diff --git a/umap_run.py b/umap_run.py
index cdc472f..c9e8058 100644
--- a/umap_run.py
+++ b/umap_run.py
@@ -5,7 +5,7 @@
 import json
 import pandas as pd
 
-from utils import UMAPParameters
+from utils import UMAPParameters, load_images_from_directory
 
 """ Compute UMAP
     Input: 1d data (N, M) or 2d data (N, H, W)
@@ -47,6 +47,8 @@ def computeUMAP(data,
     if images_dir == "data/example_latentrepresentation/f_vectors.parquet":
         df = pd.read_parquet(images_dir)
         images = df.values
+    else: # user uploaded zip file
+        images = load_images_from_directory(images_dir)
     print(images.shape)
 
     # Load dimension reduction parameter
diff --git a/utils.py b/utils.py
index 7b3c8aa..5e5f51e 100644
--- a/utils.py
+++ b/utils.py
@@ -1,4 +1,7 @@
 from pydantic import BaseModel, Field
+import os
+from PIL import Image
+import numpy as np
 
 class PCAParameters(BaseModel):
     n_components: int = Field(description='number of components to keep')
@@ -8,4 +11,17 @@ class UMAPParameters(BaseModel):
     min_dist: float = Field(description='min distance between points')
     n_neighbors: int = Field(description='number of nearest neighbors')
     
-
+def load_images_from_directory(directory_path):
+    image_data = []
+    for filename in os.listdir(directory_path):
+        if filename.endswith(".png"):
+            file_path = os.path.join(directory_path, filename)
+            try:
+                img = Image.open(file_path)
+                img_array = np.array(img)
+                image_data.append(img_array)
+            except Exception as e:
+                print(f"Error processing {file_path}: {e}")
+    
+    image_data = np.array(image_data)
+    return image_data
\ No newline at end of file