Update app.py

app.py

@@ -5,54 +5,74 @@ import gradio as gr
 # Install required packages if not already installed
 try:
     import sign_language_translator as slt
+    import requests
 except ImportError:
-    print("Installing sign-language-translator...")
-    os.system("pip install sign-language-translator --quiet")
+    print("Installing required packages...")
+    os.system("pip install sign-language-translator requests --quiet")
     import sign_language_translator as slt
+    import requests
 
-TITLE = "English to Sign Language Translator"
-DESCRIPTION = """Enter your English text and click Translate to generate a sign language video.
-The text is preprocessed, tokenized and each token is mapped to a prerecorded video which are concatenated and returned.
+TITLE = "English to Pakistan Sign Language Translator"
+DESCRIPTION = """This app translates English text to Pakistan Sign Language by first converting English to Urdu (which may improve vocabulary coverage), then using the Urdu text to generate sign language videos.
 
 **NOTE:**
-- This model only supports a fixed vocabulary of common words
+- The initial translation to Urdu uses a simple API-based translation
 - First-time loading may take a moment as the model downloads
-- For best results, use simple sentences with common words
+- For best results, use simple sentences
 """
 
-# Initialize the translation model (this may take some time on first run)
+# Global model variable
+model = None
+
 def get_model():
+    """Initialize the sign language translation model"""
     try:
-        return slt.models.ConcatenativeSynthesis("en", "pk-sl", "video")
+        return slt.models.ConcatenativeSynthesis("ur", "pk-sl", "video")
     except Exception as e:
         print(f"Error initializing model: {str(e)}")
         return None
 
-# Global model variable
-model = None
-
 def initialize_model():
+    """Ensure model is loaded"""
     global model
     if model is None:
         model = get_model()
     return model is not None
 
-def translate_text(text, format_type):
-    """Translate English text to sign language video"""
+def english_to_urdu(text):
+    """Translate English text to Urdu using a translation API"""
     if not text:
-        return None, "Please enter some text to translate."
+        return "", "Please enter text to translate"
+    
+    try:
+        # Using MyMemory translation API (free and doesn't require auth)
+        url = f"https://api.mymemory.translated.net/get?q={text}&langpair=en|ur"
+        response = requests.get(url)
+        data = response.json()
+        
+        if "responseData" in data and "translatedText" in data["responseData"]:
+            urdu_text = data["responseData"]["translatedText"]
+            return urdu_text, f"Translated to Urdu: {urdu_text}"
+        else:
+            return "", "Error: Could not translate to Urdu"
+    
+    except Exception as e:
+        print(f"Translation API error: {str(e)}")
+        return "", f"Error during Urdu translation: {str(e)}"
+
+def urdu_to_sign(urdu_text, format_type):
+    """Translate Urdu text to Pakistan Sign Language"""
+    if not urdu_text:
+        return None, "No Urdu text to translate"
     
     # Initialize model if not already done
     if not initialize_model():
-        return None, "Failed to initialize the translation model. Please try again."
+        return None, "Failed to initialize the translation model"
     
     try:
-        # Format the text (lowercase first letter as required by model)
-        text = text[:1].lower() + text[1:] if text else ""
-        
         # Configure model
-        model.text_language = "en"
-        model.sign_language = "pk-sl"
+        model.text_language = "ur"  # Urdu
+        model.sign_language = "pk-sl"  # Pakistan Sign Language
         model.sign_format = format_type
         
         if format_type == "landmarks":
@@ -60,7 +80,7 @@ def translate_text(text, format_type):
         
         # Translate
         output_path = "output.mp4"
-        sign = model.translate(text)
+        sign = model.translate(urdu_text)
         
         # Save output
         if isinstance(sign, slt.Landmarks):
@@ -71,12 +91,30 @@ def translate_text(text, format_type):
         else:
             sign.save(output_path, overwrite=True, codec="mp4v")
         
-        return output_path, f"Successfully translated: '{text}'"
+        return output_path, f"Successfully created sign language video"
     
     except Exception as e:
         error_msg = str(e)
-        print(f"Translation error: {error_msg}")
-        return None, f"Error during translation: {error_msg}"
+        print(f"Sign generation error: {error_msg}")
+        return None, f"Error generating signs: {error_msg}"
+
+def translate_english_to_sign(english_text, format_type):
+    """Complete translation pipeline: English → Urdu → Sign Language"""
+    if not english_text:
+        return None, ""
+    
+    # Step 1: Translate English to Urdu
+    urdu_text, urdu_status = english_to_urdu(english_text)
+    if not urdu_text:
+        return None, urdu_status
+    
+    # Step 2: Translate Urdu to Sign Language
+    video, sign_status = urdu_to_sign(urdu_text, format_type)
+    
+    # Combine status messages
+    status = f"English: \"{english_text}\"\nUrdu: \"{urdu_text}\"\n{sign_status}"
+    
+    return video, status
 
 # Create the Gradio interface
 with gr.Blocks(title=TITLE) as demo:
@@ -86,7 +124,7 @@ with gr.Blocks(title=TITLE) as demo:
     with gr.Row():
         with gr.Column():
             # Input area
-            text_input = gr.Textbox(
+            english_input = gr.Textbox(
                 lines=4,
                 placeholder="Enter English text here...",
                 label="English Text"
@@ -102,6 +140,10 @@ with gr.Blocks(title=TITLE) as demo:
                 clear_btn = gr.Button("Clear")
                 translate_btn = gr.Button("Translate", variant="primary")
             
+            # Intermediate Urdu translation
+            urdu_output = gr.Textbox(label="Urdu Translation", interactive=False)
+            
+            # Status area
             status_output = gr.Textbox(label="Status", interactive=False)
         
         with gr.Column():
@@ -116,31 +158,33 @@ with gr.Blocks(title=TITLE) as demo:
     # Examples
     gr.Examples(
         examples=[
-            ["Hello, how are you?", "video"],
+            ["How are you?", "video"],
             ["My name is John.", "video"],
-            ["Nice to meet you.", "video"],
+            ["Thank you for your help.", "video"],
             ["I want to learn sign language.", "video"]
         ],
-        inputs=[text_input, format_dropdown],
-        outputs=[video_output, status_output],
-        fn=translate_text
+        inputs=[english_input, format_dropdown],
+        outputs=[video_output, urdu_output, status_output],
+        fn=lambda text, fmt: (*translate_english_to_sign(text, fmt), english_to_urdu(text)[0])
     )
     
     # Event handlers
+    def handle_translation(text, fmt):
+        video, status = translate_english_to_sign(text, fmt)
+        urdu = english_to_urdu(text)[0] if text else ""
+        return video, urdu, status
+    
     translate_btn.click(
-        fn=translate_text,
-        inputs=[text_input, format_dropdown],
-        outputs=[video_output, status_output]
+        fn=handle_translation,
+        inputs=[english_input, format_dropdown],
+        outputs=[video_output, urdu_output, status_output]
     )
     
     clear_btn.click(
-        fn=lambda: ("", "Input cleared"),
+        fn=lambda: ("", "", "Input cleared"),
         inputs=None,
-        outputs=[text_input, status_output]
+        outputs=[english_input, urdu_output, status_output]
     )
-    
-    # Initialize model on load (not blocking)
-    demo.load(lambda: None, None, None)
 
 # Launch the app
 if __name__ == "__main__":