bho

app.py

@@ -21,19 +21,6 @@ MODELS = {
 
     
 image_list = loadPreloadedImages(gta_image_dir, city_image_dir, turin_image_dir)
-uuid_to_path = dict()
-
-for i in range(len(image_list)):
-    uid = str(uuid.uuid5(uuid.NAMESPACE_URL, image_list[i][1]))  
-    uuid_to_path[uid] = image_list[i][1]
-    image_list[i][1] = uid  
-
-def handle_image_click(uid):
-    print(uid)
-    print(type(uid))
-    print(uuid_to_path.get(uid))
-    return Image.open(uuid_to_path.get(uid)).convert("RGB")
-
 
 
 # %% prediction on an image
@@ -97,12 +84,15 @@ with gr.Blocks(title="Semantic Segmentation Predictors") as demo:
         gr.Markdown("## Preloaded images to be used for testing the model")
         gr.Markdown("You can use images from the Grand Theft Auto V video game, the Cityscapes dataset or even from Turin")
     with gr.Row():
-        image_gallery = gr.Gallery(value=image_list, label="Preloaded Examples",
-            type="value",  columns=5,  rows=4,
-            height=1050, allow_preview=False, show_label=False, 
-        )
-    
-    image_gallery.select(fn=handle_image_click, inputs=[], outputs=image_input)
+        def create_image_selector(image):
+            def select_image():
+                image_input.value = image
+                return gr.update(value=image, visible=True)
+            return select_image
+        
+        for img, path in image_list:
+            img_component = gr.Image(value=img, interactive=True, show_label=False)
+            img_component.select(fn=create_image_selector, inputs=[], outputs=image_input)
 
     submit_btn.click(
         fn=run_prediction,