CORRECT FIX: Use python_version in README.md YAML only, remove runtime.txt, optimize deps

README.md

@@ -1,17 +1,17 @@
 ---
-title: Arabic Sign Language Recognition
+title: Arabic Sign Language API
 emoji: 🤟
 colorFrom: blue
 colorTo: green
 sdk: gradio
 sdk_version: 4.16.0
+python_version: "3.10"
 app_file: app.py
 pinned: false
 license: mit
-python_version: 3.10
 ---
 
-# Arabic Sign Language Recognition
+# Arabic Sign Language Recognition API
 
 Upload an image of an Arabic sign language gesture and get instant predictions!
 
@@ -48,8 +48,8 @@ Total: **43 classes**
 ## Technical Stack
 
 - Python 3.10
-- TensorFlow CPU 2.15.0
-- MediaPipe 0.10.9
+- TensorFlow CPU 2.20+
+- MediaPipe 0.10.9+
 - OpenCV (headless)
 - Gradio 4.16.0
 

app.py

@@ -1,5 +1,5 @@
 """
-Arabic Sign Language Recognition - Gradio Interface
+Arabic Sign Language Recognition API
 Optimized for Hugging Face Spaces with Python 3.10
 """
 
@@ -69,7 +69,7 @@ def predict_sign(image):
         # Load model if not loaded
         load_model()
         
-        # Convert BGR to RGB
+        # Convert BGR to RGB if needed
         if len(image.shape) == 3 and image.shape[2] == 3:
             image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
         else:
@@ -128,9 +128,9 @@ def predict_sign(image):
         return image, f"❌ Error: {str(e)}", "Please try again with a different image"
 
 # Create Gradio interface
-with gr.Blocks(title="Arabic Sign Language Recognition", theme=gr.themes.Soft()) as demo:
+with gr.Blocks(title="Arabic Sign Language API", theme=gr.themes.Soft()) as demo:
     gr.Markdown("""
-    # 🤟 Arabic Sign Language Recognition
+    # 🤟 Arabic Sign Language Recognition API
     
     Upload an image of an Arabic sign language gesture and get instant predictions!
     
@@ -165,14 +165,14 @@ with gr.Blocks(title="Arabic Sign Language Recognition", theme=gr.themes.Soft())
             confidence_text = gr.Markdown(label="Confidence")
     
     # Info section
-    with gr.Accordion("ℹ️ About this model", open=False):
+    with gr.Accordion("ℹ️ About this API", open=False):
         gr.Markdown("""
         ### Model Information
         
         - **Model**: Multi-Layer Perceptron (MLP)
         - **Input**: MediaPipe hand landmarks (21 points × 3 coordinates = 63 features)
         - **Output**: 43 classes (Arabic letters, numbers 0-10, space)
-        - **Framework**: TensorFlow/Keras
+        - **Framework**: TensorFlow/Keras (CPU optimized)
         - **Repository**: [katyy2000/arabic-sign-language-recognition](https://huggingface.co/katyy2000/arabic-sign-language-recognition)
         
         ### How it works
@@ -200,7 +200,7 @@ with gr.Blocks(title="Arabic Sign Language Recognition", theme=gr.themes.Soft())
 
 # Load model on startup
 print("="*60)
-print("🚀 Starting Arabic Sign Language Recognition")
+print("🚀 Starting Arabic Sign Language Recognition API")
 print("="*60)
 
 try:

requirements.txt

@@ -1,4 +1,4 @@
-tensorflow-cpu==2.15.0
-opencv-python-headless==4.8.1.78
-mediapipe==0.10.9
-huggingface_hub==0.20.3
+tensorflow-cpu>=2.20.0
+opencv-python-headless>=4.8.0
+mediapipe>=0.10.9
+huggingface_hub>=0.20.0

runtime.txt

@@ -1 +0,0 @@
-python-3.10