markup/img.py: cleanup

markup/img.py

@@ -1,6 +1,4 @@
-#from __future__ import absolute_import, unicode_literals
+import os
-
-import sys, os.path, re, json, pickle, subprocess
 import shutil
 
 from PIL import Image, ImageFilter
@@ -27,83 +25,55 @@ def find_shapes(image_path):
         return None
 
     alpha_layer = img.convert('RGBA').split()[-1]
-    
+
     alpha_layer = alpha_layer.filter(ImageFilter.GaussianBlur(5))
-    
+
     threshold = 5
     alpha_layer = alpha_layer.point(lambda p: p > threshold and 255)
-
     threshold = numpy.array(alpha_layer)
 
-    #bnw = Image.new('RGBA', img.size, (255, 255, 255))
+    # alternate method
-    #src = cv2.imread(image_path)
+    # blurred = cv2.GaussianBlur(gray, (5, 5), 0)
-
+    # thresh = cv2.threshold(blurred, 60, 255, cv2.THRESH_BINARY)[1]
-    # TODO just get alpha, 1 bit
-    #threshold = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
-    #threshold = cv2.blur(threshold, (4,4))
 
     thresh_path = str(path.with_suffix('.thresh.png'))
-    print('write to', thresh_path)
+    # print('write to', thresh_path)
     cv2.imwrite(thresh_path, threshold)
+    os.chmod(thresh_path, 0o664)
+    shutil.chown(thresh_path, group='procat')
 
-    # find all the 'not black' shapes in the image
+    contours = cv2.findContours(threshold, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-    # upper = np.array([255, 255, 255])
-    # lower = np.array([15, 15, 15])
-    # shapeMask = cv2.inRange(image, lower, upper)
-
-    # # alternate to below:
-    # #imgray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-    # #ret, thresh = cv2.threshold(imgray, 127, 255, 0)
-    # #im2, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
-    # #cv2.imshow('Thresh', thresh)
-    # #cv2.waitKey(0)
-
-    #threshold = 100
-    #canny_output = cv2.Canny(threshold, threshold, threshold * 2)
-    #contours = cv2.findContours(canny_output, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
-    contours = cv2.findContours(threshold, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
-    #print("contours: {}".format(contours))
-
-    # find the contours in the mask
-    #contours = cv2.findContours(shapeMask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-    #contours = cv2.findContours(shapeMask.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
     contours = imutils.grab_contours(contours)
-    print("{} shapes".format(len(contours)))
+    # print("{} shapes".format(len(contours)))
-    #cv2.imshow("Mask", shapeMask)
 
-    # Find the convex hull object for each contour
+    bboxes = []
-    hull_list = []
-    #for i in range(len(contours)):
     for c in contours:
-        hull = cv2.convexHull(c)
+        # bounding rect
-        hull_list.append(hull)
+        x, y, w, h = cv2.boundingRect(c)
+        # essentially center of mass
+        # NOT center of the bbox!
+        # M = cv2.moments(c)
+        # if M["m00"] == 0: M["m00"] = 0.00001
+        # cX = int(M["m10"] / M["m00"])
+        # cY = int(M["m01"] / M["m00"])
+        bboxes.append({'x': x, 'y': y, 'w': w, 'h': h})
 
-    # Draw contours + hull results
+    # draw contours
-    #contour_image = shapeMask.copy() # np.zeros((shapeMask.shape[0], shapeMask.shape[1], 3), dtype=numpy.uint8)
     contour_image = numpy.zeros((threshold.shape[0], threshold.shape[1], 3), dtype=numpy.uint8)
     for i in range(len(contours)):
         # compute the center of the contour
-        M = cv2.moments(contours[i])
-        if M["m00"] == 0: M["m00"] = 0.00001
-        cX = int(M["m10"] / M["m00"])
-        cY = int(M["m01"] / M["m00"])
         color = (rng.randint(0,512), rng.randint(0,512), rng.randint(0,512))
         cv2.drawContours(contour_image, contours, i, color)
-        #cv2.drawContours(contour_image, hull_list, i, color)
+        box = bboxes[i]
-        x, y, w, h = cv2.boundingRect(contours[i])
+        cv2.rectangle(contour_image, (box['x'],box['y']), (box['x']+box['w'],box['y']+box['h']), color, 1)
-        cv2.rectangle(contour_image, (x,y), (x+w,y+h), color, 1)
+        # cv2.circle(contour_image, (cX, cY), 2, color, -1)
-        cv2.circle(contour_image, (cX, cY), 2, color, -1)
         # cv2.putText(contour_image, "center", (cX - 20, cY - 15),
         #             cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 1)
 
     contour_path = str(path.with_suffix('.contour.png'))
-    print('write to', contour_path)
+    #print('write to', contour_path)
     cv2.imwrite(contour_path, contour_image)
+    os.chmod(contour_path, 0o664)
+    shutil.chown(contour_path, group='procat')
 
-    # for c in contours:
+    return bboxes
-    #     #print json.dumps(c)
-    #     print(dumper.dump(c))
-    #     # draw the contour and show it
-    #     # cv2.drawContours(image, [c], -1, (0, 255, 0), 2)
-    #     # cv2.imshow("Image", image)
-    #     # cv2.waitKey(0)

markup/work/test_scribble.py

@@ -32,7 +32,8 @@ def main(argv):
     for (k, v) in opts:
         if k == '-d': debug += 1
 
-    find_shapes(args[0])
+    boxes = find_shapes(args[0])
+    print(boxes)
 
 
 if __name__ == '__main__': sys.exit(main(sys.argv))