如何保存与其他图像具有相同属性的图像 [英] How to save an image with the same properties as a different image

问题描述

我想使用特定图像的属性，例如:

I want to use the properties of a specific image, for example:

t0 = cv2.cvtColor(cv2.imread('original.jpg'), cv2.COLOR_BGR2RGB)

并保存具有相同属性的新图像.

and save a new image with the same properties.

重述我的问题:

我想以与'原始'相同的dpi，尺寸，颜色属性(RGB/BGR/GRAYSCALE)等保存'new_image'

I want to save 'new_image' with the same dpi, dimensions, color properties (RGB/BGR/GRAYSCALE), etc. as 'original'

original = cv2.cvtColor(cv2.imread('original.jpg'), cv2.COLOR_BGR2RGB)
new_image = cv2.cvtColor(cv2.imread('new.jpg'), cv2.COLOR_BGR2RGB)

如何通过opencv或matplotlib做到这一点?

How can I do it via opencv or matplotlib?

推荐答案

AFAIK，使用 OpenCV 编写JPEG时无法设置dpi，因此您可以"shell out"；使用 cv2.imwrite()写入图像后，使用Python的 subprocess 命令将转换为 exiftool :

AFAIK, you cannot set the dpi when writing a JPEG with OpenCV, so you could maybe "shell out" to exiftool with Python's subprocess command after writing the image with cv2.imwrite():

exiftool -jfif:Xresolution=301 -jfif:Yresolution=302 result.jpg

---

作为替代方案，这是一个相当讨厌的黑客，可以覆盖由 OpenCV 生成的JPEG文件中的dpi，x分辨率和y分辨率:

---

As an alternative, this is a rather nasty hack to overwrite the dpi and x-resolution and y-resolution in a JPEG file generated by OpenCV:

#!/usr/bin/env python3

import struct
import numpy as np
import cv2

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

   # Encode as JPEG into memory
   retval, buffer = cv2.imencode(".jpg", im)
   s = bytearray(buffer)

   # APP0 segment looks like this
   # 0xFF, 0xE0,                     // APP0 segment
   # 0x00, 0x10,                     // size of segment, including these 2 bytes; 0x10 = 16 bytes
   # 0x4A, 0x46, 0x49, 0x46, 0x00,   // identifier string: "JFIF"
   # 0x01, 0x01,                     // JFIF version 1.01
   # 0x00,                           // density units (0=no units, 1=dpi)
   # 0x00, 0x01,                     // horizontal density
   # 0x00, 0x01,                     // vertical density
   # 0x00,                           // X thumbnail size
   # 0x00                            // Y thumbnail size

   # Find JFIF marker
   JFIF = s.find(b'JFIF\0')

   # Overwrite units, and x-resolution, and y-resolution 
   s[JFIF+7:JFIF+8]   = b'\x01'                                # density units = 1, i.e. dpi
   s[JFIF+8 :JFIF+10] = (dpi[0]).to_bytes(2, byteorder='big')  # 2 bytes of x-resolution
   s[JFIF+10:JFIF+12] = (dpi[1]).to_bytes(2, byteorder='big')  # 2 bytes of y-resolution

   with open(filename, "wb") as out:
      out.write(s)

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

# Load sample image
im = cv2.imread('/Users/mark/sample/images/lena.png')

# Save at specific dpi
writeJPEGwithdpi(im, "result.jpg", (77,309))

---

使用 exiftool 检查结果:

exiftool result.jpg

ExifTool Version Number         : 12.00
File Name                       : result.jpg
Directory                       : .
File Size                       : 105 kB
File Modification Date/Time     : 2021:02:08 14:48:52+00:00
File Access Date/Time           : 2021:02:08 14:48:54+00:00
File Inode Change Date/Time     : 2021:02:08 14:48:52+00:00
File Permissions                : rw-r--r--
File Type                       : JPEG
File Type Extension             : jpg
MIME Type                       : image/jpeg
JFIF Version                    : 1.01
Resolution Unit                 : inches      <--- LOOKS GOOD
X Resolution                    : 77          <--- LOOKS GOOD
Y Resolution                    : 309         <--- LOOKS GOOD
Image Width                     : 512
Image Height                    : 512
Encoding Process                : Baseline DCT, Huffman coding
Bits Per Sample                 : 8
Color Components                : 3
Y Cb Cr Sub Sampling            : YCbCr4:2:0 (2 2)
Image Size                      : 512x512
Megapixels                      : 0.262

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