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 1, cv2.CV_AA)
+            cv2.putText(img, result[i][0] + ' : %.2f' % result[i][5], (x - w + 5, y - h - 7), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 1, cv2.LINE_AA)
 
     def detect(self, img):
         img_h, img_w, _ = img.shape
@@ -169,6 +169,7 @@ def main():
     parser.add_argument('--weight_dir', default='weights', type=str)
     parser.add_argument('--data_dir', default="data", type=str)
     parser.add_argument('--gpu', default='', type=str)
+    parser.add_argument('--file_name',default="person.jpg",type=str)
     args = parser.parse_args()
 
     os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu
@@ -182,7 +183,7 @@ def main():
     # detector.camera_detector(cap)
 
     # detect from image file
-    imname = 'test/person.jpg'
+    imname = 'test/'+args.file_name
     detector.image_detector(imname)
 
 

train.py

@@ -63,7 +63,7 @@ def train(self):
         train_timer = Timer()
         load_timer = Timer()
 
-        for step in xrange(1, self.max_iter + 1):
+        for step in range(1, self.max_iter + 1):
 
             load_timer.tic()
             images, labels = self.data.get()

utils/pascal_voc.py

@@ -2,7 +2,7 @@
 import xml.etree.ElementTree as ET
 import numpy as np
 import cv2
-import cPickle
+import pickle
 import copy
 import yolo.config as cfg
 
@@ -16,7 +16,7 @@ def __init__(self, phase, rebuild=False):
         self.image_size = cfg.IMAGE_SIZE
         self.cell_size = cfg.CELL_SIZE
         self.classes = cfg.CLASSES
-        self.class_to_ind = dict(zip(self.classes, xrange(len(self.classes))))
+        self.class_to_ind = dict(zip(self.classes, range(len(self.classes))))
         self.flipped = cfg.FLIPPED
         self.phase = phase
         self.rebuild = rebuild
@@ -59,8 +59,8 @@ def prepare(self):
             for idx in range(len(gt_labels_cp)):
                 gt_labels_cp[idx]['flipped'] = True
                 gt_labels_cp[idx]['label'] = gt_labels_cp[idx]['label'][:, ::-1, :]
-                for i in xrange(self.cell_size):
-                    for j in xrange(self.cell_size):
+                for i in range(self.cell_size):
+                    for j in range(self.cell_size):
                         if gt_labels_cp[idx]['label'][i, j, 0] == 1:
                             gt_labels_cp[idx]['label'][i, j, 1] = self.image_size - 1 - gt_labels_cp[idx]['label'][i, j, 1]
             gt_labels += gt_labels_cp
@@ -74,7 +74,7 @@ def load_labels(self):
         if os.path.isfile(cache_file) and not self.rebuild:
             print('Loading gt_labels from: ' + cache_file)
             with open(cache_file, 'rb') as f:
-                gt_labels = cPickle.load(f)
+                gt_labels = pickle.load(f)
             return gt_labels
 
         print('Processing gt_labels from: ' + self.data_path)
@@ -100,7 +100,7 @@ def load_labels(self):
             gt_labels.append({'imname': imname, 'label': label, 'flipped': False})
         print('Saving gt_labels to: ' + cache_file)
         with open(cache_file, 'wb') as f:
-            cPickle.dump(gt_labels, f)
+            pickle.dump(gt_labels, f)
         return gt_labels
 
     def load_pascal_annotation(self, index):

yolo/config.py

@@ -14,8 +14,8 @@
 
 WEIGHTS_DIR = os.path.join(PASCAL_PATH, 'weight')
 
-WEIGHTS_FILE = None
-# WEIGHTS_FILE = os.path.join(DATA_PATH, 'weights', 'YOLO_small.ckpt')
+#WEIGHTS_FILE = None
+WEIGHTS_FILE = os.path.join(DATA_PATH, 'weights', 'YOLO_small.ckpt')
 
 CLASSES = ['aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus',
            'car', 'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse',
@@ -59,7 +59,7 @@
 
 STAIRCASE = True
 
-BATCH_SIZE = 45
+BATCH_SIZE = 4
 
 MAX_ITER = 15000