Update app.py

app.py

@@ -43,7 +43,7 @@ def get_figure(in_pil_img, in_results):
         w, h = prediction['box']['xmax'] - prediction['box']['xmin'], prediction['box']['ymax'] - prediction['box']['ymin']
 
         ax.add_patch(plt.Rectangle((x, y), w, h, fill=False, color=selected_color, linewidth=3))
-        ax.text(x, y, f"{prediction['label']}: {round(prediction['score']*100, 1)}%", fontdict=fdic)
+        # ax.text(x, y, f"{prediction['label']}: {round(prediction['score']*100, 1)}%", fontdict=fdic)
 
     plt.axis("off")
 
@@ -81,23 +81,23 @@ with gr.Blocks(title="Object Detection",
     # model = gr.Radio(["detr-resnet-50", "detr-resnet-101"], value="detr-resnet-50", label="Model name")
 
     # gr.HTML("""<br/>""")
-    gr.HTML("""<h4>Select an example by clicking a thumbnail below.</h4>""")
-    gr.HTML("""<h4>Or upload an image by clicking on the canvas.</h4>""")
+    # gr.HTML("""<h4>Select an example by clicking a thumbnail below.</h4>""")
+    # gr.HTML("""<h4>Or upload an image by clicking on the canvas.</h4>""")
 
     with gr.Row():
         input_image = gr.Image(label="Input image", type="pil")
-        output_image = gr.Image(label="Output image with predicted instances", type="pil")
+        output_image = gr.Image(label="Output image with object detection", type="pil")
 
     gr.Examples(['samples/cats.jpg', 'samples/detectron2.png', 'samples/cat.jpg', 'samples/hotdog.jpg'], inputs=input_image)
 
     # gr.HTML("""<br/>""")
-    gr.HTML("""<h4>Click "Infer" button to predict object instances. It will take about 10 seconds (on cpu)</h4>""")
+    gr.HTML("""<h4>Click "Infer" button to predict object instances. It will take about 10-15 seconds</h4>""")
 
     send_btn = gr.Button("Infer")
     send_btn.click(fn=infer, inputs=[input_image], outputs=[output_image])
  
 #demo.queue()
-demo.launch(debug=True)
+demo.launch()
 
 
 ### EOF ###