Update app.py

app.py

@@ -6,11 +6,17 @@ from keras.models import load_model
 from keras.models import Model
 from datasets import load_dataset
 from sklearn.cluster import KMeans
-import matplotlib.pyplot as plt
+import matplotlib.pyplot as pl
+from huggingface_hub import hf_hub_download
 
-autoencoder = load_model("autoencoder_model.keras")
-encoded_images = np.load("X_encoded_compressed.npy")
+# Download and load model and encoded images
+model_path = hf_hub_download(repo_id="eybro/autoencoder", filename="autoencoder_model.keras")
+data_path = hf_hub_download(repo_id="eybro/encoded_images", filename="X_encoded_compressed.npy")
 
+autoencoder = load_model(model_path)
+encoded_images = np.load(data_path)
+
+# Load and split dataset
 dataset = load_dataset("eybro/images")
 split_dataset = dataset['train'].train_test_split(test_size=0.2, seed=42)  # 80% train, 20% test
 dataset['train'] = split_dataset['train']
@@ -67,7 +73,6 @@ def process_image(image):
 def inference(image):
     input_image = process_image(image)
 
-    
     nearest_neighbors = find_nearest_neighbors(encoded_images, input_image, top_n=5)
     
     # Print the results