I am having difficulty sending a jpeg opened with cv2 to a server as bytes. The server complains that the file type is not supported. I can send it without problems using Python's "open" function, but not with OpenCV. How can I get this to work?
import cv2
path = r".\test\frame1.jpg"
with open(path, "rb") as image:
image1 = image.read()
image2 = cv2.imread(path, -1)
image2 = cv2.imencode(".jpg", image2)[1].tobytes() #also tried tostring()
print(image1 == image2)
#This prints False.
#I want it to be True or alternatively encoded in a way that the server accepts.
I want to start by getting your test case working, we will do this by using a lossless format with no compression so we are comparing apples to apples:
import cv2
path_in = r".\test\frame1.jpg"
path_temp = r".\test\frame1.bmp"
img = cv2.imread(path_in, -1)
cv2.imwrite(path_temp, img) # save in lossless format for a fair comparison
with open(path_temp, "rb") as image:
image1 = image.read()
image2 = cv2.imencode(".bmp", img)[1].tobytes() #also tried tostring()
print(image1 == image2)
#This prints True.
This is not ideal since compression is desirable for moving around bytes, but it illustrates that there is nothing inherently wrong with your encoding.
Without knowing the details of your server it is hard to know why it isn't accepting the opencv encoded images. Some suggestions are:
provide format specific encoding parameters as described in the docs, available flags are here
try different extensions
Related
import requests
from PIL import Image
url_shoes_for_choice = [
"https://content.adidas.co.in/static/Product-CM7531/Unisex_OUTDOOR_SANDALS_CM7531_1.jpg",
"https://cdn.shopify.com/s/files/1/0080/1374/2161/products/product-image-897958210_640x.jpg?v=1571713841",
"https://cdn.chamaripashoes.com/media/catalog/product/cache/9/image/9df78eab33525d08d6e5fb8d27136e95/1/_/1_8_3.jpg",
"https://ae01.alicdn.com/kf/HTB1EyKjaI_vK1Rjy0Foq6xIxVXah.jpg_q50.jpg",
"https://www.converse.com/dw/image/v2/BCZC_PRD/on/demandware.static/-/Sites-cnv-master-catalog/default/dwb9eb8c43/images/a_107/167708C_A_107X1.jpg"
]
def img():
for url in url_shoes_for_choice:
image = requests.get(url, stream=True).raw
out = Image.open(image)
out.save('image/image.jpg', 'jpg')
if __name__=="__main__":
img()
Error:
OSError: cannot identify image file <_io.BytesIO object at 0x7fa185c52d58>
The problem is that one of the images is making issues with the byte data returned by the requests.get(url, stream=True).raw, I'm not sure but I guess the data of the 3rd image is invalid byte data so instead of getting the raw data we can just fetch the content and then by using BytesIO we can fix the byte data.
I fixed one more thing from your original code, I added numbering to your images so each can be saved with different name.
from io import BytesIO
def img():
for count, url in enumerate(url_shoes_for_choice):
image = requests.get(url, stream=True)
with BytesIO(image.content) as f:
with Image.open(f) as out:
# out.show() # See the images
out.save('image/image{}.jpg'.format(count))
(Though this works fine but I'm not sure what was the main issue. If anyone knows exactly what is the issue please comment and explain.)
I opened the first link in my browser and saved the image. It's actually a webp file.
$ file Unisex_OUTDOOR_SANDALS_CM7531_1.webp
Unisex_OUTDOOR_SANDALS_CM7531_1.webp: RIFF (little-endian) data, Web/P image, VP8 encoding, 500x500, Scaling: [none]x[none], YUV color, decoders should clamp
You explicitly tell the image library that it should expect a jpg. When you remove that parameter and let it figure it out on its own using out.save('image/image.jpg') the first image successfully downloads for me.
The first two images work this way if you make sure to save each under a different name:
def img():
i = 0
for url in url_shoes_for_choice:
i+=1
image = requests.get(url, stream=True).raw
out = Image.open(image)
out.save('image{}.jpg'.format(i))
the third is a valid jpeg file, as well as the fourth, but using the JFIF standard 1.01 which I hear the first time of. I'm pretty sure you'll have to figure out support for different such filetypes.
It is worth noting that if I download the images in chrome and open those with python, nothing fails. So chrome might be adding information to the file.
The documentation of PIL/pillow explains here that you need a new enough version for animated images, but that is not your problem.
Support for animated WebP files will only be enabled if the system
WebP library is v0.5.0 or later. You can check webp animation support
at runtime by calling features.check(“webp_anim”).
I'm trying to send json dict that should contain Pillow image as one of his fields, to do that I have to convert the image to string.
I tried to use pillow function:
image.toString()
but still got it as bytes, so I tried to encode it:
buff = BytesIO()
image.save(buff, format="JPEG")
img_str = base64.b64encode(buff.getvalue())
but still got it as bytes.
How can I convert Pillow images to format that can be saved in json file?
In the comments, Mark Setchell suggests calling .decode('ascii') on the result of your b64encode call. I agree that this will work, but I think base64encoding to begin with is introducing an unnecessary extra step that complicates your code.*
Instead, I suggest directly decoding the bytes returned by image.tostring. The only complication is that the bytes object can contain values larger than 128, so you can't decode it with ascii. Try using an encoding that can handle values up to 256, such as latin1.
from PIL import Image
import json
#create sample file. You don't have to do this in your real code.
img = Image.new("RGB", (10,10), "red")
#decode.
s = img.tobytes().decode("latin1")
#serialize.
with open("outputfile.json", "w") as file:
json.dump(s, file)
(*but, to my surprise, the resulting json file is still smaller than one made with a latin1 encoding, at least for my sample file. Use your own judgement to determine whether file size or program clarity is more important.)
I use the following to exchange Pillow images via json.
import json
from PIL import Image
import numpy as np
filename = "filename.jpeg"
image = Image.open(filename)
json_data = json.dumps(np.array(image).tolist())
new_image = Image.fromarray(np.array(json.loads(json_data), dtype='uint8'))
1) I have an image that I converted to a string. It looks like this:
bytesimage = b'iVBORw0KGgoAAAANSUhEUgA.... etc etc
2) I can convert it to an 'bytesimage.png' using:
def StringToImage(self, stringname, imageoutput):
imgdata = base64.b64decode(stringname)
imagename = imageoutput
with open(imagename, 'wb') as f:
f.write(imgdata)
3) But then I want to save that image or string to memory to use in wxpython interface without needing to save the file. I have seen several related questions where the solution is using io.BytesIO, but I just cant connect the steps and both wxpython or PIL don't seem to read the bytes properly.
So to clarify:
I have a image stored in a string DONE
I can convert that to an image (if needed) but dont want to save it DONE
I need that string OR image (whichever is best) saved to memory NEEDS SOLVING
Then I want to be able to use that image in wxpython (I can open in PIL first if required)
Any help would be fantastic!
StringIO seems to be the way to go. It allows you to pass the decoded string directly to PIL.
import base64
from PIL import Image
import StringIO
# Banana emoji (JPG) as a b64 string.
b64_img_str = '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'
# Decode back to the original bytes
new_img_str = base64.b64decode(b64_img_str)
# Use StringIO to provide an in-memory buffer that we can use
# to pass the image string to PIL.
sio = StringIO.StringIO(new_img_str)
img = Image.open(sio)
# Display the image
img.show()
When importing an image I receive a different value than when I create an image. If I import the image
img = open('16x9.gif','rb')
img.read().encode('base64')
# 'R0lGODlhEAAJAIAAAAAAAAAAACH5BAEAAAAALAAAAAAQAAkAAAIKhI+py+0Po5yUFQA7\n'
But, If I create the image in cStringIO:
import cStringIO
import base64
import Image
tmp = cStringIO.StringIO()
img = Image.new('RGB', (16,9))
img.save(tmp, format='GIF', transparency=0)
base64.b64encode(tmp.getvalue())
# Response truncated for readability
# 'R0lGODdhEAAJAIcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADMAAGYAAJkAAMwAAP8AA...
The value returned by this second snippet is different and much longer than the first.
Why are my return values different and how do i get the shorter (see first) base64 value?
The difference is between those images representations is format, as your first string is a gif in 89a format, while your tmp is 87a.
>>> 'R0lGODlh'.decode('base64')
'GIF89a'
>>> 'R0lGODdh'.decode('base64')
'GIF87a'
The only related discussion on the topic I found is this: GIF89A and PIL, so it seems that PIL can load 89a format, but can't create it on his own.
As #delnan pointed out, I was not using the equivalent image.
But, in my search I found that png images return shorter base64 strings than gif images.
Closer to what was retuned from a gif that was made in photoshop.
I am streaming some data down from a webcam. When I get all of the bytes for a full image (in a string called byteString) I want to display the image using OpenCV. Done fast enough, this will "stream" video from the webcam to an OpenCV window.
Here's what I've done to set up the window:
cvNamedWindow('name of window', CV_WINDOW_AUTOSIZE)
And here's what I do when the byte string is complete:
img = cvCreateImage(IMG_SIZE,PIXEL_DEPTH,CHANNELS)
buf = ctypes.create_string_buffer(byteString)
img.imageData = ctypes.cast(buf, ctypes.POINTER(ctypes.c_byte))
cvShowImage('name of window', img)
cvWaitKey(0)
For some reason this is producing an error:
File "C:\Python26\lib\site-packages\ctypes_opencv\highgui_win32.py", line 226, in execute
return func(*args, **kwargs)
WindowsError: exception: access violation reading 0x015399E8
Does anybody know how to do what I'm trying to do / how to fix this crazy violation error?
I actually solved this problem and forgot to post the solution. Here's how I did it, though it may not be entirely robust:
I analyzed the headers coming from the MJPEG of the network camera I was doing this to, then I just read from the stream 1 byte at a time, and, when I detected that the header of the next image was also in the bytestring, I cut the last 42 bytes off (since that's the length of the header).
Then I had the bytes of the JPEG, so I simply created a new Cv Image by using the open(...) method and passing it the byte string wrapped in a StringIO class.
Tyler:
I'm not sure what you are trying to do..i have a few guesses.
if you are trying to simply read an image from a webcam connected to your pc then this code should work:
import cv
cv.NamedWindow("camera", 1)
capture = cv.CaptureFromCAM(0)
while True:
img = cv.QueryFrame(capture)
cv.ShowImage("camera", img)
if cv.WaitKey(10) == 27:
break
are you trying to stream video from an internet cam?
if so, you should check this other post:
opencv-with-network-cameras
If for some reason you cannot do it in any of these ways then may be you can just somehow savethe image on the hard drive and then load it in your opencv program by doing a simple cvLoadImage ( of course this way is much slower).
another approach would be to set the new image pixels by hand by reading each of the values from the byteString, doing something like this:
for(int x=0;x<640;x++){
for(int y=0;y<480;y++){
uchar * pixelxy=&((uchar*) (img->imageData+img->widthStep*y))[x];
*pixelxy=buf[y*img->widthStep + x];
}
}
this is also slower but faster than using the hard drive.
Anyway, hope some of this helps, you should also specify which opencv version are you using.