added image handling

app.py

@@ -1,5 +1,6 @@
 import torch, uuid
 import gradio as gr
+from PIL import Image
 
 from utils.imageHandling import hfImageToTensor, preprocessing, postprocessing, loadPreloadedImages
 from model.modelLoading import loadBiSeNet, loadBiSeNetV2
@@ -18,6 +19,7 @@ MODELS = {
 }
 
 
+    
 image_list = loadPreloadedImages(gta_image_dir, city_image_dir, turin_image_dir)
 uuid_to_path = dict()
 
@@ -26,6 +28,10 @@ for i in range(len(image_list)):
     uuid_to_path[uid] = image_list[i][1]
     image_list[i][1] = uid  
 
+def handle_image_click(uid):
+    return Image.open(uuid_to_path.get(uid)).convert("RGB")
+
+
 
 # %% prediction on an image
 
@@ -90,9 +96,10 @@ with gr.Blocks(title="Semantic Segmentation Predictors") as demo:
     with gr.Row():
         image_gallery = gr.Gallery(value=image_list, label="Preloaded Examples",
             type="value",  columns=5,  rows=4,
-            height=1200, allow_preview=False
+            height=1050, allow_preview=False, show_label=False, 
         )
-
+    
+    image_gallery.select(fn=handle_image_click, inputs=[], outputs=image_input)
 
     submit_btn.click(
         fn=run_prediction,