Update app.py

app.py

@@ -44,21 +44,9 @@ def inference(image_path):
 
 examples = ["examples/1.jpg", "examples/2.jpg", "examples/3.jpg"]
 with gr.Blocks(theme='gradio/monochrome') as demo:
-    gr.Markdown("# Speed Limit Detection demo")
-    gr.Markdown("**Author**: *Lu CHEN*")
-    gr.Markdown(
-        """This interactive demo is based on the Faster R-CNN model for object detection. The model is 
-        trained using the [Detectron2](https://github.com/facebookresearch/detectron2) library with a custom
-          dataset that I created by combining images from [Tsinghua-Tencent100K](https://cg.cs.tsinghua.edu.cn/traffic-sign/) and [GTSDB](https://benchmark.ini.rub.de/), both of which provide real-world traffic signs captured within the autonomous driving domain.
+    gr.Markdown("# Detección de velocidad - one Shot - ")
+    gr.Markdown("**Edición**: *SITIA*")
 
-To use the demo, simply upload an image and click on *"Infer"* to view the following results: 
-- **Detection**: outputs of Object Detector
-- **Detection summary**: a summary of the detection outputs
-
-You can also select an image from the cached **Examples** to quickly try out. Without clicking *"Infer"*, the cached outputs will be loaded automatically. 
-In case the output image seems too small, simply right-click on the image, and choose “Open image in new tab” to visualize it in full size.
-    """
-    )
     with gr.Row():
         with gr.Column():
             image = gr.Image(type="filepath")