use .csv file for input

app.py

@@ -16,15 +16,8 @@ model = from_pretrained_keras(
 
 # Examples
 samples = []
-input_images = glob.glob("asset/source/*.png")
-examples = [
-    [
-        im,
-        f"asset/ground_truth/{im.split('/')[-1].split('.')[0]}.png",
-        f"asset/source/{im.split('/')[-1].split('.')[0]}.csv",
-    ]
-    for im in input_images
-]
+input_images = glob.glob("asset/source/*.csv")
+examples = [[im] for im in input_images]
 LABELS = ["wing", "body", "tail", "engine"]
 COLORS = ["blue", "green", "red", "pink"]
 
@@ -53,20 +46,18 @@ def visualize_data(point_cloud, labels, output_path=None):
 
 
 def inference(
-    im_path,
-    truth_path,
-    file_obj,
+    csv_file,
     output_path="asset/output",
     cpu=False,
 ):
 
-    csv_path = file_obj.name
+    csv_path = csv_file.name
     im_name = csv_path.split("/")[-1].split(".")[0]
 
     if os.path.exists(csv_path):
         df = pd.read_csv(csv_path, index_col=None)
         inputs = df[["x", "y", "z"]].values
-        y_test = df.iloc[:, 3:].values
+        y_test = df.iloc[:, 3:].values  # TODO: show ground truth image if y_test is not None
     else:
         warnings.warn(f"{csv_path} not found for {im_path}")
         return
@@ -82,8 +73,6 @@ article = "<div style='text-align: center;'><a href='https://nouamanetazi.me/' t
 iface = gr.Interface(
     inference,  # main function
     inputs=[
-        gr.inputs.Image(label="Image", type="filepath"),
-        gr.inputs.Image(label="Ground Truth", type="filepath"),
         "file",
     ],
     outputs=[