Update inference.py

inference.py

@@ -49,7 +49,7 @@ def save_plot_as_png(prediction_result, map_name, legend, outputPath):
     legend_patch = h5_image.get_legend(map_name, legend)
     
     # Resize the legend to the specified dimensions
-    legend_resized = tf.image.resize(legend_patch, (256,256))
+    legend_resized = cv2.resize(legend_patch, (256,256))
 
     # Convert the legend to uint8 range [0, 255] if its dtype is float32
     if legend_resized.dtype == tf.float32:
@@ -162,10 +162,10 @@ def perform_inference(legend_patch, map_patch, model):
     """
     global h5_image
     
-    legend_resized = tf.image.resize(legend_patch, (h5_image.patch_size, h5_image.patch_size))
+    legend_resized = cv2.resize(legend_patch, (h5_image.patch_size, h5_image.patch_size))
     legend_resized = tf.cast(legend_resized, dtype=tf.float32) / 255.0
 
-    map_patch_resize = tf.image.resize(map_patch, (h5_image.patch_size, h5_image.patch_size))
+    map_patch_resize = cv2.resize(map_patch, (h5_image.patch_size, h5_image.patch_size))
     map_patch_resize = tf.cast(map_patch_resize, dtype=tf.float32) / 255.0
 
     # Concatenate along the third axis and normalize