Update README.md

README.md

@@ -15,6 +15,8 @@ license: apache-2.0
 
 🎯 **Purpose:** To classify handwritten digits from images with high accuracy
 
+☁️ **Download:** [Click here](https://huggingface.co/lizardwine/DigitClassifier/resolve/main/DigitClassifier.keras?download=true) to download
+
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 ## 📚 Description
@@ -78,6 +80,80 @@ This model is designed to recognize handwritten digits from 0 to 9. It processes
 1. **Preprocess the Image:** Resize and normalize the image to 28x28 pixels with values between 0 and 1.
 2. **Feed the Image:** Input the preprocessed image into the model.
 3. **Interpret the Output:** Analyze the 10-dimensional output vector to find the digit with the highest probability.
+### Loading the Model
+
+To use the model, first, load it using Keras.
+
+```python
+from keras.models import load_model
+
+# Load the pre-trained model
+model = load_model('path/to/DigitClassifier.keras')
+```
+
+### Preprocessing the Input
+
+Preprocess the input image to fit the model's requirements.
+
+```python
+import numpy as np
+from keras.preprocessing import image
+
+def preprocess_image(img_path):
+    # Load the image
+    img = image.load_img(img_path, color_mode='grayscale', target_size=(28, 28))
+    # Convert to numpy array
+    img_array = image.img_to_array(img)
+    # Normalize the image
+    img_array = img_array / 255.0
+    # Reshape to add batch dimension
+    img_array = np.expand_dims(img_array, axis=0)
+    return img_array
+
+# Example usage
+img_path = 'path/to/your/image.png'
+processed_image = preprocess_image(img_path)
+```
+
+### Making Predictions
+
+Use the model to predict the digit from the processed image.
+
+```python
+# Predict the digit
+predictions = model.predict(processed_image)
+
+# Get the digit with the highest probability
+predicted_digit = np.argmax(predictions)
+print(f'The predicted digit is: {predicted_digit}')
+```
+
+### Full Example
+
+Combining all steps into a single example.
+
+```python
+from keras.models import load_model
+from keras.preprocessing import image
+import numpy as np
+
+# Load the pre-trained model
+model = load_model('path/to/DigitClassifier.keras')
+
+def preprocess_image(img_path):
+    img = image.load_img(img_path, color_mode='grayscale', target_size=(28, 28))
+    img_array = image.img_to_array(img)
+    img_array = img_array / 255.0
+    img_array = np.expand_dims(img_array, axis=0)
+    return img_array
+
+img_path = 'path/to/your/image.png'
+processed_image = preprocess_image(img_path)
+
+predictions = model.predict(processed_image)
+predicted_digit = np.argmax(predictions)
+print(f'The predicted digit is: {predicted_digit}')
+```
 
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