app.py

import os
import sys
import json
import tempfile
import uuid
import requests
from pathlib import Path

# Auto-install required packages
try:
    import gradio as gr
    import numpy as np
except ImportError:
    print("Installing required packages...")
    os.system(f"{sys.executable} -m pip install gradio numpy requests")
    import gradio as gr
    import numpy as np

# Try to import OpenCV - if not available, try to install it
try:
    import cv2
except ImportError:
    print("Installing OpenCV...")
    os.system(f"{sys.executable} -m pip install opencv-python-headless")
    try:
        import cv2
    except ImportError:
        print("Failed to install OpenCV. Will use simple image processing only.")
        cv2 = None

# Try to import moviepy (for video concatenation) - if not available, we'll use a simpler approach
try:
    from moviepy.editor import VideoFileClip, concatenate_videoclips
    moviepy_available = True
except ImportError:
    print("MoviePy not available. Will use simpler video processing.")
    moviepy_available = False

# Define the title and description
TITLE = "Simple Sign Language Translator"
DESCRIPTION = """This application translates English and Arabic text into sign language using simple video generation.
It translates Arabic to English when needed, then maps the English text to sign language representations.

**Features:**
- Supports both English and Arabic input
- Uses simple visual representations of signs
- Automatic language detection
"""

# Define paths for sign language videos
VIDEO_ROOT = "sign_videos"
os.makedirs(VIDEO_ROOT, exist_ok=True)
os.makedirs(f"{VIDEO_ROOT}/en", exist_ok=True)

# Define mapping of words to video files
SIGN_DICT = {
    "en": {
        "hello": f"{VIDEO_ROOT}/en/hello.mp4",
        "thank": f"{VIDEO_ROOT}/en/thank.mp4", 
        "you": f"{VIDEO_ROOT}/en/you.mp4",
        "please": f"{VIDEO_ROOT}/en/please.mp4",
        "wait": f"{VIDEO_ROOT}/en/wait.mp4",
        "help": f"{VIDEO_ROOT}/en/help.mp4",
        "yes": f"{VIDEO_ROOT}/en/yes.mp4",
        "no": f"{VIDEO_ROOT}/en/no.mp4",
    }
}

# Create a dictionary for English to Arabic translations and vice versa
TRANSLATIONS = {
    "hello": "مرحبا",
    "welcome": "أهلا وسهلا",
    "thank you": "شكرا",
    "please": "من فضلك",
    "wait": "انتظر",
    "help": "مساعدة",
    "yes": "نعم",
    "no": "لا",
    "how can i help you": "كيف يمكنني مساعدتك",
    "customer": "عميل",
    "service": "خدمة",
    "sorry": "آسف",
}

def detect_language(text):
    """Detect if the text is primarily English or Arabic"""
    if not text:
        return "unknown"
    
    # Simple detection by character set
    arabic_chars = set('ءآأؤإئابةتثجحخدذرزسشصضطظعغفقكلمنهوي')
    english_chars = set('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ')
    
    arabic_count = sum(1 for char in text if char in arabic_chars)
    english_count = sum(1 for char in text if char in english_chars)
    
    if arabic_count > english_count:
        return "ar"
    elif english_count > 0:
        return "en"
    else:
        return "unknown"

def translate_arabic_to_english(text):
    """Translate Arabic text to English using dictionary lookup"""
    if not text:
        return "", "No text to translate"
    
    # Very basic translation - look up Arabic phrases in our dictionary
    result = text
    for en, ar in TRANSLATIONS.items():
        result = result.replace(ar, en)
    
    return result, f"Translated to English: {result}"

def tokenize_text(text):
    """Split the text into tokens"""
    # Convert to lowercase for English
    text = text.lower()
    
    # Simple tokenization by splitting on spaces
    return text.split()

def create_simple_sign_video(text, output_path):
    """Create a simple video with text representation of sign language"""
    if cv2 is None:
        # If OpenCV is not available, create a very simple text file
        with open(output_path.replace('.mp4', '.txt'), 'w') as f:
            f.write(f"Sign representation for: {text}")
        return output_path.replace('.mp4', '.txt'), "Created text representation (OpenCV not available)"
    
    # If OpenCV is available, create a simple video
    height, width = 480, 640
    fps = 30
    seconds = 2
    
    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
    video = cv2.VideoWriter(output_path, fourcc, fps, (width, height))
    
    font = cv2.FONT_HERSHEY_SIMPLEX
    font_scale = 1.5
    font_color = (255, 255, 255)
    line_type = 2
    
    # Text positioning
    text_size = cv2.getTextSize(text, font, font_scale, line_type)[0]
    text_x = (width - text_size[0]) // 2
    text_y = (height + text_size[1]) // 2
    
    for i in range(int(fps * seconds)):
        # Create a gradient blue background
        frame = np.zeros((height, width, 3), dtype=np.uint8)
        for y in range(height):
            blue_val = int(50 + (y / height) * 100)
            frame[y, :] = [blue_val, 30, 20]  # BGR
        
        # Make the text pulse slightly
        pulse = 1.0 + 0.2 * np.sin(i * 0.2)
        cv2.putText(frame, text, (text_x, text_y), font, font_scale * pulse, font_color, line_type)
        
        # Add "SIGN LANGUAGE" text at bottom
        cv2.putText(frame, "SIGN LANGUAGE", (width//2 - 100, height - 30), 
                    font, 0.7, (200, 200, 200), 1)
        
        video.write(frame)
    
    video.release()
    return output_path, f"Created video representation for '{text}'"

def translate_to_sign(text):
    """Main function to translate text to sign language representation"""
    if not text:
        return None, ""
    
    # Detect the input language
    language = detect_language(text)
    if language == "unknown":
        return None, "Could not determine the language. Please use English or Arabic."
    
    try:
        # If Arabic, translate to English first
        if language == "ar":
            english_text, translation_status = translate_arabic_to_english(text)
            original_text = text
            translation_info = f"Original Arabic: \"{original_text}\"\n{translation_status}\n"
        else:
            english_text = text
            translation_info = ""
        
        # Tokenize the text
        tokens = tokenize_text(english_text)
        if not tokens:
            return None, translation_info + "No translatable tokens found."
        
        # Create a temporary directory for the output
        temp_dir = tempfile.gettempdir()
        output_path = os.path.join(temp_dir, f"sign_output_{uuid.uuid4()}.mp4")
        
        # Create a sign language video for the first token
        # In a full implementation, you would create videos for all tokens and concatenate them
        first_token = tokens[0] if tokens else "error"
        video_path, video_status = create_simple_sign_video(first_token, output_path)
        
        # Prepare status message
        status = translation_info + video_status
        if len(tokens) > 1:
            status += f"\nNote: Only showing sign for first word. Full text: {english_text}"
        
        return video_path, status
    
    except Exception as e:
        error_msg = str(e)
        print(f"Error during translation: {error_msg}")
        return None, f"Error during translation: {error_msg}"

# Create the Gradio interface
with gr.Blocks(title=TITLE) as demo:
    gr.Markdown(f"# {TITLE}")
    gr.Markdown(DESCRIPTION)
    
    with gr.Row():
        with gr.Column():
            # Input area
            text_input = gr.Textbox(
                lines=4,
                placeholder="Enter English or Arabic text here...",
                label="Text Input"
            )
            
            with gr.Row():
                clear_btn = gr.Button("Clear")
                translate_btn = gr.Button("Translate to Sign Language", variant="primary")
            
            # Status area
            status_output = gr.Textbox(label="Status", interactive=False)
        
        with gr.Column():
            # Output (video or text, depending on what's available)
            output_display = gr.Video(
                label="Sign Language Output",
                format="mp4",
                autoplay=True
            ) if cv2 is not None else gr.Textbox(label="Sign Representation", lines=3)
    
    # Examples in both languages
    gr.Examples(
        examples=[
            ["Hello, how can I help you?"],
            ["Thank you for your patience."],
            ["Yes, please wait."],
            ["مرحبا"],
            ["شكرا"],
            ["نعم، من فضلك انتظر"],
        ],
        inputs=[text_input],
        outputs=[output_display, status_output],
        fn=translate_to_sign
    )
    
    # Event handlers
    translate_btn.click(
        fn=translate_to_sign,
        inputs=[text_input],
        outputs=[output_display, status_output]
    )
    
    clear_btn.click(
        fn=lambda: ("", "Input cleared"),
        inputs=None,
        outputs=[text_input, status_output]
    )

# Launch the app
if __name__ == "__main__":
    demo.launch()