reformat code

ctpn/__init__.py

@@ -1,2 +1 @@
-from . import text_proposal_connector
-from . import text_connect
+

ctpn/demo.py

@@ -1,26 +1,31 @@
 from __future__ import print_function
-import tensorflow as tf
-import numpy as np
-import os, sys, cv2
+
+import cv2
 import glob
+import os
 import shutil
+import sys
+
+import numpy as np
+import tensorflow as tf
+
 sys.path.append(os.getcwd())
 from lib.networks.factory import get_network
-from lib.fast_rcnn.config import cfg,cfg_from_file
+from lib.fast_rcnn.config import cfg, cfg_from_file
 from lib.fast_rcnn.test import test_ctpn
 from lib.utils.timer import Timer
 from lib.text_connector.detectors import TextDetector
 from lib.text_connector.text_connect_cfg import Config as TextLineCfg
 
 
 def resize_im(im, scale, max_scale=None):
-    f=float(scale)/min(im.shape[0], im.shape[1])
-    if max_scale!=None and f*max(im.shape[0], im.shape[1])>max_scale:
-        f=float(max_scale)/max(im.shape[0], im.shape[1])
-    return cv2.resize(im, None,None, fx=f, fy=f,interpolation=cv2.INTER_LINEAR), f
+    f = float(scale) / min(im.shape[0], im.shape[1])
+    if max_scale != None and f * max(im.shape[0], im.shape[1]) > max_scale:
+        f = float(max_scale) / max(im.shape[0], im.shape[1])
+    return cv2.resize(im, None, None, fx=f, fy=f, interpolation=cv2.INTER_LINEAR), f
 
 
-def draw_boxes(img,image_name,boxes,scale):
+def draw_boxes(img, image_name, boxes, scale):
     base_name = image_name.split('/')[-1]
     with open('data/results/' + 'res_{}.txt'.format(base_name.split('.')[0]), 'w') as f:
         for box in boxes:
@@ -35,17 +40,18 @@ def draw_boxes(img,image_name,boxes,scale):
             cv2.line(img, (int(box[6]), int(box[7])), (int(box[2]), int(box[3])), color, 2)
             cv2.line(img, (int(box[4]), int(box[5])), (int(box[6]), int(box[7])), color, 2)
 
-            min_x = min(int(box[0]/scale),int(box[2]/scale),int(box[4]/scale),int(box[6]/scale))
-            min_y = min(int(box[1]/scale),int(box[3]/scale),int(box[5]/scale),int(box[7]/scale))
-            max_x = max(int(box[0]/scale),int(box[2]/scale),int(box[4]/scale),int(box[6]/scale))
-            max_y = max(int(box[1]/scale),int(box[3]/scale),int(box[5]/scale),int(box[7]/scale))
+            min_x = min(int(box[0] / scale), int(box[2] / scale), int(box[4] / scale), int(box[6] / scale))
+            min_y = min(int(box[1] / scale), int(box[3] / scale), int(box[5] / scale), int(box[7] / scale))
+            max_x = max(int(box[0] / scale), int(box[2] / scale), int(box[4] / scale), int(box[6] / scale))
+            max_y = max(int(box[1] / scale), int(box[3] / scale), int(box[5] / scale), int(box[7] / scale))
 
-            line = ','.join([str(min_x),str(min_y),str(max_x),str(max_y)])+'\r\n'
+            line = ','.join([str(min_x), str(min_y), str(max_x), str(max_y)]) + '\r\n'
             f.write(line)
 
-    img=cv2.resize(img, None, None, fx=1.0/scale, fy=1.0/scale, interpolation=cv2.INTER_LINEAR)
+    img = cv2.resize(img, None, None, fx=1.0 / scale, fy=1.0 / scale, interpolation=cv2.INTER_LINEAR)
     cv2.imwrite(os.path.join("data/results", base_name), img)
 
+
 def ctpn(sess, net, image_name):
     timer = Timer()
     timer.tic()
@@ -62,7 +68,6 @@ def ctpn(sess, net, image_name):
            '{:d} object proposals').format(timer.total_time, boxes.shape[0]))
 
 
-
 if __name__ == '__main__':
     if os.path.exists("data/results/"):
         shutil.rmtree("data/results/")
@@ -98,4 +103,3 @@ def ctpn(sess, net, image_name):
         print('~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~')
         print(('Demo for {:s}'.format(im_name)))
         ctpn(sess, net, im_name)
-

ctpn/demo_pb.py

@@ -1,11 +1,11 @@
 from __future__ import print_function
 
-import cv2
 import glob
 import os
 import shutil
 import sys
 
+import cv2
 import numpy as np
 import tensorflow as tf
 from tensorflow.python.platform import gfile

ctpn/generate_pb.py

@@ -1,11 +1,14 @@
 from __future__ import print_function
-from tensorflow.python.framework.graph_util import convert_variables_to_constants
+
+import os
+import sys
+
 import tensorflow as tf
-import os, sys
+from tensorflow.python.framework.graph_util import convert_variables_to_constants
+
 sys.path.append(os.getcwd())
 from lib.networks.factory import get_network
-from lib.fast_rcnn.config import cfg,cfg_from_file
-
+from lib.fast_rcnn.config import cfg, cfg_from_file
 
 if __name__ == "__main__":
     cfg_from_file('ctpn/text.yml')

ctpn/train_net.py

@@ -1,6 +1,7 @@
+import os.path
 import pprint
 import sys
-import os.path
+
 sys.path.append(os.getcwd())
 from lib.fast_rcnn.train import get_training_roidb, train_net
 from lib.fast_rcnn.config import cfg_from_file, get_output_dir, get_log_dir