add image_threshold.py

edge_detection/image_threshold.py

@@ -0,0 +1,40 @@
+#!/usr/bin/python
+#coding=utf8
+
+# 图像二值化工具
+
+from tensorflow import flags
+from skimage import color
+from skimage import io
+from skimage import transform
+import numpy as np
+from skimage import filters
+import os
+
+flags.DEFINE_string('input_img', '',
+                    'input image.')
+flags.DEFINE_string('output_img', '',
+                    'output image.')
+
+FLAGS = flags.FLAGS
+
+if not os.path.exists(FLAGS.input_img):
+    print('--input_img invalid')
+    exit()
+
+if FLAGS.output_img == '':
+    print('--output_img invalid')
+    exit()
+
+
+def threshold(ann_path, save_path):
+    img = io.imread(ann_path, mode='RGB')
+    img = color.rgb2gray(img)
+    thresh = filters.threshold_otsu(img)
+    img = np.where(img > thresh, [255], [0])
+    img = np.clip(img, 0, 255).astype(np.uint8)
+    io.imsave(save_path, img)
+
+
+if __name__ == '__main__':
+    threshold(FLAGS.input_img, FLAGS.output_img)

edge_detection/simple_maker.py

@@ -0,0 +1,31 @@
+from tensorflow import flags
+from skimage import color
+from skimage import io
+from skimage import transform
+import numpy as np
+from skimage import filters
+import os
+import math
+
+# todo
+
+if __name__ == '__main__':
+    background = io.imread('make_test/background.jpg')
+    background_shape = background.shape
+    background_width = background_shape[0]
+    background_height = background_shape[1]
+
+    rect = io.imread('make_test/rect.png')
+    rect_shape = rect.shape
+    rect_width = rect_shape[0]
+    rect_height = rect_shape[1]
+
+    src = np.array([[0, 0], [400, 400], [800, 400], [400, 0]])
+    dst = np.array([[0, 0], [0, rect_height], [rect_width, rect_height], [rect_width, 0]])
+
+    tform3 = transform.ProjectiveTransform()
+    tform3.estimate(src, dst)
+
+    warped = transform.warp(rect, tform3, output_shape=(background_width, background_height))
+
+    io.imsave('make_test/rect_tr.png', warped)

edge_detection/util.py

@@ -7,7 +7,6 @@
 
 import scipy.misc
 import numpy as np
-from skimage import color
 
 
 def save_img(out_path, img):
@@ -28,15 +27,3 @@ def load_sample_from_csv(csv_file):
     return images, annotations
 
 
-def threshold(ann_path, hold):
-    # shutil.copy(ann_path, '{}.backup'.format(ann_path))
-    img = scipy.misc.imread(ann_path, mode='RGB')
-    img = color.rgb2gray(img)
-    img = np.where(img > hold, [255], [0])
-    save_img(ann_path+"_threshold.jpg", img)
-
-
-if __name__ == '__main__':
-    ann_file = './test_image/annotation_IMG_20190704_143127.png'
-    threshold(ann_file, 0.5)
-