import cv2
import numpy as np
from PIL import Image, ImageDraw

def dbg(arr2d):
   dbg = {}
   for x in arr2d:
     for y in x:
       dbg[y] = dbg.get(y, 0) + 1
   print(dbg)
   #return
   img = Image.new("1", (max([len(x) for x in arr2d]), len(arr2d)))
   draw = ImageDraw.Draw(img)
   for x in range(len(arr2d)):
      for y in range(len(arr2d[x])):
         draw.point( (y,x), fill=1 if arr2d[x][y] > 100 else 0)
   img.show()

def draw_boxes(arr2d, boxes):
   img = Image.new("1", (max([len(x) for x in arr2d]), len(arr2d)))
   draw = ImageDraw.Draw(img)
   for x in range(len(arr2d)):
      for y in range(len(arr2d[x])):
         draw.point( (y,x), fill=1 if arr2d[x][y] > 100 else 0)
   for box in boxes:
      x0 = box[0]
      y0 = box[1]
      x1 = box[0] + box[2]
      y1 = box[1] + box[3]
      draw.line( [(x0,y0), (x1,y0)], fill=1)
      draw.line( [(x1,y0), (x1,y1)], fill=1)
      draw.line( [(x1,y1), (x0,y1)], fill=1)
      draw.line( [(x0,y1), (x0,y0)], fill=1)
   img.show()

# Load image, convert to HSV format, define lower/upper ranges, and perform
# color segmentation to create a binary mask
image = cv2.imread('1.png')
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
lower = np.array([0, 0, 0])
upper = np.array([0, 255, 200])
mask = cv2.inRange(hsv, lower, upper)
#dbg(mask)

# Create horizontal kernel and dilate to connect text characters
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5,3))
dilate = cv2.dilate(mask, kernel, iterations=0)
#dbg(dilate)

# Find contours and filter using aspect ratio
# Remove non-text contours by filling in the contour
cnts = cv2.findContours(dilate, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
draw_boxes(dilate, [cv2.boundingRect(c) for c in cnts])
for c in cnts:
    x,y,w,h = cv2.boundingRect(c)
    ar = w / float(h)
    print(x, y, w, h)
    if ar < 5:
        cv2.drawContours(dilate, [c], -1, (0,0,0), -1)
#dbg(dilate)
exit()

# Bitwise dilated image with mask, invert, then OCR
result = 255 - cv2.bitwise_and(dilate, mask)
dbg(result)