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# CS4804 Mini-Project OCR
## Due days
04/24 Presentation
**Coding should end before Presentation**
05/01 Final Report & Submission
## Presentation
A short class presentation (6~8 minutes)
Q & A (2 minutes)
Presentation:
* Title
* Problem statement and analysis
* Use-Case scenarios
* AI algorithm and model
* Results and demonstration
* Lesson learned
* Q & A
## Final Report
A maximum of 8 pages summarizes all aspects of the project:
* Problem statement and analysis
* Use-Case scenarios
* Literature review
* AI algorithm and model
* Results and demonstration
* Code and documentation
* Lessons learned
* Future work (if any)
## Final Submission
Compile all files into a zip file,
including:
* Presentation slides
* Code (file or link)
* Final report
Ensure that all links in your report and slides are accessible
## Code Specifications
1. Language: Python
2. Third-party library: Install all with ```pip install -r requirements.txt```
- tensorflow ```pip install tensorflow```
- scikit-learn ```pip install scikit-learn```
- openCV ```pip install opencv-python```
1. Language: Python3
2. Install third-party library
```pip install -r requirements.txt```
3. Trainning dataset:
1. [English Handwritten Characters](https://www.kaggle.com/datasets/dhruvildave/english-handwritten-characters-dataset) Size: 13.7 MB / 25.2 MB(after unzip)
2. [Handwritten Digits and English Characters](https://www.kaggle.com/datasets/hrishabhtiwari/handwritten-digits-and-english-characters/) Size: 85 MB / 545.57 MB(after unzip)
4. Usage
1. Train the model
```train-ocr-model.py [-h] -d DATASET [-m MODEL] [-p PLOT] [-s] [-t]```
Example:
```python train-ocr-model.py -d eng_dataset/dataset_mnist.csv -s -m model.keras -p result.png```
2. Implement OCR by running model
```run-ocr-model.py [-h] -m MODEL -i IMAGE -s SIZE```
```python train-ocr-model.py -d eng_dataset/dataset_mnist.csv -s -m new-model.keras -p result.png```
Example:
```python run-ocr-model.py -i simple_ocr_example/test_cases/hand_writing/1-image.png -m new-model.keras -s 28```
```python run-ocr-model.py -m model.keras -i /test_cases/hand_writing/1-image.png -s 28```
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