Devanagari-Handwritten-Character-Dataset

The dataset can be downloaded from: https://archive.ics.uci.edu/ml/datasets/Devanagari+Handwritten+Character+Dataset#

Accuracies of the models created:

Model	Accuracy
Logistic Regression	65.9%
SVM with degree 2 Polynomial Kernel	82.52%
KNN	83%
Random Forest	83.1%
Covolutional Autoencoder (CAE)	95.09%
CAE+SVM	95.9%
CNN	98.83
CNN+SVM	99.06%

For more details, see the Report.

Contributors:

1. anandthegreat
2. atul2938
3. singh4akash

To convert the raw dataset to csv format, use the following code:

root_dir = os.getcwd()
img_dir = [os.path.join(root_dir, 'train'),os.path.join(root_dir, 'test')]

pixels = np.array(['pixel_{:03d}'.format(x) for x in range(784)])

for i in range(0,2):
    for char_name in sorted(os.listdir(img_dir[i])):
        char_dir = os.path.join(img_dir[i], char_name)
        img_df = pd.DataFrame(columns=pixels)

        for img_file in sorted(os.listdir(char_dir)):
            image = imread(os.path.join(char_dir, img_file))
            image = image[2:30,2:30]
            image = pd.Series(image.flatten(),index = pixels)
            img_df = img_df.append(image.T, ignore_index=True)

        img_df = img_df.astype(np.uint8)
        img_df['character'] = char_name
        
        if(i==0):
            img_df.to_csv('data.csv', index=False, mode='a', header=flag)
        else:
            img_df.to_csv('data_test.csv', index=False, mode='a', header=flag)

or simply run the SVM code.