Update app.py

app.py

@@ -61,8 +61,8 @@ def load_plan_vi(mapa_seleccionado, uploaded_file):
 
     plan_im = Image.open(buf)
 
-    tick_positions = np.linspace(0, 256, 15)
-    tick_labels = np.linspace(0, 20, 15, dtype=int)
+    tick_positions = np.linspace(0, 256, 20)
+    tick_labels = np.linspace(0, 20, 20, dtype=int)
 
     buf = BytesIO()
     plt.imshow(plan_n)
@@ -571,6 +571,16 @@ with gr.Blocks() as demo:
     """
     ## Fast Indoor Radio Propagation Prediction using Deep Learning
     This app uses deep learning models for radio map estimation (RME) with and without interference, simulating 2.4 GHz and 5 GHz bands. RME involves estimating the received RF power based on spatial information maps.
+    
+    Instructions for use:
+
+    - A predefined list of indoor floor plans is available for use.
+    - You can upload your own indoor floor plan.
+    - Negative numbers are not allowed.
+    - The established format for the coordinates of each access point (AP) must be followed.
+    - A maximum of 2 APs per channel is allowed for the interference case.
+    - A maximum of 5 APs is allowed for the non-interference case.
+    - The uploaded plan must meet the dimensions [256,256,3], with free spaces as white pixels and walls as black pixels.
     """
     )
 
@@ -631,18 +641,4 @@ with gr.Blocks() as demo:
                           coords_ch1_input, coords_ch6_input, coords_ch11_input],
                   outputs=[image_ch1, image_ch6, image_ch11, image_ap1, image_ap2, image_cover_final, image_cells])
 
-    gr.Markdown(
-    """
-    Instructions for use:
-
-    - A predefined list of indoor floor plans is available for use.
-    - You can upload your own indoor floor plan.
-    - Negative numbers are not allowed.
-    - The established format for the coordinates of each access point (AP) must be followed.
-    - A maximum of 2 APs per channel is allowed for the interference case.
-    - A maximum of 5 APs is allowed for the non-interference case.
-    - The uploaded plan must meet the dimensions [256,256,3], with free spaces as white pixels and walls as black pixels.
-    """
-    )
-
 demo.launch()