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import gradio as gr
from ai4bharat.transliteration import XlitEngine
# Function for transliteration
def transliterate_to_kashmiri(user_input):
# Create an instance of the transliteration engine
e = XlitEngine(src_script_type="en", beam_width=5, rescore=False) # Adjusted beam_width for faster performance
# Perform transliteration
out = e.translit_sentence(user_input, lang_code="ks")
return out
# Examples for display in the interface
examples = [
["Hello, how are you?", "ہیلؤ، ہاؤ آر یو؟"],
["Good morning!", "گڈ مارننگ!"],
["What is your name?", "تُہند ناو کِیہ چھ؟"],
["I am feeling great today!", "آج سچِہ زبردست ہوں!"],
["See you later!", "بَعِد چُھٹ چھُ؟"]
]
# Path to your before and after image files
before_image_path = "https://cdn-uploads.huggingface.co/production/uploads/66afb3f1eaf3e876595627bf/cPHY7iEpErxAEakPBWvKR.png" # Replace with actual path to your "before" image
after_image_path = "https://cdn-uploads.huggingface.co/production/uploads/66afb3f1eaf3e876595627bf/TZNNe4XJcO4qzoFfug18v.png" # Replace with actual path to your "after" image
# Set up the Gradio interface
with gr.Blocks() as demo:
gr.Markdown("""
# English to Kashmiri Transliteration
This tool allows you to convert English sentences into Kashmiri transliterations.
**How to use:**
1. Enter a sentence in English in the text box.
2. Click "Transliterate" to see the Kashmiri output.
""")
# Display the examples
gr.Markdown("### Enter your own sentence:")
# Create input field for user sentence
user_input = gr.Textbox(label="Enter the sentence in English:", placeholder="e.g., Hello, how are you?")
# Output area for transliterated text
transliterated_output = gr.Textbox(label="Transliterated Output (Kashmiri):", placeholder="Result will be shown here")
# Button to trigger the transliteration
submit_button = gr.Button("Transliterate")
# Define the button action
submit_button.click(fn=transliterate_to_kashmiri, inputs=user_input, outputs=transliterated_output)
# Add examples to the interface for easy testing
gr.Examples(examples=examples, inputs=user_input, outputs=transliterated_output)
# Display the "Before" and "After" images
with gr.Row():
gr.Image(before_image_path, label="Before", elem_id="before-image", show_label=True)
gr.Image(after_image_path, label="After", elem_id="after-image", show_label=True)
# Launch the Gradio interface
demo.launch(share=True, inbrowser=True)
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