Update app.py

app.py

@@ -1,15 +1,35 @@
 import gradio as gr
 import numpy as np
-import tifffile as tiff
+import tifffile
 from aicsimageio import AICSImage  # To handle .czi files
 import matplotlib.pyplot as plt
+import predict_mask from prediction
 
 # Placeholder for your 3D model
 def process_3d_image(image):
     # Dummy model implementation: Replace with your actual model logic
-    binary_mask = (image > image.mean()).astype(np.uint8)
+    model_dir = 'https://huggingface.co/Hemaxi/3DCycleGAN/tree/main/CycleGANVesselSegmentation.h5'
+    binary_mask = predict_mask(model_dir,image)
     return binary_mask
 
+def auximread(filepath):
+
+    image = tifffile.imread(filepath)
+        
+    #the output image should be (X,Y,Z)
+    original_0 = np.shape(image)[0]
+    original_1 = np.shape(image)[1]
+    original_2 = np.shape(image)[2]
+
+    index_min = np.argmin([original_0, original_1, original_2])
+
+    if index_min == 0:
+        image = image.transpose(1,2,0)
+    elif index_min == 1:
+        image = image.transpose(0,2,1)
+
+    return image
+
 # Function to handle file input and processing
 def process_file(file):
     """
@@ -17,12 +37,7 @@ def process_file(file):
     """
     if file.name.endswith(".tif"):
         # Load .tif file as a 3D numpy array
-        image = tiff.imread(file.name)
-    elif file.name.endswith(".czi"):
-        # Load .czi file using AICSImage
-        img = AICSImage(file.name)
-        image = img.get_image_data("CZYX")  # Extracting 3D data
-        image = image[0, 0]  # Assuming single channel, single timepoint
+        image = auximread(file.name)
     else:
         raise ValueError("Unsupported file format. Please upload a .tif or .czi file.")