SILICON VISION
SILICON VISION
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Відео

OCR Model Comparison | Tesseract OCR, EasyOCR, Keras-OCR, Paddle OCR, MMOCR, OCR-SAM
Переглядів 6 тис.11 місяців тому
OCR Model Comparison: Tesseract OCR, EasyOCR, Keras-OCR, Paddle OCR, MMOCR, OCR-SAM Purpose of OCR Model: Text extraction Document digitization Data entry automation Searchability Accessibility Translation services Text analysis Forms processing Practical use case of OCR: Car Number Plate Recognition (ANPR) Receipt and Invoice Processing Document Scanning and Archiving Passport and ID Card Scan...
Opencv Autocomplete not Working on Pycharm | PyCharm cannot find cv2 references |
Переглядів 439Рік тому
#opencv #computervision #artificialintelligence #deeplearning #pycharm Solution of the error: opencv autocomplete not working on pycharm Autocomplete for OpenCV-Python in Windows not working cv2 no suggestions PyCharm cannot find cv2 references
Segment Anything Model (SAM) with Grounding DINO to detect and extract object from the image
Переглядів 2,8 тис.Рік тому
#computervision #opencv #artificialintelligence #deeplearning #machinelearning Segment Anything Model (SAM) with Grounding DINO to detect and extract object from the image according to text prompt or classes of object. Colab Notebook Link: colab.research.google.com/drive/14OD5NbTd3470WdkF_075pI4titJNab7X?usp=sharing
Image Inpainting with Segment Anything Model (SAM) and Stable Diffusion
Переглядів 2 тис.Рік тому
#computervision #opencv #artificialintelligence #deeplearning #machinelearning Image Impainting using Segment anything model and Stable Diffusion explanation with example. Here you will get details code and implementation details in Google Colab Notebook SAM Github link for instalation: !pip install 'git github.com/facebookresearch/segment-anything.git' SAM weights download link: !wget -q dl.fb...
Segment Anything Model in Python| SAM | A to Z | Segment Anything Model (SAM)
Переглядів 2,9 тис.Рік тому
#computervision #opencv #artificialintelligence #deeplearning #machinelearning Segment anything model explanation with example. Here you will get details code for extract any segmented part of image using SAM model. Image Segmentation, Image masking, Object Detection. SAM Github link for instalation: !pip install 'git github.com/facebookresearch/segment-anything.git' SAM weights download link: ...
MMOCR-Optical Character Recognition | Modular Architecture of MMOCR
Переглядів 2,3 тис.Рік тому
#computervision #deeplearning #artificialintelligence #opencv #machinelearning MMOCR is an open-source toolbox based on PyTorch and mmdetection for…… Text detection Text recognition Key information extraction It is popular for scene or curve text detection & recognition. STEPS & LINK: step 1. Clone MMOCR git clone github.com/open-mmlab/mmocr.git cd mmocr mim install -e . step 2. Then MMOCR dire...
OCR-SAM | Optical Character Recognition (OCR) with Segment Anything Model (SAM)
Переглядів 1,4 тис.Рік тому
#artificialintelligence #computervision #deeplearning #opencv #machinelearning Basically, SAM can be applied on OCR model. OCR-SAM is the combination of off-the-self OCR Model MMOCR and SAM which can put mask on detected text and several application can develop using OCR-SAM like….. Segment text from image Text removal from image and Text inpainting Step 1: git clone github.com/yeungchenwa/OCR-...
Grounding DINO | Detect Anything | No Training | Zero Shot Object Detection
Переглядів 3,1 тис.Рік тому
#computervision #artificialintelligence #deeplearning #opencv #machinelearning Grounding DINO is a self supervised zero shot object detection algorithm which can detect object from an image based on the text prompt. I have implemented it on PyCharm. Necessary command need to execute in PyCharm terminal: Clone the GroundingDINO repository from GitHub. git clone github.com/IDEA-Research/Grounding...
Grounding DINO | AssertionError: Torch not compiled with CUDA enabled | Solve Easily
Переглядів 6 тис.Рік тому
#computervision #artificialintelligence #deeplearning #opencv #machinelearning Grounding DINO: AssertionError: Torch not compiled with CUDA enabled This video will solve the AssertionError: "Torch not compiled with CUDA enabled" when you run Grounding DINO algorithm for object detection.

КОМЕНТАРІ

  • @zishaansayyed2092
    @zishaansayyed2092 10 днів тому

    i want to train model on custom data how can i do that ?

  • @jaiswalrohan
    @jaiswalrohan 2 місяці тому

    4:13 media offline

  • @karthikbalu5824
    @karthikbalu5824 3 місяці тому

    paddler or mmocr which is most accurate?

  • @tasnimjahan-qv7hy
    @tasnimjahan-qv7hy 3 місяці тому

    Could you provide the code? The GitHub link is not working.

  • @shivampadmani
    @shivampadmani 4 місяці тому

    This solution is same as commenting the whole code to avoid error instead of finding the bug.

  • @shivampadmani
    @shivampadmani 4 місяці тому

    This solution is same as commenting the whole code to avoid errors instead of finding a bug.

  • @AhmedOmayar
    @AhmedOmayar 5 місяців тому

    Sir, Would you mind giiving me this solution of this porblem . when I want to run your code in terms of solar panel image then it is creating this problem like "SupervisionWarnings: green is deprecated: `Color.green()` is deprecated and will be removed in `supervision-0.22.0`. Use `Color.GREEN` instead. SupervisionWarnings: annotate is deprecated: `BoxAnnotator` is deprecated and will be removed in `supervision-0.22.0`. Use `BoundingBoxAnnotator` and `LabelAnnotator` instead" . Original code of your is "import supervision as sv import numpy as np mask_annotator = sv.MaskAnnotator() box_annotator = sv.BoxAnnotator(color=sv.Color.green()) detections=sv.Detections.from_sam(result) annotated_image = box_annotator.annotate(scene=image_bgr.copy(),detections=detections,skip_label=True) annotated_image = mask_annotator.annotate(scene=annotated_image.copy(),detections=detections) sv.plot_images_grid( images=[image_bgr,annotaed_image], grid_size=(1,2), titles=['Original_image','Annotated_image'], )"

  • @muhammadhuzaifa-11
    @muhammadhuzaifa-11 5 місяців тому

    @siliconvision does the notebook still work?

  • @chingkhei_thoudam
    @chingkhei_thoudam 5 місяців тому

    How to run with gpu instead of cpu?

  • @moizmansoor9830
    @moizmansoor9830 6 місяців тому

    How can we perform it on whole dataset with multi class classification? Do you have any notebook for it?

  • @jonyifamily7311
    @jonyifamily7311 6 місяців тому

    I can't find the same path 😢

  • @stern7658
    @stern7658 7 місяців тому

    doesthis work for text too as in copy original signature to paste in a document?

  • @elvenkim
    @elvenkim 7 місяців тому

    Hi, I tried to implement on Raspberry Pi but has the "too many value to unpack" error. Any advice? I have trimmed from 5 parameters to 4, and change the first param to "boxes.

  • @ElfTRAVELTOUR
    @ElfTRAVELTOUR 7 місяців тому

    Can share the python codes?

  • @dhrubajyotipaul8204
    @dhrubajyotipaul8204 7 місяців тому

    I have been looking for something this. Excellent quality. Loved that you also talked about multi-lingual support! Thank you! 🙂

  • @MostafaHamdy-gp8zi
    @MostafaHamdy-gp8zi 8 місяців тому

    Hi, I tryed to do the same method but I get a very incorrectly colored generated images, then i tryed SDXL instead of SD v2 and now I get black generated images, i would appreciate if you know how to solve this.

  • @yosmy5431
    @yosmy5431 8 місяців тому

    do we need to set the cuda_home first?

  • @EduCreatives
    @EduCreatives 8 місяців тому

    Its great! I am recently working on character, face, object recognition. Suggest the best libraries for: 1. Face (I use Opencv LBPH..) 2. Image to text? 3. Table Image to csv 4. Objects recognition? You should make more similar videos, soon you will be monetized.

  • @sardaromar
    @sardaromar 8 місяців тому

    Could you please provide source code

  • @nihar865
    @nihar865 8 місяців тому

    could you please provide this colab notebook

  • @kanall103
    @kanall103 9 місяців тому

    colab is = a stable diffision????? I didn know that

  • @techtb2923
    @techtb2923 9 місяців тому

    Thanks i really wanted this 😊

  • @badrisushruth6048
    @badrisushruth6048 9 місяців тому

    👏👏👏

  • @nicklesseos
    @nicklesseos 10 місяців тому

    Wow nice video!

  • @EachDayForever
    @EachDayForever 10 місяців тому

    Incredibly high-quality overview! Thank you!

  • @elvenkim
    @elvenkim 10 місяців тому

    Nice and easy way of programming. Thanks for showing all the steps!

  • @shamukshi
    @shamukshi 11 місяців тому

    do you freelance ? i need to segment solar panels from UAV images. If yes, can you share your email id ?

    • @siliconvision
      @siliconvision 10 місяців тому

      Sorry for late response. Yes, akazad.engr@gmail.com

  • @Muhaiminul_coding_club
    @Muhaiminul_coding_club 11 місяців тому

    thank you

  • @Muhaiminul_coding_club
    @Muhaiminul_coding_club 11 місяців тому

    thank you

  • @Muhaiminul_coding_club
    @Muhaiminul_coding_club 11 місяців тому

    excellent 🙂🙂

  • @rheyasharma2548
    @rheyasharma2548 11 місяців тому

    did not solve the problem.

  • @finnsteur5639
    @finnsteur5639 11 місяців тому

    Hi could you please help us with our project? We want to detect all text on screenshot of software. This is a more complex task than we tough, Tesseract and EasyOCR doesn't work. We did a lot of preprocessing (binarization, denoise, scale*3, grayscale...) and managed to go up to 90% detection on tesseract on most software. Our software is an AI that answer question based on what it saw on the screen ( It is called onistep ). This is a desktop app. This will be used by all our client on their end so we cannot use the GPU and the answer must take 5 second maximum. We think that solution like MMocr, keras OCR or paddle OCR could work but we never worked with machine learning based OCR. Do you think you can work with us on this? Do you think it is doable? Of course it would be paid work. I also sent you an email with some image preprocessed if you wanna test our image.

  • @muharremsahin9281
    @muharremsahin9281 Рік тому

    Nice video brom, it helped me a lot.

  • @timtensor6994
    @timtensor6994 Рік тому

    I think your notebook is a bit outdated because groundino module is not working. missing some installation

  • @Shajirr_
    @Shajirr_ Рік тому

    this doesn't solve the problem at all...... this switches Torch to run on your CPU instead of GPU, so it will be slow as hell

  • @gosingabke.cdsongtutegnh
    @gosingabke.cdsongtutegnh Рік тому

    Can you do about face detection and face regconition?

    • @siliconvision
      @siliconvision Рік тому

      Yes. You can write here what you need. or You can email me: akazad.engr@gmail.com

  • @sangampaudel9616
    @sangampaudel9616 Рік тому

    Great tutorial sir but while solving I get "size mismatch for wrapped_model.backbone.layer1.0.downsample.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([256, 64, 1, 1])." this error. how can I solve it ?

  • @priyakushwaha7008
    @priyakushwaha7008 Рік тому

    could you share google colab link for your notebook?

    • @Varunk47
      @Varunk47 Рік тому

      Hey, even I'm looking for a project that's similar to this. Can you please send me some sources or colab links

    • @siliconvision
      @siliconvision Рік тому

      most of the information are in the video description box..

    • @stevenvafadar9318
      @stevenvafadar9318 9 місяців тому

      @@siliconvision you supplied the weights not the colab file. easier to follow the video if you supply the colab notebook :)

    • @siliconvision
      @siliconvision 9 місяців тому

      Thanks for your suggestion.@@stevenvafadar9318

  • @eyad_aiman
    @eyad_aiman Рік тому

    that is not solving anything what about pepole who actually want to use cuda??

    • @yosmy5431
      @yosmy5431 8 місяців тому

      has you managed to solve ? i have _C error even using pytorch with cuda

  • @user-hj2ed5pe6j
    @user-hj2ed5pe6j Рік тому

    Solve? or Avoid the problem.

  • @guthriethornley8245
    @guthriethornley8245 Рік тому

    "promo sm" 😱

  • @floppy4990
    @floppy4990 Рік тому

    If I only want to extract 1 object from an image, it doesn't work. For example if I want to detect a bear, i have to set the classes = ['bear', 'bear'] and get 2 extractions of the same bear. Also, when I print detection class_ids, it says None, None instead of 0,1. I have to manually set class_id = [1, 0]. Also, how can I download the final extracted objects instead of just plotting them?

    • @siliconvision
      @siliconvision Рік тому

      colab.research.google.com/drive/14OD5NbTd3470WdkF_075pI4titJNab7X?usp=sharing#scrollTo=PHUNi2wX2odl

    • @siliconvision
      @siliconvision Рік тому

      plz check details here. After plotting in colab , you can save it in your local pc.

  • @zanishbilal355
    @zanishbilal355 Рік тому

    Brother ho can i contact you

  • @zanishbilal355
    @zanishbilal355 Рік тому

    Brother how i can i contact you

    • @siliconvision
      @siliconvision Рік тому

      Sure.. Plz email me: akazad.engr@gmail.com