I have a BMP image and I want to extract a small portion of it and save it as a new BMP image file.
I was able to load image and read it however I was not able to extract the small portion of BMP image as I am new to manipulating BMP image with python and also it not same as reading text file.
Things I have to do is
load image.
extract small portion of image.
eg. I have to extract 40X40 pixel image from 900X900 image file
then save extracted image as new file. eg new.bmp
I am trying to do this for last 3 days also I have searched a lot in the net but got solution which uses Pillow library however I need it to do this without using any external module of Python. Stackoverflow is my last hope I need some guidance from a expert people present here, please provide my some guidance.
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i have a file with 300 .tif images, i want to open it with python and save them into an array, list or any similar structure. I´ve tried the code below but only appears 3 images. ¿Any solution?. Thanks.
raw = cv2.imread('sen_15Hz_500Hz_6_6A.tif')
print(np.shape(raw))
I´ve tried with PIL and cv2 too.
If you really have one single TIFF file with 300 images in it, the simplest is to open it with tifffile.
with TiffFile('temp.tif') as tif:
for page in tif.pages:
image = page.asarray()
If you want to use PIL look at the section "Image Sequences" here.
Interested in getting the raw data that is streamed from a webcam..before it is transformed into binary -> pixels or whatever the sequence is.
From my understanding, libraries like opencv won't help with this.
Edit: kiss
in order to see the image output from a webcam using python you need to convert it from raw image data (the pixels) into a image that can be displayed one way you can do it is by using matplotlib more info here https://matplotlib.org/stable/tutorials/introductory/images.html
this will display the image but will not convert it into other image formats such as .png .jpeg ext. but the data you are getting is probably pixel data which is the rawest image data you will get
Its been asked a lot of times how to resize an image and keep the existing exif data. I'm able to do that easily with PIL:
from PIL import Image
im = Image.open("image.jpeg")
exif = im.info['exif']
# process the image, for example resize:
im_resized = im.resize((1920, 1080), resample=PIL.Image.LANCZOS)
im_resized.save("resized.jpeg", quality=70, exif=exif)
I was wondering is there a way to keep the XMP metadata from the original image? There's a lot of GPS data in the XMP which I would love to keep in the resized version.
Not even the successor Pillow can read XMP (and IPTC). Also you're not really keeping anything - you create a whole new file and add a copy of the other EXIF data (including now potentially invalid information like width/height).
JFIF files aren't black magic - their file format can be parsed rather easily; XMP is most likely found in an APP1 segment (just like EXIF). In rare cases it spans over multiple segments. You could first use PIL/Pillow to create your file and then modify it - inserting additional segments is trivial and needs no additional work.
I am working on OCR problem for Bank receipts and I need to extract details like the Date and Account Number for the same. After processing the input,I am using Tessaract-OCR (using pyteserract in python) for the same.I have obtained the hocr output file however I am not able to make sense of it.How do we extract information from the HOCR output file?Note that the receipt has numbers filled in Boxes like the normal forms.
I used the below text for extraction.Should I use a different Encoding?
import os
if os.path.isfile('output.hocr'):
fp=open('output.hocr','r',encoding='UTF-8')
text=fp.read()
fp.close()
Note:The attached image is one example of data.These images are available in pdf files which I am converting programmatically into images.
I personally would use something more like tesseract to do the OCR and then perhaps something like opencv with surf for the tick boxes...
or even do edge detection with opencv and surf for each section and ocr that specific area to make it more robust by analyzing that specific area rather than the whole document..
You can simply provide the image as input, instead of processing and creating an HOCR output file.
Try:-
from PIL import Image
import pytesseract
im = Image.open("reciept.jpg")
text = pytesseract.image_to_string(im, lang = 'eng')
print(text)
This program takes in the location of your image which is to be run through OCR, and extracts text from it, stores it in a variable text, and prints it out. If you want you can store the data in text in a separate file too.
P.S.:- The Image that you are trying to process, is way too complex as compared to images that tesseract is made to deal with. Due to this you may get incorrect results, after the text is processed. I would definitely recommend you to optimize it before using, like reducing the character set used, processing the image before passing it to OCR, upsampling image, having dpi over 250 etc.
I have very picky label printer and need to convert black and white .pdf file to .tiff image saving as much quality as possible. I have an example .tiff converted using some adobe software and that's the quality I am aiming for.
Tried using graphicsmagick for the job, but I just can't get close enough. Here's a section of an image: on the left side is my try and on the right is the one converted with adobe software:
As you can see adobe converted image is much thicker but those images are of same resolution (200x400)
Can somebody give me a hint how to convert .pdf to .tiff using most common python libraries or Ubuntu packages and get similar results?
Cheers