Update app.py

app.py

@@ -32,7 +32,7 @@ app_ui = ui.page_fillable(
     shinyswatch.theme.minty(),
     ui.layout_sidebar(
         ui.sidebar(
-            ui.input_file("tile_image", "Choose TIFF File", accept=[".tif", ".tiff", ".png"], multiple=False),
+            ui.input_file("tile_image", "Choose an Image", accept=[".tif", ".tiff", ".png"], multiple=False),
             # Artwork by @allison_horst
             ui.input_selectize(
                 "xvar",
@@ -53,7 +53,7 @@ app_ui = ui.page_fillable(
             ui.input_switch("by_species", "Show species", value=True),
             ui.input_switch("show_margins", "Show marginal plots", value=True),
         ),
-        ui.output_image("uploaded_image"),  # display the uploaded TIFF sidewalk tile image
+        ui.output_image("uploaded_image"),  # display the uploaded sidewalk tile image
         ui.output_plot("prediction_plots", fill=True),
         ui.output_ui("value_boxes"),
         ui.output_plot("scatter", fill=True),
@@ -66,9 +66,9 @@ app_ui = ui.page_fillable(
 )
 
 ### HELPER FUNCTIONS ###
-def tif_bytes_to_pil_image(tif_bytes):
-    # Create a BytesIO object from the TIFF bytes
-    bytes_io = io.BytesIO(tif_bytes)
+def bytes_to_pil_image(bytes):
+    # Create a BytesIO object from the bytes
+    bytes_io = io.BytesIO(bytes)
     
     # Open the BytesIO object as an Image, crop to square, resize to 256
     image = Image.open(bytes_io).convert("RGB")
@@ -126,7 +126,7 @@ def server(input: Inputs, output: Outputs, session: Session):
         """Displays the uploaded image"""
         img_src = uploaded_image_path()
         if img_src:
-            img: ImgData = {"src": str(img_src), "width": "100px"}
+            img: ImgData = {"src": str(img_src), "width": "200px"}
             print("IMAGE", img)
             return img
         else:
@@ -187,7 +187,7 @@ def server(input: Inputs, output: Outputs, session: Session):
             image_bytes = f.read()
         
         # Convert the image bytes to a PIL Image
-        image = tif_bytes_to_pil_image(image_bytes)
+        image = bytes_to_pil_image(image_bytes)
 
         """ Prepare Inputs """
         # get input points prompt (grid of points)
@@ -234,7 +234,7 @@ def server(input: Inputs, output: Outputs, session: Session):
         if image is None or prob is None or prediction is None:
             # Return a placeholder plot or message
             fig, ax = plt.subplots()
-            ax.text(0.5, 0.5, "Upload a square image to see predictions. Predictions will take a few moments to load.", fontsize=12, ha="center")
+            ax.text(0.5, 0.5, "Upload an image to see predictions. Predictions will take a few moments to load.", fontsize=12, ha="center")
             ax.axis("off")  # Hide axis
             plt.tight_layout()
             return fig
@@ -252,14 +252,14 @@ def server(input: Inputs, output: Outputs, session: Session):
         axes[1].imshow(prob)
         axes[1].set_title("Probability Map")
         
-        # # Plot the prediction image on the right
-        # axes[2].imshow(prediction) 
-        # axes[2].set_title("Prediction")
+        # Plot the prediction image on the right
+        axes[2].imshow(prediction) 
+        axes[2].set_title("Prediction")
         
-        # # Plot the predicted mask on the right
-        # axes[3].imshow(image) 
-        # show_mask(prediction, axes[3])
-        # axes[3].set_title("Predicted Mask")
+        # Plot the predicted mask on the right
+        axes[3].imshow(image) 
+        show_mask(prediction, axes[3])
+        axes[3].set_title("Predicted Mask")
         
         # Hide axis ticks and labels
         for ax in axes: