update Readme

README.md

 # 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```