Update app.py

app.py

@@ -121,43 +121,31 @@ def detect_text(model_name, input_image, confidence_threshold):
 # --- 4. GRADIO INTERFACE ---
 # (This section remains exactly the same)
 with gr.Blocks() as demo:
-    gr.Markdown("# Meiki Text Detection")
+    gr.Markdown("# meiki text detect v0")
     gr.Markdown(
-        "Upload an image and choose a model to detect horizontal and vertical text lines. "
-        "The **small** model is more accurate, especially for dense text like manga, while the **tiny** model is much faster."
+        "upload an image and choose a model to detect horizontal and vertical text lines. "
+        "the **small** model is more accurate, especially for images with many text lines like manga, while the **tiny** model is much faster."
     )
     
     with gr.Row():
         with gr.Column():
-            input_image = gr.Image(type="numpy", label="Upload Image")
+            input_image = gr.Image(type="numpy", label="upload image")
             model_name = gr.Radio(
-                ["tiny", "small"], label="Choose Model", value="small"
+                ["tiny", "small"], label="choose model", value="small"
             )
             confidence_threshold = gr.Slider(
-                minimum=0.1, maximum=1.0, value=0.4, step=0.1, label="Confidence Threshold"
+                minimum=0.1, maximum=1.0, value=0.4, step=0.1, label="confidence threshold"
             )
-            detect_button = gr.Button("Detect Text", variant="primary")
+            detect_button = gr.Button("detect text", variant="primary")
             
         with gr.Column():
-            output_image = gr.Image(type="numpy", label="Result")
+            output_image = gr.Image(type="numpy", label="result")
             
     detect_button.click(
         fn=detect_text,
         inputs=[model_name, input_image, confidence_threshold],
         outputs=output_image
     )
-    
-    gr.Examples(
-        examples=[
-            ["example_vn.jpg", "small", 0.4],
-            ["example_manga.jpg", "small", 0.4],
-            ["example_manga.jpg", "tiny", 0.4]
-        ],
-        inputs=[input_image, model_name, confidence_threshold],
-        outputs=output_image,
-        fn=detect_text,
-        cache_examples=False
-    )
 
 # --- 5. LAUNCH THE APP ---
 demo.launch()