update

app.py

@@ -20,7 +20,7 @@ concat = lambda x: np.concatenate(x, axis=0)
 # Embeddings
 gdown.cached_download(
     url="https://drive.google.com/uc?id=116CiA_cXciGSl72tbAUDoN-f1B9Frp89",
-    path="./embeddings.pkl",
+    path="./embeddings.pickle",
     quiet=False,
     md5="002b2a7f5c80d910b9cc740c2265f058",
 )
@@ -84,15 +84,10 @@ def search(query_image, searcher=searcher):
     gallery_images = [training_folder.imgs[int(X)][0] for X in top_indices[:5]]
     predicted_labels = {id_to_bird_name[X[0]]: X[1] / 20.0 for X in result_ctr}
 
-    print("gallery_images:", gallery_images)
-
     # CHM Prediction
     kNN_results = (top1_label, result_ctr[0][1], gallery_images)
     support_files = [training_folder.imgs[int(X)][0] for X in indices[0]]
-
-    print(support_files)
     support_labels = [training_folder.imgs[int(X)][1] for X in indices[0]]
-    print(support_labels)
 
     support = [support_files, support_labels]
 
@@ -102,14 +97,22 @@ def search(query_image, searcher=searcher):
 
     viz_plot = plot_from_reranker_output(chm_output, draw_arcs=False)
 
-    return predicted_labels, gallery_images, viz_plot
+    return viz_plot, predicted_labels, gallery_images
 
 
 demo = gr.Interface(
     search,
     gr.Image(type="filepath"),
-    ["label", "gallery", "plot"],
-    examples=[["./examples/bird.jpg"]],
+    ["plot", "label", "gallery"],
+    examples=[
+        ["./examples/bird.jpg"],
+        ["./examples/Red_Winged_Blackbird_0012_6015.jpg"],
+        ["./examples/Red_Winged_Blackbird_0025_5342.jpg"],
+        ["./examples/sample1.jpeg"],
+        ["./examples/sample2.jpeg"],
+        ["./examples/Yellow_Headed_Blackbird_0020_8549.jpg"],
+        ["./examples/Yellow_Headed_Blackbird_0026_8545.jpg"],
+    ],
     description="WIP - kNN on CUB dataset",
     title="Work in Progress - CHM-Corr",
 )