Create preprocessing file for images

Author: ashwin2000

preprocessing.py

@@ -0,0 +1,64 @@
+import numpy as np
+import cv2
+from scipy import ndimage
+import math
+
+def getBestShift(img):
+    cy,cx = ndimage.measurements.center_of_mass(img)
+
+    rows,cols = img.shape
+    shiftx = np.round(cols/2.0-cx).astype(int)
+    shifty = np.round(rows/2.0-cy).astype(int)
+
+    return shiftx,shifty
+    
+def shift(img,sx,sy):
+    rows,cols = img.shape
+    M = np.float32([[1,0,sx],[0,1,sy]])
+    shifted = cv2.warpAffine(img,M,(cols,rows))
+    return shifted
+
+
+
+def preprocess(img):
+    img=255-np.array(img).reshape(28,28).astype(np.uint8)
+    (thresh, gray) = cv2.threshold(img, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
+
+    while np.sum(gray[0]) == 0:
+        gray = gray[1:]
+
+    while np.sum(gray[:,0]) == 0:
+        gray = np.delete(gray,0,1)
+
+    while np.sum(gray[-1]) == 0:
+        gray = gray[:-1]
+
+    while np.sum(gray[:,-1]) == 0:
+        gray = np.delete(gray,-1,1)
+
+    rows,cols = gray.shape
+
+    if rows > cols:
+        factor = 20.0/rows
+        rows = 20
+        cols = int(round(cols*factor))
+        gray = cv2.resize(gray, (cols,rows))
+    else:
+        factor = 20.0/cols
+        cols = 20
+        rows = int(round(rows*factor))
+        gray = cv2.resize(gray, (cols, rows))
+
+    colsPadding = (int(math.ceil((28-cols)/2.0)),int(math.floor((28-cols)/2.0)))
+    rowsPadding = (int(math.ceil((28-rows)/2.0)),int(math.floor((28-rows)/2.0)))
+    gray = np.lib.pad(gray,(rowsPadding,colsPadding),'constant')
+
+    shiftx,shifty = getBestShift(gray)
+    shifted = shift(gray,shiftx,shifty)
+    gray = shifted
+
+    img = gray.reshape(1,28,28).astype(np.float32)
+
+    img-= int(33.3952)
+    img/= int(78.6662)
+    return img