lose rotation info using this repo

Now,i have a picture at

when i use

img = cv2.imread("cong.jpg")

the picture is been correctly displayed.But when i use

in_file = open("cong.jpg", 'rb')
img = jpeg.decode(in_file.read())
in_file.close()

the picture loses its rotation info which leads to wrong display. You can try and hope that you can fix this bug.

[lfxx]

Since numpy is not physically rotating the image in memory by simply changing the striding, if you want to get correct result after rotating, you need to call copy() before calling encode() function like below.

out_file = open('output.jpg', 'wb')
out_file.write(turbo_jpeg.encode(transposed_image.copy()))
out_file.close()

This is what i need!thank you!

[lfxx]

I assume you’re using Python 3 (not Python 2), here is a possible solution if the JPEG file is located on web server.

# This example shows how to use PyTurboJPEG with ExifRead to
# transpose an image if the image has an EXIF Orientation tag.
#
# pip install PyTurboJPEG -U
# pip install exifread -U

import cv2
import numpy as np
import exifread
import requests
from turbojpeg import TurboJPEG
from io import BytesIO

def transposeImage(image, orientation):
    """See Orientation in https://www.exif.org/Exif2-2.PDF for details."""
    if orientation == None: return image
    val = orientation.values[0]
    if val == 1: return image
    elif val == 2: return np.fliplr(image)
    elif val == 3: return np.rot90(image, 2)
    elif val == 4: return np.flipud(image)
    elif val == 5: return np.rot90(np.flipud(image), -1)
    elif val == 6: return np.rot90(image, -1)
    elif val == 7: return np.rot90(np.flipud(image))
    elif val == 8: return np.rot90(image)

# using default library installation
turbo_jpeg = TurboJPEG()
# download the jpeg file
file_content = requests.get('https://user-images.githubusercontent.com/27956643/122202251-7025a700-cecf-11eb-8f3c-f1f43a7f254f.jpg', stream=True, timeout=3600).content
# parse orientation
orientation = exifread.process_file(BytesIO(file_content)).get('Image Orientation', None)
# start to decode the JPEG file
image = turbo_jpeg.decode(file_content)
# transpose image based on EXIF Orientation tag
transposed_image = transposeImage(image, orientation)

cv2.imshow('transposed_image', transposed_image)
cv2.waitKey(0)

It works!thanks.This repo is still 1x faster than opencv though added so much ops.