README.md

---
library_name: pytorch
license: other
tags:
- android
pipeline_tag: image-to-text

---

![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/easyocr/web-assets/model_demo.png)

# EasyOCR: Optimized for Mobile Deployment
## Ready-to-use OCR with 80+ supported languages and all popular writing scripts


EasyOCR is a machine learning model that can recognize text in images. It supports 80+ supported languages and all popular writing scripts.

This model is an implementation of EasyOCR found [here](https://github.com/JaidedAI/EasyOCR).


This repository provides scripts to run EasyOCR on Qualcomm® devices.
More details on model performance across various devices, can be found
[here](https://aihub.qualcomm.com/models/easyocr).



### Model Details

- **Model Type:** Model_use_case.image_to_text
- **Model Stats:**
  - Model checkpoint: easyocr-small-stage1
  - Input resolution: 608x800
  - Number of parameters (EasyOCRDetector): 20.8M
  - Model size (EasyOCRDetector) (float): 79.2 MB
  - Number of parameters (EasyOCRRecognizer): 3.84M
  - Model size (EasyOCRRecognizer) (float): 14.7 MB

| Model | Precision | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit | Target Model
|---|---|---|---|---|---|---|---|---|
| EasyOCRDetector | float | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | TFLITE | 272.633 ms | 0 - 38 MB | NPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRDetector | float | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | TFLITE | 66.837 ms | 1 - 49 MB | NPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRDetector | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | TFLITE | 38.331 ms | 0 - 154 MB | NPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRDetector | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | ONNX | 37.212 ms | 0 - 100 MB | NPU | [EasyOCR.onnx.zip](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.onnx.zip) |
| EasyOCRDetector | float | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | TFLITE | 70.052 ms | 1 - 39 MB | NPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRDetector | float | SA7255P ADP | Qualcomm® SA7255P | TFLITE | 272.633 ms | 0 - 38 MB | NPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRDetector | float | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | TFLITE | 38.595 ms | 1 - 150 MB | NPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRDetector | float | SA8295P ADP | Qualcomm® SA8295P | TFLITE | 76.792 ms | 1 - 42 MB | NPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRDetector | float | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | TFLITE | 38.613 ms | 0 - 145 MB | NPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRDetector | float | SA8775P ADP | Qualcomm® SA8775P | TFLITE | 70.052 ms | 1 - 39 MB | NPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRDetector | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | TFLITE | 28.182 ms | 1 - 50 MB | NPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRDetector | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX | 27.373 ms | 6 - 49 MB | NPU | [EasyOCR.onnx.zip](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.onnx.zip) |
| EasyOCRDetector | float | Samsung Galaxy S25 | Snapdragon® 8 Elite For Galaxy Mobile | TFLITE | 22.974 ms | 0 - 41 MB | NPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRDetector | float | Samsung Galaxy S25 | Snapdragon® 8 Elite For Galaxy Mobile | ONNX | 22.205 ms | 3 - 42 MB | NPU | [EasyOCR.onnx.zip](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.onnx.zip) |
| EasyOCRDetector | float | Snapdragon 8 Elite Gen 5 QRD | Snapdragon® 8 Elite Gen5 Mobile | TFLITE | 17.091 ms | 0 - 43 MB | NPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRDetector | float | Snapdragon 8 Elite Gen 5 QRD | Snapdragon® 8 Elite Gen5 Mobile | ONNX | 16.87 ms | 7 - 50 MB | NPU | [EasyOCR.onnx.zip](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.onnx.zip) |
| EasyOCRDetector | float | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 38.579 ms | 36 - 36 MB | NPU | [EasyOCR.onnx.zip](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.onnx.zip) |
| EasyOCRRecognizer | float | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | TFLITE | 531.491 ms | 8 - 18 MB | CPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRRecognizer | float | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | TFLITE | 122.208 ms | 8 - 27 MB | CPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRRecognizer | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | TFLITE | 104.226 ms | 8 - 11 MB | CPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRRecognizer | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | ONNX | 35.163 ms | 0 - 69 MB | NPU | [EasyOCR.onnx.zip](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.onnx.zip) |
| EasyOCRRecognizer | float | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | TFLITE | 356.313 ms | 10 - 21 MB | CPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRRecognizer | float | SA7255P ADP | Qualcomm® SA7255P | TFLITE | 531.491 ms | 8 - 18 MB | CPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRRecognizer | float | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | TFLITE | 98.14 ms | 8 - 11 MB | CPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRRecognizer | float | SA8295P ADP | Qualcomm® SA8295P | TFLITE | 214.189 ms | 7 - 24 MB | CPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRRecognizer | float | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | TFLITE | 104.441 ms | 7 - 10 MB | CPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRRecognizer | float | SA8775P ADP | Qualcomm® SA8775P | TFLITE | 356.313 ms | 10 - 21 MB | CPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRRecognizer | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | TFLITE | 97.216 ms | 3 - 24 MB | CPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRRecognizer | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX | 26.284 ms | 0 - 272 MB | NPU | [EasyOCR.onnx.zip](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.onnx.zip) |
| EasyOCRRecognizer | float | Samsung Galaxy S25 | Snapdragon® 8 Elite For Galaxy Mobile | TFLITE | 116.505 ms | 11 - 23 MB | CPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRRecognizer | float | Samsung Galaxy S25 | Snapdragon® 8 Elite For Galaxy Mobile | ONNX | 21.32 ms | 0 - 280 MB | NPU | [EasyOCR.onnx.zip](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.onnx.zip) |
| EasyOCRRecognizer | float | Snapdragon 8 Elite Gen 5 QRD | Snapdragon® 8 Elite Gen5 Mobile | TFLITE | 69.803 ms | 15 - 27 MB | CPU | [EasyOCR.tflite](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.tflite) |
| EasyOCRRecognizer | float | Snapdragon 8 Elite Gen 5 QRD | Snapdragon® 8 Elite Gen5 Mobile | ONNX | 19.355 ms | 0 - 304 MB | NPU | [EasyOCR.onnx.zip](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.onnx.zip) |
| EasyOCRRecognizer | float | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 35.996 ms | 12 - 12 MB | NPU | [EasyOCR.onnx.zip](https://huggingface.co/qualcomm/EasyOCR/blob/main/EasyOCR.onnx.zip) |




## Installation


Install the package via pip:
```bash
# NOTE: 3.10 <= PYTHON_VERSION < 3.14 is supported.
pip install "qai-hub-models[easyocr]"
```


## Configure Qualcomm® AI Hub Workbench to run this model on a cloud-hosted device

Sign-in to [Qualcomm® AI Hub Workbench](https://workbench.aihub.qualcomm.com/) with your
Qualcomm® ID. Once signed in navigate to `Account -> Settings -> API Token`.

With this API token, you can configure your client to run models on the cloud
hosted devices.
```bash
qai-hub configure --api_token API_TOKEN
```
Navigate to [docs](https://workbench.aihub.qualcomm.com/docs/) for more information.



## Demo off target

The package contains a simple end-to-end demo that downloads pre-trained
weights and runs this model on a sample input.

```bash
python -m qai_hub_models.models.easyocr.demo
```

The above demo runs a reference implementation of pre-processing, model
inference, and post processing.

**NOTE**: If you want running in a Jupyter Notebook or Google Colab like
environment, please add the following to your cell (instead of the above).
```
%run -m qai_hub_models.models.easyocr.demo
```


### Run model on a cloud-hosted device

In addition to the demo, you can also run the model on a cloud-hosted Qualcomm®
device. This script does the following:
* Performance check on-device on a cloud-hosted device
* Downloads compiled assets that can be deployed on-device for Android.
* Accuracy check between PyTorch and on-device outputs.

```bash
python -m qai_hub_models.models.easyocr.export
```



## How does this work?

This [export script](https://aihub.qualcomm.com/models/easyocr/qai_hub_models/models/EasyOCR/export.py)
leverages [Qualcomm® AI Hub](https://aihub.qualcomm.com/) to optimize, validate, and deploy this model
on-device. Lets go through each step below in detail:

Step 1: **Compile model for on-device deployment**

To compile a PyTorch model for on-device deployment, we first trace the model
in memory using the `jit.trace` and then call the `submit_compile_job` API.

```python
import torch

import qai_hub as hub
from qai_hub_models.models.easyocr import Model

# Load the model
torch_model = Model.from_pretrained()

# Device
device = hub.Device("Samsung Galaxy S25")

# Trace model
input_shape = torch_model.get_input_spec()
sample_inputs = torch_model.sample_inputs()

pt_model = torch.jit.trace(torch_model, [torch.tensor(data[0]) for _, data in sample_inputs.items()])

# Compile model on a specific device
compile_job = hub.submit_compile_job(
    model=pt_model,
    device=device,
    input_specs=torch_model.get_input_spec(),
)

# Get target model to run on-device
target_model = compile_job.get_target_model()

```


Step 2: **Performance profiling on cloud-hosted device**

After compiling models from step 1. Models can be profiled model on-device using the
`target_model`. Note that this scripts runs the model on a device automatically
provisioned in the cloud.  Once the job is submitted, you can navigate to a
provided job URL to view a variety of on-device performance metrics.
```python
profile_job = hub.submit_profile_job(
    model=target_model,
    device=device,
)
        
```

Step 3: **Verify on-device accuracy**

To verify the accuracy of the model on-device, you can run on-device inference
on sample input data on the same cloud hosted device.
```python
input_data = torch_model.sample_inputs()
inference_job = hub.submit_inference_job(
    model=target_model,
    device=device,
    inputs=input_data,
)
    on_device_output = inference_job.download_output_data()

```
With the output of the model, you can compute like PSNR, relative errors or
spot check the output with expected output.

**Note**: This on-device profiling and inference requires access to Qualcomm®
AI Hub Workbench. [Sign up for access](https://myaccount.qualcomm.com/signup).




## Deploying compiled model to Android


The models can be deployed using multiple runtimes:
- TensorFlow Lite (`.tflite` export): [This
  tutorial](https://www.tensorflow.org/lite/android/quickstart) provides a
  guide to deploy the .tflite model in an Android application.


- QNN (`.so` export ): This [sample
  app](https://docs.qualcomm.com/bundle/publicresource/topics/80-63442-50/sample_app.html)
provides instructions on how to use the `.so` shared library  in an Android application.


## View on Qualcomm® AI Hub
Get more details on EasyOCR's performance across various devices [here](https://aihub.qualcomm.com/models/easyocr).
Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/)


## License
* The license for the original implementation of EasyOCR can be found
  [here](https://github.com/JaidedAI/EasyOCR/blob/master/LICENSE).
* The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)



## References
* [Source Model Implementation](https://github.com/JaidedAI/EasyOCR)



## Community
* Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
* For questions or feedback please [reach out to us](mailto:[email protected]).