tesseract - How to save dpi info in py-opencv?

Question

import cv2

def clear(img):
    back = cv2.imread("back.png", cv2.IMREAD_GRAYSCALE)
    img = cv2.bitwise_xor(img, back)
    ret, img = cv2.threshold(img, 120, 255, cv2.THRESH_BINARY_INV)
    return img


def threshold(img):
    ret, img = cv2.threshold(img, 120, 255, cv2.THRESH_BINARY_INV)
    img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    ret, img = cv2.threshold(img, 248, 255, cv2.THRESH_BINARY)
    return img


def fomatImage(img):
    img = threshold(img)
    img = clear(img)
    return img


img = fomatImage(cv2.imread("1566135246468.png",cv2.IMREAD_COLOR))
cv2.imwrite("aa.png",img)

This is my code. But when I tried to identify it with tesseract-ocr, I got a warning.

Warning: Invalid resolution 0 dpi. Using 70 instead.

How should I set up dpi?

Answer 1

AFAIK, OpenCV doesn't set the dpi of PNG files it writes, so you are looking at work-arounds. Here are some ideas...

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Method 1 - Use PIL/Pillow instead of OpenCV

PIL/Pillow can write dpi information into PNG files. So you would:

Step 1 - Convert your BGR OpenCV image into RGB to match PIL's channel ordering

from PIL import Image
RGBimage = cv2.cvtColor(BGRimage, cv2.COLOR_BGR2RGB)

Step 2 - Convert OpenCV Numpy array onto PIL Image

PILimage = Image.fromarray(RGBimage)

Step 3 - Write with PIL

PILimage.save('result.png', dpi=(72,72))

As Fred mentions in the comments, you could equally use Python Wand in much the same way.

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Method 2 - Write with OpenCV but modify afterwards with some tool

You could use Python's subprocess module to shell out to, say, ImageMagick and set the dpi like this:

magick OpenCVImage.png -set units pixelspercentimeter -density 28.3 result.png

All you need to know is that PNG uses metric (dots per centimetre) rather than imperial (dots per inch) and there are 2.54cm in an inch, so 72 dpi becomes 28.3 dots per cm.

If your ImageMagick version is older than v7, replace magick with convert.

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Method 3 - Write with OpenCV and insert dpi yourself

You could write your file to memory using OpenCV's imencode(). Then search in the file for the IDAT (image data) chunk - which is the one containing the image pixels and insert a pHYs chunk before that which sets the density. Then write to disk.

It's not that hard actually - it's just 9 bytes, see here and also look at pngcheck output at end of answer.

This code is not production tested but seems to work pretty well for me:

#!/usr/bin/env python3

import struct
import numpy as np
import cv2
import zlib

def writePNGwithdpi(im, filename, dpi=(72,72)):
   """Save the image as PNG with embedded dpi"""

   # Encode as PNG into memory
   retval, buffer = cv2.imencode(".png", im)
   s = buffer.tostring()

   # Find start of IDAT chunk
   IDAToffset = s.find(b'IDAT') - 4

   # Create our lovely new pHYs chunk - https://www.w3.org/TR/2003/REC-PNG-20031110/#11pHYs
   pHYs = b'pHYs' + struct.pack('!IIc',int(dpi[0]/0.0254),int(dpi[1]/0.0254),b"x01" ) 
   pHYs = struct.pack('!I',9) + pHYs + struct.pack('!I',zlib.crc32(pHYs))

   # Open output filename and write...
   # ... stuff preceding IDAT as created by OpenCV
   # ... new pHYs as created by us above
   # ... IDAT onwards as created by OpenCV
   with open(filename, "wb") as out:
      out.write(buffer[0:IDAToffset])
      out.write(pHYs)
      out.write(buffer[IDAToffset:])

################################################################################
# main
################################################################################

# Load sample image
im = cv2.imread('lena.png')

# Save at specific dpi
writePNGwithdpi(im, "result.png", (32,300))

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Whichever method you use, you can use pngcheck --v image.png to check what you have done:

pngcheck -vv a.png

Sample Output

File: a.png (306 bytes)
  chunk IHDR at offset 0x0000c, length 13
    100 x 100 image, 1-bit palette, non-interlaced
  chunk gAMA at offset 0x00025, length 4: 0.45455
  chunk cHRM at offset 0x00035, length 32
    White x = 0.3127 y = 0.329,  Red x = 0.64 y = 0.33
    Green x = 0.3 y = 0.6,  Blue x = 0.15 y = 0.06
  chunk PLTE at offset 0x00061, length 6: 2 palette entries
  chunk bKGD at offset 0x00073, length 1
    index = 1
  chunk pHYs at offset 0x00080, length 9: 255x255 pixels/unit (1:1). <-- THIS SETS THE DENSITY
  chunk tIME at offset 0x00095, length 7: 19 Aug 2019 10:15:00 UTC
  chunk IDAT at offset 0x000a8, length 20
    zlib: deflated, 2K window, maximum compression
    row filters (0 none, 1 sub, 2 up, 3 avg, 4 paeth):
      0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
      0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
      0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
      0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
      (100 out of 100)
  chunk tEXt at offset 0x000c8, length 37, keyword: date:create
  chunk tEXt at offset 0x000f9, length 37, keyword: date:modify
  chunk IEND at offset 0x0012a, length 0
No errors detected in a.png (11 chunks, 76.5% compression).

---

While I am editing PNG chunks, I also managed to set a tIME chunk and a tEXt chunk with the Author. They go like this:

# Create a new tIME chunk - https://www.w3.org/TR/2003/REC-PNG-20031110/#11tIME
year, month, day, hour, min, sec = 2020, 12, 25, 12, 0, 0    # Midday Christmas day 2020
tIME = b'tIME' + struct.pack('!HBBBBB',year,month,day,hour,min,sec)
tIME = struct.pack('!I',7) + tIME + struct.pack('!I',zlib.crc32(tIME))

# Create a new tEXt chunk - https://www.w3.org/TR/2003/REC-PNG-20031110/#11tEXt
Author = "Authorx00Sir Mark The Great"
tEXt = b'tEXt' + bytes(Author.encode('ascii'))
tEXt = struct.pack('!I',len(Author)) + tEXt + struct.pack('!I',zlib.crc32(tEXt))

# Open output filename and write...
# ... stuff preceding IDAT as created by OpenCV
# ... new pHYs as created by us above
# ... new tIME as created by us above
# ... new tEXt as created by us above 
# ... IDAT onwards as created by OpenCV
with open(filename, "wb") as out:
   out.write(buffer[0:IDAToffset])
   out.write(pHYs)
   out.write(tIME)
   out.write(tEXt)
   out.write(buffer[IDAToffset:])

Keywords: OpenCV, PIL, Pillow, dpi, density, imwrite, PNG, chunks, pHYs chunk, Python, image, image-processing, tEXt chunk, tIME chunk, author, comment