@richardbloemenkamp8532
Thanks for showing how to use all three methods. For the comparison part I think you could go a lot more in depth on the results. For most applications the results seem largely insufficient to me, but for some applications it is already fine.
@travezripley
I love that you had an “Chain of Strength” image!!!! Straight Edge Hardcore Lives! Youth Crew!
@tusharniras
Hey Rob, thank you for the Video! this helped me a lot.!!! @to my Indian Developers, I have tried these libraries for Indian languages. And `pytesseract` seems to be a winner fro reading Marathi and Hindi language.
@rushdamansuri8545
Thank you so much, your code removed my days of frustation.
@cyberhard
Great video! Clear and concise. You've earned my subscription.
@lphilippeabadieo298
Hi there! I wanted to thank you for the incredible video on text detection in images using `pytesseract`, `easyocr`, and `keras_ocr`. It was exactly what I needed to resolve all my doubts about which tool to use in my projects. Your clear explanation and comparative analysis helped me understand the advantages and disadvantages of each, allowing me to make an informed decision. Thanks again for sharing your knowledge and for the quality of your content. I would love to see more videos like this, where you explain and compare different tools and technologies. Keep up the excellent work! Best regards and well done! Philippe
@vesper8
Great video but man I would have loved to see another half hour where you compare the results to the original annotations, give a score to each technique, and then try to make improvements to get the score to increase
@tanvirhossain18
Thanks a lot, Rob. This is a great Tutorial. Hats off!
@IntenseRouge
Your video is really great, thank you Rob!
@MM-un7wg
Great job as always mate!
@wingops150
I lost track of what happens at the 5:04 mark. Some text moves around, and other text all of a sudden appears, and I can't follow what exactly is happening there. Can you explain?
@ShubhamNarkhede1920
i do have human filled forms and I want to extract data from it , like it might have check marks , dot ... filled but he patient , will this work for that?
@xoblm4938
Hi Medallion, do you know how to improve the accuracy of the easyocr ? I have a image , like a dataframe image, it can only read 95% of the data in the image. Thanks in advance
@zaheerbeg4810
Highly appreciated
@tigranmkrtchyan7346
Hey Rob, thanks a ton for the awesome job you do, I have learnt a lot of new cool stuff (I was only aware of pytessaract, thought it is the best one and tried it on pictures), now I will definitely give a try to the other libraries as well. As I already mentioned, overall you are doing an extremely great job, I just have 1 idea and 1 suggestion : ) 1) idea: as you mentioned in the video, we have the annotations (like the ground truth) already provided in the dataset, right? Wouldn't it be a good idea to check the results vs the ground truth? I.e. smth like lib2 has 3 out of 10 annotations correctly ( recall 0,3) out of 6 predicted texts (0,5 precision) smth like accuracy etc. I understand, this is not perfect as it could only partially extract the text (like miss 1-2 letters) or recognize letter 'G' instead of 'C'. I mean the question is: what's a fair way to have some numerical result based on the dataset? Say library 1 has accuracy X precision Y and recall Z and based on this values and the confusion matrix to be able to make a selection of a library given a particular dataset? 2) Suggestion: I am mentioning this 3rd time already, but your videos are just marvellous, I mean extremely informative, to the point, no second wasted at all. Just perfect. So, what I would really love to see is (as you asked about suggestion for some next video) is almost the same kind of video for some audio task. There is this new BLOOM model out today, I haven't checked it yet, but maybe you could pick some models (like based on wav2vec2) that recognize voice (asr) and compare them using transformers and huggingface for example? Would really be nice to see some comparison of different models in some audio related task, where the whole pipeline (like loading audio, extracting the numerical features, feeding to some pretrained model and finally prediction) would be implemented and validated based on say word error rate. Thanks in advance ; )
@muhammadsyaukitarmizi9184
I have a problem, the problem is DataFrame.___init___() got an unexpected keyword argument 'coloumn'. How should i do ?
@nalinbranden
Hey Rob, Amazing content, thanks for making this. Can you suggest the best method to detect words from a printed text? also like to isolate a single word out of a paragraph. Keep up the good work!
@notmyname6452
hi, i'm trying to find a way to process bulk ai generated art, and flag any images that contain even the tiniest watermark or text. I fumbled around with some OCR previously in python (don't remember what i used) but it wasn't very close to what i needed it to do considering the text is often just random scribbles or gibberish. any chance you could point me in the right direction to a possible solution? thanks.
@KuldipSolanki-o5b
ditect place and shape and size of upload second image in main image and after ditectin all thing second image upload in main image acording to ditection and save image i dont get solution please help me sir give me solution :face-red-droopy-eyes:
@pcargolo1