<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>

CC BY-SA 4.0
2023-12-05T04:53:20.357Z
Great! I voted for you
Zollikofen4
CC BY-SA 4.0
2023-12-05T03:54:07.673Z
2023-12-05T03:54:07.673Z
Hiren Namera
<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>

CC BY-SA 4.0
2023-03-09T18:09:24.563Z
2023-12-14T11:31:30.620Z
2023-12-14T11:31:30.620Z
Scott Auchmoody
<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>

<deep-learning><optical-character-recognition><text-detection>
How to improve the performance of Easy OCR
Suresh Nayak
# 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


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## 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  

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### 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

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

If you do a "pip list", you should see, which are the GPU versions
torch                          1.13.1+cu116
torchaudio                     0.13.1+cu116
torchvision                    0.14.1+cu116

I hope this helps.


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