i can't believe i found this amazing channel !!! I've been working on an OCR mobile app to extract fields from scanned invoices and these videos are exactly what I m looking for million thanks man !!!
Awesome! Glad you are finding them useful! I have 10 more videos planned for this series. I am getting over a cold and have not been able to post for a while.
Hey thank you so much! The video is about an hour long, so I’m really happy that your voice is so pleasant and happy to listen to! This video helped me a lot on my project.
Hi!, First thank for the tutorial. In my case I had a problem while correcting the rotated image with the function. In the link it gives you a really cool solution, if anyone had the problem just comment the line of the angle and put this lines instead and it will work perfectly. middleContour = contours[len(contours) // 2] angle = cv2.minAreaRect(middleContour)[-1] As I said it comes in the link given but this is in the case you're in a rush. Thanks for the channel and the videos for real. I would have liked to have teachers like you while I was studying!!!!
Thanks for your input. I tried every option but it'll always get -90º to -30º (aprox) rotated. Cannot find where the problem is. I'm trying with a picture of my own, like the ones I will process.
Hey, any idea why I got "ValueError: not enough values to unpack (expected 3, got 2)" at 15:43. I'm using Python3.8.2 and open-cv 4.5.1. Also, please check patron messages. Thanks!
Good question. I don't think I explained this in the video. The problem is likely from the display function with the height, width, (sometimes depth). Make sure that im_data.shape[:2] is in your display function. I updated this for GitHub so this error wouldn't pop up, but I don't think I mentioned it in the video. Here is the corrected display function: def display(im_path): dpi = 80 im_data = plt.imread(im_path) height, width = im_data.shape[:2] # What size does the figure need to be in inches to fit the image? figsize = width / float(dpi), height / float(dpi) # Create a figure of the right size with one axes that takes up the full figure fig = plt.figure(figsize=figsize) ax = fig.add_axes([0, 0, 1, 1]) # Hide spines, ticks, etc. ax.axis('off') # Display the image. ax.imshow(im_data, cmap='gray') plt.show()
@@python-programming Thank you for your response, nonetheless, I already found and fix it from SO. The point was that I didn't get the idea. Here is my current thought about it, the reason behind it is the code trying to unpack more values from an object than those that actually exist. So either we have to remove some requests or return the 'requested' value (before actually request it) to the program and then request the results. I know that this is a bit more detailed and out of the topic to appropriately fit on your video comment section but, a clarified answer would be greatly appreciated. Learn without gaps is better in the long run, don't you agree?
Precisely the problem! It was a good catch and I'm glad this comment is here. No worries about it being out of topic. I think it is very much on topic.
First I'd like to thank you for the tutorial. I have a question. In the 28th min you are talking about pros and cons of noise removal. And you said that for this particular image you wouldn't use it for stated reasons. So what if you have a thousand images you want to process with maximum rate of success. How would you then implement noise removal to those images that actually benefit from it and skip it for those that don't and would in case of using it result in worse performance?
Thanks for the comment! I'm glad you liked the video! There are a few solutions here, perhaps a small image classifier to detect those pages that have a lot of noise and flag them for manual adjustments. It likely wouldn't take many examples to train a binary model to do this. Another approach could be with Open-CV but it may take longer for some data to get that up and running effectively. It really comes down to the images you are using, though.
I get this error when trying to get the gray version of the image at 18:12 Cell In[4], line 4, in display(img_path) 2 dpi = 80 3 img_data = plt.imread(img_path) ----> 4 height, width, depth = img_data.shape 6 img_size = width / float(dpi), height/ float(dpi) 8 fig = plt.figure(figsize=img_size) ValueError: not enough values to unpack (expected 3, got 2)
Wow awesome video, totally subscribing 🙂, I would like a transparency example, as we have invoices scanning from thin paper with duplex pages bleeding through the image. I'm assuming the transparency will help?
@@python-programming hi sorry I don’t do twitter or social media. But simply put sometimes a scanner will produce an image which has some ghosting of the other side coming through
I am working through the video stack and trying to comprehend it all. Trying to develop an auto scan ocr solution of sorts. Really helpful what you and others have shared
Thank you for the very helpful tutorial. I am wondering if there is any difference between from preprocessing SCENE-TEXT dataset from OCR dataset? In my POV, BW function will not be needed in SCENE-TEXT since there is various color in an image. Thanks again.
Thanks for the video. I was having issues with the "getSkewAngle" function. I found an easy workaround though. I changed the last line "return -1.0 * angle" to just "return angle" Hope this helps anyone else with this problem.
For anyonne getting a error message when importing pylot. heres a few solutions: 1. Instalation problem. error in python-slugify setup command: use_2to3 - solution: update your setup tools in the terminal with the comand "setuptools==58". Then try "pip install pylot" 2. Error in import - solution: change comand to "import matplotlib.pyplot as plt"
Hi! Thanks for the amazing explanation, it has helped me alot! I am currently working on optimizing the Tesseract engine for my specific needs. However, I am having some problems with rotating documents. For some reason, removing the borders is not working. Since the document is rotated, so are the borders (so I am seeing black triangle-shaped borders). Furthermore, if the document is rotated counter-clockwise just a little bit, it will correct it by rotating the image to 90 degrees counter-clockwise, rather then to the closest 90 degree angle. Any ideas for the problems I am having?
Hi , Thank you so much for such a detailed explanation and making a series out of this , I have one question, Can you please tell me or refer a link as to how to get a threshold of image, like get the threshold of an image, so that we can use it as a reference for other images?
Hi! Interesting question. If I understand you right, that is not possible as far as I know. The threshold is a change to the image based on a certain pixle number. Are instead thinking of trying to get an ubderstanding of the average range of pixles in an image?
@@python-programming uhh yes something like that, so in here , instead of setting the threshold on an image and correcting it via trial and error, I was thinking if it is possible to get a threshold of a perfect image and apply those values to a problamatic image. Actually I was trying ur tutorial, and you have mentioned that , if we try to use dilation and erotion on a perfectly fine image, it will ruin it. and thats what was happening. So I got into thinking if there is any way to get a threshold value of an image.
your display function is not working in greyscale image bcz function need three argument "width" "height" "depth" , but grey scale give only 2 parameter .
Hi I just copied the same exact code that you have used for deskewing and also used the image that you used, but it doesn't work correctly, could you guide me through this? Thank you
@@python-programming I had imported the rotated image with borders accidentally. my bad thank you for sharing your knowledge. I am learning a ton of new things
@@python-programming i already did the object detection part. trained the license plate in yolo v4. i cropped the license plate from images and having a hard time using easy OCR to get the text from plate.
Great Tutorial. How to deskew an image when the page is rotated upside down? Or atleast how to get an angle of rotation.? If anyone can help, please suggest me some method/ approach.
Hi, what if I have a region of interest that is about 150x50 which has a single number let's say 1235 that I want to ocr, and that number takes a large portion of the roi image, like 60% of the height and 50% of the width, the image itself is a frame from a video capture so its good quality, what preprocessing do you think should be done? I am using tesseract for the ocr. Thanks!
Hello!! So when I try to convert the image and when I pass on this command inverted_image = cv2.bitwise_not(img) cv2.imwrite('PYTESSERACT/inverted.png', inverted_image) Its output is showing me "False" Please tell me how do I fix this.
Can you suggest me an algorithm or any library through which we can separate text from image which is having text in different languages. I am having a image which is having text in both German and English language. I want to separate the text for text summarization. Any help will be appreciated.
Dear Sir, I am your Subscriber I want to create a tool that finds text errors in the image. For Example: if I forgot to write CONTACT US, BUY NOW, CONTACT NUMBER, SPELLING MISTAKE, etc... in my social media post. that the tool finds error and suggests what are missing or what is incorrect in social media post. 🙏 Please guide me and suggest what course I need to buy or what I need to learn to create this tool Thank you!
Hello sir I am working on a project where I need user to upload a pdf if it has only handwritten text in the images of pdf and not the computer typed text. Is there any python library which can help me in this?
I tried the code for rotation and deskewing but it doesn't change anything. I used raspberry pi 4 to try it. Is it possible that it cannot perform in raspberry pi? Please reply..
How to extract different kind of text such as hand written, tabular, free text from different scanned docs and pdf's and images using ML OCR and its pre-processing techniques ?
Thanks a lot !! That's exactly the kind of material I was looking for. I have a question about deskewing though. Although it straightens the document well, there are cases where it completely flips it 90 degrees (the original skew was quite small actually), so I had to set a limit of 35/-35 in the angle to ignore what's outside the range. However, what bothers me more is that the OCR results get worse after applying the deskew. I mean, the results before are quite good, but if I apply it, it fails to detect many words that I can detect without applying it and even detects another language not existing in the document (I used 2 languages because in some documents, they both appear). Again, these two issues don't happen when I don't deskew
the reason this problem is happening is that the rotation function does the same things we already did such as turning the pic to gray, dialation etc.. so if u do it again the quality is going to change not in your favor this time which will make rotating the pic impossible. so you simply need to start by rotating the pic THEN move on to the next steps.
I am learning tons of stuff from this OCR series! It has helped me massively in developing my own project! But the display (im_path) function you are using to print every image is never working for me; I keep getting the same error ---> "ValueError: not enough values to unpack (expected 3, got 2)". Can you please help me with this?
Not sure if you have solved this or not, but this is how I got around that issue. Please comment if there is a better way. When converted to grayscale you lose the depth dimension. I put an if statement in the function to specify the number of dimensions to be expected. I hope this helps # 3 dimensions for RGB, 2 dimensions for gray scale def display(im_path,dimensions):
if dimensions == 3: dpi = mpl.rcParams['figure.dpi'] im_data = plt.imread(im_path)
I get the following error, can anyone suggest a solution ? : error: OpenCV(4.5.4) :-1: error: (-5:Bad argument) in function 'dilate' > Overload resolution failed: > - src is not a numpy array, neither a scalar > - Expected Ptr for argument 'src'
I actually tried to play around on my own before watcNice tutorialng tNice tutorials and finally knowing what many of the buttons I randomly clicked on an is
bro you're literally the goat. Three years after you've uploaded this and your work is saving my ass today
Doing all the steps finally got me to 98% accuracy. Thanks so much!
Awesome! No problem!
How did u calculate accurency ?
What a legend only one ad in the beginning . Your so damn underrated
i can't believe i found this amazing channel !!! I've been working on an OCR mobile app to extract fields from scanned invoices and these videos are exactly what I m looking for million thanks man !!!
Awesome! Glad you are finding them useful! I have 10 more videos planned for this series. I am getting over a cold and have not been able to post for a while.
@@python-programming i hope you get well soon and i m looking forward to these videos
same!
did you finish your work ?
@@cuneytsn yes I did
Hey thank you so much! The video is about an hour long, so I’m really happy that your voice is so pleasant and happy to listen to! This video helped me a lot on my project.
This is awesome ! Really helpful for my dissertation research about OCR in the accountability field. Many thanks from Paris !
So happy to hear that! No problem!
why are we working
on jupyter all of a sudden?
Hi!, First thank for the tutorial. In my case I had a problem while correcting the rotated image with the function. In the link it gives you a really cool solution, if anyone had the problem just comment the line of the angle and put this lines instead and it will work perfectly.
middleContour = contours[len(contours) // 2]
angle = cv2.minAreaRect(middleContour)[-1]
As I said it comes in the link given but this is in the case you're in a rush.
Thanks for the channel and the videos for real. I would have liked to have teachers like you while I was studying!!!!
Thanks for your input. I tried every option but it'll always get -90º to -30º (aprox) rotated. Cannot find where the problem is. I'm trying with a picture of my own, like the ones I will process.
Inverting took me from garbage to great recognition. Thanks!
Awesome! Glad these are useful and working. I was not sure if I explained it well enough.
Amazing, I am going to recommend to my colleagues. Great work.
I appreciate your step-by-step explanations
Thank you so much. I just upgraded from Making Waves, so the concepts are familiar, but tNice tutorials is a whole new world! Look forward to
Thank you, I've been looking for a long time
Hey, any idea why I got "ValueError: not enough values to unpack (expected 3, got 2)" at 15:43. I'm using Python3.8.2 and open-cv 4.5.1.
Also, please check patron messages.
Thanks!
Good question. I don't think I explained this in the video. The problem is likely from the display function with the height, width, (sometimes depth). Make sure that im_data.shape[:2] is in your display function. I updated this for GitHub so this error wouldn't pop up, but I don't think I mentioned it in the video. Here is the corrected display function:
def display(im_path):
dpi = 80
im_data = plt.imread(im_path)
height, width = im_data.shape[:2]
# What size does the figure need to be in inches to fit the image?
figsize = width / float(dpi), height / float(dpi)
# Create a figure of the right size with one axes that takes up the full figure
fig = plt.figure(figsize=figsize)
ax = fig.add_axes([0, 0, 1, 1])
# Hide spines, ticks, etc.
ax.axis('off')
# Display the image.
ax.imshow(im_data, cmap='gray')
plt.show()
@@python-programming Thank you for your response, nonetheless, I already found and fix it from SO. The point was that I didn't get the idea.
Here is my current thought about it, the reason behind it is the code trying to unpack more values from an object than those that actually exist. So either we have to remove some requests or return the 'requested' value (before actually request it) to the program and then request the results.
I know that this is a bit more detailed and out of the topic to appropriately fit on your video comment section but, a clarified answer would be greatly appreciated.
Learn without gaps is better in the long run, don't you agree?
Precisely the problem! It was a good catch and I'm glad this comment is here. No worries about it being out of topic. I think it is very much on topic.
First I'd like to thank you for the tutorial. I have a question. In the 28th min you are talking about pros and cons of noise removal. And you said that for this particular image you wouldn't use it for stated reasons. So what if you have a thousand images you want to process with maximum rate of success. How would you then implement noise removal to those images that actually benefit from it and skip it for those that don't and would in case of using it result in worse performance?
Thanks for the comment! I'm glad you liked the video! There are a few solutions here, perhaps a small image classifier to detect those pages that have a lot of noise and flag them for manual adjustments. It likely wouldn't take many examples to train a binary model to do this. Another approach could be with Open-CV but it may take longer for some data to get that up and running effectively. It really comes down to the images you are using, though.
Men you are an amazing teacher! I love the way you explain things! thank you BTW!
Thank you! This will help me save my work :>
You're welcome!
found actually helpful for people started from scratch
Great thanks from Uganda the pearl of Africa
from numpy import ones, uint8
kernel = ones((1, 1), uint8)
is a lot faster than importing the entire numpy module
Great and helpful comment!
Great content and clear explanation
Thanks!
Thankyou so much for this Video . This is an Great Video.
Thanks! No problem! Happy I could help you.
Plzz upload more videos on this
Thank you man for sharing this stuff
I get this error when trying to get the gray version of the image at 18:12
Cell In[4], line 4, in display(img_path)
2 dpi = 80
3 img_data = plt.imread(img_path)
----> 4 height, width, depth = img_data.shape
6 img_size = width / float(dpi), height/ float(dpi)
8 fig = plt.figure(figsize=img_size)
ValueError: not enough values to unpack (expected 3, got 2)
copy and paste the fonction call it "display2" for exemple and remove the "depth" then use the display2 when display dosen't work
good job man!
Thanks!
just amazing, thank you!
No problem!
Wow awesome video, totally subscribing 🙂, I would like a transparency example, as we have invoices scanning from thin paper with duplex pages bleeding through the image. I'm assuming the transparency will help?
Thanks! Can you DM me on Twitter with some example images?
@@python-programming hi sorry I don’t do twitter or social media. But simply put sometimes a scanner will produce an image which has some ghosting of the other side coming through
I am working through the video stack and trying to comprehend it all. Trying to develop an auto scan ocr solution of sorts. Really helpful what you and others have shared
you saved my life....thanks
yo bro, really thankya. Big respect
Amazing Video, what do I do if some parts of the image are skewed? I can't just rotate the whole image. Any solution for that please?
I'm unable to acces the notebook. Can you please share the notebook.
Great video. But I need to point out that `/` is actually a forward slash
Rescaling code is not filled in the final notebook on GitHub.
at 41:15 line 395 i get an error saying : name 'new' is not defined ( im working with pycharm)
you really helped me, thank you
Are the functions you built only suitable for this specific document? Or will they be able to handle new input documents?
(14:49) Why we use function grayscale, when we can simply use built-in function cvtColor?
fire video, thanks bro
Thank you for the very helpful tutorial. I am wondering if there is any difference between from preprocessing SCENE-TEXT dataset from OCR dataset? In my POV, BW function will not be needed in SCENE-TEXT since there is various color in an image. Thanks again.
Thanks for the video. I was having issues with the "getSkewAngle" function.
I found an easy workaround though.
I changed the last line
"return -1.0 * angle"
to just
"return angle"
Hope this helps anyone else with this problem.
For anyonne getting a error message when importing pylot. heres a few solutions:
1. Instalation problem. error in python-slugify setup command: use_2to3 - solution: update your setup tools in the terminal with the comand "setuptools==58". Then try "pip install pylot"
2. Error in import - solution: change comand to "import matplotlib.pyplot as plt"
Good video. not completely relevant for my case as i dont know what the image will look like, but still usefull!
Thanks!
which theme ur using for jupyter, please share the method so it doesnt effect intellisense as well
I'm using the standard dark theme in JupyterLab
Great videos thanks for sharing !. Would you be able to tackle the problem of removing an image watermark in scanned pdfs please?
Thank you for your valuable tutorial, but i have a question, how to save extracted text and corresponding image name in excel.
Hi! Thanks for the amazing explanation, it has helped me alot! I am currently working on optimizing the Tesseract engine for my specific needs. However, I am having some problems with rotating documents. For some reason, removing the borders is not working. Since the document is rotated, so are the borders (so I am seeing black triangle-shaped borders). Furthermore, if the document is rotated counter-clockwise just a little bit, it will correct it by rotating the image to 90 degrees counter-clockwise, rather then to the closest 90 degree angle.
Any ideas for the problems I am having?
How did you success to rotate the image ? It rotate every time the image to 90, i don't know how to fix that !
What happened to using PIL to open an image..?
Hi , Thank you so much for such a detailed explanation and making a series out of this ,
I have one question,
Can you please tell me or refer a link as to how to get a threshold of image, like get the threshold of an image, so that we can use it as a reference for other images?
Hi! Interesting question. If I understand you right, that is not possible as far as I know. The threshold is a change to the image based on a certain pixle number. Are instead thinking of trying to get an ubderstanding of the average range of pixles in an image?
@@python-programming uhh yes something like that, so in here , instead of setting the threshold on an image and correcting it via trial and error, I was thinking if it is possible to get a threshold of a perfect image and apply those values to a problamatic image. Actually I was trying ur tutorial, and you have mentioned that , if we try to use dilation and erotion on a perfectly fine image, it will ruin it. and thats what was happening. So I got into thinking if there is any way to get a threshold value of an image.
your display function is not working in greyscale image bcz function need three argument "width" "height" "depth" , but grey scale give only 2 parameter .
Can i use it for handwritten text recognition? Please?
HTR is a different problem. Much more custom solutions are needed. Transkribus or OCR4All (open source) are both good options to consider.
@@python-programming Thanks
can you plz share display method which you found in stack overflow
Thank you for this awesome tutorial! 1 questions though. Can we just manually crop the image instead of removing the borders?
Could you please make a video on “Hand written digit recognition using neural network” in python
Did you make a video for rescaling? :)
I do not think I did. I will try and do that.
Thank you
Sir, Is there any way to separate handwritten text and printed text in documents?
Hi
I just copied the same exact code that you have used for deskewing and also used the image that you used, but it doesn't work correctly, could you guide me through this?
Thank you
Whats the error?
@@python-programming
I had imported the rotated image with borders accidentally.
my bad
thank you for sharing your knowledge. I am learning a ton of new things
No worries at all! Glad you figured it out and I am glad you are getting a lot from this channel!
Please make the video on how to detect the table and how to Calculate the accuracy of the image
That sounds like fun! I will do that.
HOW TO RETRAIN OCR? I WANT TO DETECT LIVE LICENCE PLATE NUMBER
That would be object detection first then OCR
@@python-programming i already did the object detection part. trained the license plate in yolo v4. i cropped the license plate from images and having a hard time using easy OCR to get the text from plate.
@@modeltrainer1246 excellent. Okay mind dming me on Twitter with some sample images?
Hi bro ,Have you got to know ? how can i retrain my model to implement ocr object detection was done
Great Tutorial. How to deskew an image when the page is rotated upside down? Or atleast how to get an angle of rotation.?
If anyone can help, please suggest me some method/ approach.
Hi, what if I have a region of interest that is about 150x50 which has a single number let's say 1235 that I want to ocr, and that number takes a large portion of the roi image, like 60% of the height and 50% of the width, the image itself is a frame from a video capture so its good quality, what preprocessing do you think should be done? I am using tesseract for the ocr. Thanks!
Hey Bro, for the Rescaling part and the Alpha channel/transparency part, do you have a source or a github link for the codes
wait we dont need to invert image on tesseract 4.0?
Hello!!
So when I try to convert the image and when I pass on this command
inverted_image = cv2.bitwise_not(img)
cv2.imwrite('PYTESSERACT/inverted.png', inverted_image)
Its output is showing me "False"
Please tell me how do I fix this.
Can you suggest me an algorithm or any library through which we can separate text from image which is having text in different languages. I am having a image which is having text in both German and English language. I want to separate the text for text summarization. Any help will be appreciated.
OpenCV. I have 5 videos coming out on how to do this statting next week. You will want to use bounding boxes.
Lot of modules r here u can use Fitz,pypdf2 , pdfplumber complot ,pytesseratte
Dear Sir, I am your Subscriber
I want to create a tool that finds text errors in the image.
For Example:
if I forgot to write CONTACT US, BUY NOW, CONTACT NUMBER, SPELLING MISTAKE, etc... in my social media post.
that the tool finds error and suggests what are missing or what is incorrect in social media post.
🙏 Please guide me and suggest what course I need to buy or what I need to learn to create this tool
Thank you!
Thank you very much, Sir. it helped me a a lot in my OCR project
I am so happy to hear that!
Which IDE you have used in vedio
Jupyter notebook
Could you please tell me where do you write this code , I mean is it in python or IDLE?
For this I used Jupyter Lab
Hello sir I am working on a project where I need user to upload a pdf if it has only handwritten text in the images of pdf and not the computer typed text. Is there any python library which can help me in this?
Have you found that library?
@Krishna-r6q8c nope
@@hemantchauhan6437 😓😓
Awesome!
is it possible to use it for handwrittting?
I tried the code for rotation and deskewing but it doesn't change anything. I used raspberry pi 4 to try it. Is it possible that it cannot perform in raspberry pi? Please reply..
what is kernel in the deskewing function ?
How to extract different kind of text such as hand written, tabular, free text from different scanned docs and pdf's and images using ML OCR and its pre-processing techniques ?
Hi Sir could you do a session on Houghline transformation
Thats a great idea!
Thanks a lot !! That's exactly the kind of material I was looking for. I have a question about deskewing though. Although it straightens the document well, there are cases where it completely flips it 90 degrees (the original skew was quite small actually), so I had to set a limit of 35/-35 in the angle to ignore what's outside the range. However, what bothers me more is that the OCR results get worse after applying the deskew. I mean, the results before are quite good, but if I apply it, it fails to detect many words that I can detect without applying it and even detects another language not existing in the document (I used 2 languages because in some documents, they both appear). Again, these two issues don't happen when I don't deskew
Thanks for the commen! Glad you liked the video. That is odd indeed! I am not sure why that would be the case
the reason this problem is happening is that the rotation function does the same things we already did such as turning the pic to gray, dialation etc.. so if u do it again the quality is going to change not in your favor this time which will make rotating the pic impossible.
so you simply need to start by rotating the pic THEN move on to the next steps.
bro did you forget to fill the rescaling the img in Github? Anyway Thankyou
I am learning tons of stuff from this OCR series! It has helped me massively in developing my own project! But the display (im_path) function you are using to print every image is never working for me; I keep getting the same error ---> "ValueError: not enough values to unpack (expected 3, got 2)". Can you please help me with this?
Not sure if you have solved this or not, but this is how I got around that issue. Please comment if there is a better way. When converted to grayscale you lose the depth dimension. I put an if statement in the function to specify the number of dimensions to be expected. I hope this helps
# 3 dimensions for RGB, 2 dimensions for gray scale
def display(im_path,dimensions):
if dimensions == 3:
dpi = mpl.rcParams['figure.dpi']
im_data = plt.imread(im_path)
elif dimensions == 2:
dpi = mpl.rcParams['figure.dpi']
im_data = plt.imread(im_path)
Wierd - i agree with you - but if the shape is only 2 dimensional for grayscale that the error didn't come up in the video.
Hello, can you help me please?
how to detect inverted text or letters in an image? and after rotate the image the normal state?, thanks
Will it work with scanned pdf?
display('photos/gray.jpg')
ValueError Traceback (most recent call last)
Cell In[83], line 1
----> 1 display1('photos/gray.jpg')
Cell In[65], line 4, in display1(im_path)
2 dpi = 80
3 im_data = plt.imread(im_path)
----> 4 height, width, depth = im_data.shape
6 figsize = width / float(dpi), height / float(dpi)
8 fig = plt.figure(figsize=figsize)
ValueError: not enough values to unpack (expected 3, got 2)
Wow good
Please please make the video on how to detect the table in image ?
Amazing video.
I wanna skew code plz....................
not wNice tutorialle quarantine but how r u doing is that hard ?
What name application editor ? tq...
Jupyter notebook
The only tNice tutorialng I learnt myself in soft soft is pressing tab in the keyboard to bring up the channel rack
I get the following error, can anyone suggest a solution ? :
error: OpenCV(4.5.4) :-1: error: (-5:Bad argument) in function 'dilate'
> Overload resolution failed:
> - src is not a numpy array, neither a scalar
> - Expected Ptr for argument 'src'
Border removal does not work with white borders. Anyone has any idea why?
how can i detect check box yes and no answer ?
not able to access the notebook!
rescaling is not added
i need ocr detection of kannada language...;how can i co that?
which IDE is used in this
No alignment?
Ok nice
misconceptions that the comnt is supposed to soft like I am in love with Nice tutorialm or sotNice tutorialng.
Jupyter lab is saying “No module named matplotlib”
Not Working for Windows...I am stuffed up with this...!
need to have pdf scanned into text
Good idea for a video!
I actually tried to play around on my own before watcNice tutorialng tNice tutorials and finally knowing what many of the buttons I randomly clicked on an is