Answers.Body: <p>I think currently you are using CPU for detection and Recognition try installing the cuda to use GPU</p>
  <pre><code>pip install torch==1.13.1+cu117 torchvision==0.14.1+cu117 torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cu117
  </code></pre>
  <p>This will improve speed by around <strong>10X</strong>.</p>
  <p>If you further want to increase the speed of the detection and recognition then:</p>
  <p>Try using <a href="https://github.com/NVIDIA-AI-IOT/scene-text-recognition" rel="nofollow noreferrer">https://github.com/NVIDIA-AI-IOT/scene-text-recognition</a></p>
  <p>It will further increase the speed of detection by <strong>2X</strong> and for recognition by <strong>5X</strong>.</p>
  
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Answers.Text: Great! I voted for you
Answers.UserDisplayName: Zollikofen4
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Answers.UserDisplayName: Hiren Namera
Answers.Body: <p>EasyOCR should not be that slow using a GPU, have you installed the CPU version of PyTorch?</p>
  <p>If you have a CPU version of PyTorch in the local cache you will need to do the following</p>
  <h1>uninstall the CPU version of pytorch<br></h1>
  <pre><code>pip uninstall torch&lt;br&gt;
  </code></pre>
  <h1>install the GPU version, don't use the local cache<br></h1>
  <pre><code>pip install torch --extra-index-url https://download.pytorch.org/whl/cu116 --no-cache-dir&lt;br&gt;
  </code></pre>
  <p>If you do a &quot;pip list&quot;, you should see, which are the GPU versions<br></p>
  <pre><code>torch                          1.13.1+cu116&lt;br&gt;
  torchaudio                     0.13.1+cu116&lt;br&gt;
  torchvision                    0.14.1+cu116&lt;br&gt;
  </code></pre>
  <p>I hope this helps.</p>
  
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Answers.UserDisplayName: Scott Auchmoody
Body: <p>I am working on a project that requires me to identify a product on a grocery shelf. For that, I am trying to use test recognition and localization to spot a product.</p>
  <p>I tried Easy OCR and tesseract OCR because they are giving me accurate results, but it takes a lot of time to process the image</p>
  <ol>
  <li>Easy OCR takes about 7 seconds to process one image.</li>
  <li>Keras OCR takes about 42 seconds.</li>
  </ol>
  <p>I followed this post to implement the code: <a href="https://www.kaggle.com/code/odins0n/keras-ocr-vs-easyocr-vs-pytesseract" rel="nofollow noreferrer">https://www.kaggle.com/code/odins0n/keras-ocr-vs-easyocr-vs-pytesseract</a></p>
  <p>I am running this on my laptop with NVIDIA GeForce RTX 3050 GPU.
  Is this expected behavior? Is there any way to improve the speed?</p>
  
Tags: <deep-learning><optical-character-recognition><text-detection>
Title: How to improve the performance of Easy OCR
UserDisplayName: Suresh Nayak
ThreadText: # How to improve the performance of Easy OCR
  
  (Asked by: username_0 on 2022-07-29)
  
  I am working on a project that requires me to identify a product on a grocery shelf. For that, I am trying to use test recognition and localization to spot a product.
  
  I tried Easy OCR and tesseract OCR because they are giving me accurate results, but it takes a lot of time to process the image
  
  1. Easy OCR takes about 7 seconds to process one image.
  2. Keras OCR takes about 42 seconds.
  
  I followed this post to implement the code: <https://www.kaggle.com/code/odins0n/keras-ocr-vs-easyocr-vs-pytesseract>
  
  I am running this on my laptop with NVIDIA GeForce RTX 3050 GPU.
  Is this expected behavior? Is there any way to improve the speed?
  
  **Tags:** deep-learning, optical-character-recognition, text-detection
  
  
  ---
  
  ## 2 answers
  
  ### Answer by username_1 on 2023-12-05. Score: 1
  
  I think currently you are using CPU for detection and Recognition try installing the cuda to use GPU
  
  ```
  pip install torch==1.13.1+cu117 torchvision==0.14.1+cu117 torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cu117
  
  ```
  
  This will improve speed by around **10X**.
  
  If you further want to increase the speed of the detection and recognition then:
  
  Try using <https://github.com/NVIDIA-AI-IOT/scene-text-recognition>
  
  It will further increase the speed of detection by **2X** and for recognition by **5X**.
  
  > **Comments:**
  > **username_2**: Great! I voted for you  
  
  ---
  
  ### Answer by username_3 on 2023-03-09. Score: 0
  
  EasyOCR should not be that slow using a GPU, have you installed the CPU version of PyTorch?
  
  If you have a CPU version of PyTorch in the local cache you will need to do the following
  
  # uninstall the CPU version of pytorch
  
  ```
  pip uninstall torch<br>
  
  ```
  
  # install the GPU version, don't use the local cache
  
  ```
  pip install torch --extra-index-url https://download.pytorch.org/whl/cu116 --no-cache-dir<br>
  
  ```
  
  If you do a "pip list", you should see, which are the GPU versions
  
  ```
  torch                          1.13.1+cu116<br>
  torchaudio                     0.13.1+cu116<br>
  torchvision                    0.14.1+cu116<br>
  
  ```
  
  I hope this helps.
  
  
  ---
  
  