Create Three.py

Three.py

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+import numpy as np
+from sklearn.neighbors import NearestNeighbors
+
+# Convert the feature vectors to a NumPy array
+features_array = np.array(list(features_dict.values()))
+
+# Create a NearestNeighbors object and fit it to the features array
+knn = NearestNeighbors(n_neighbors=11, metric='cosine')
+knn.fit(features_array)
+
+# Define a function to retrieve the most similar images to a query image
+def retrieve_similar_images(query_image_name, knn_model, features_dict):
+    # Get the features for the query image
+    query_features = features_dict[query_image_name]
+    # Reshape the features to match the expected input format for the knn_model
+    query_features = query_features.reshape(1, -