city

app.py

@@ -5,6 +5,7 @@ import numpy as np
 from PIL import Image
 import tensorflow as tf
 from transformers import SegformerFeatureExtractor, TFSegformerForSemanticSegmentation
+import os
 
 feature_extractor = SegformerFeatureExtractor.from_pretrained(
     "nvidia/segformer-b1-finetuned-cityscapes-1024-1024"
@@ -75,6 +76,10 @@ def draw_plot(pred_img, seg):
     return fig
 
 def sepia(input_text):
+    # Check if the input text is a valid file path
+    if not os.path.isfile(input_text):
+        return "Invalid file path. Please enter a valid image file path."
+
     # Load the image using the input text (assumed to be a path to an image)
     input_img = Image.open(input_text)
 
@@ -97,13 +102,13 @@ def sepia(input_text):
     pred_img = np.array(input_img) * 0.5 + color_seg * 0.5
     pred_img = pred_img.astype(np.uint8)
 
-    fig = draw_plot(pred_img, seg)
-    return fig
+    # Convert the image array to a format suitable for Gradio
+    pred_img = Image.fromarray(pred_img)
+
+    return pred_img
 
-demo = gr.Interface(fn=sepia,
-                    inputs=gr.Textbox(text="Enter text here"),
-                    outputs=['plot'],
-                    examples=["img_1.jpg", "img_2.jpeg", "img_3.jpg", "img_4.jpg", "img_5.png"],
-                    allow_flagging='never')
+# Define the Gradio interface
+iface = gr.Interface(fn=sepia, inputs="image", outputs="image")
 
-demo.launch()
+# Launch the Gradio app
+iface.launch()