Updated app.py

app.py

@@ -68,14 +68,14 @@ gr.Interface(fn=unpaired_img2img,
                     gr.inputs.Image(shape=(256,256))],
             outputs=gr.outputs.Image(type="numpy"),
             title="Unpaired Image to Image Translation",
-            examples=[['Horse to Zebra',"data/horse1.jpg"], 
-            ['Horse to Zebra',"data/horse3.jpg"],
-            ['Orange to Apple', "data/orange1.jpg"],
-            ['Orange to Apple', "data/orange2.jpg"],
-            ['Image to Van Gogh', "data/img1.jpg"],
-            ['Image to Van Gogh', "data/img2.jpg"],
-            ['Image to Monet', "data/img1.jpg"],
-            ['Image to Monet', "data/img2.jpg"]],
+            examples=[['Horse to Zebra', "examples/horse1.jpg"], 
+            ['Horse to Zebra', "examples/horse3.jpg"],
+            ['Orange to Apple', "examples/orange1.jpg"],
+            ['Orange to Apple', "examples/orange2.jpg"],
+            ['Image to Van Gogh', "examples/img1.jpg"],
+            ['Image to Van Gogh', "examples/img2.jpg"],
+            ['Image to Monet', "examples/img1.jpg"],
+            ['Image to Monet', "examples/img2.jpg"]],
             description="This is a PyTorch implementation of the unpaired image-to-image translation using a pretrained CycleGAN model. Kindly select first the type of translation you wish to see using the dropdown menu. Then, upload the image you wish to translate and click on the 'Submit' button.",
             article="To know more about Unpaired Image to Image Translation and CycleGAN, you may access their <a href = https://paperswithcode.com/paper/unpaired-image-to-image-translation-using>Papers with Code</a> page.",
             allow_flagging="never").launch(inbrowser=True)