temp

app.py

@@ -3,40 +3,43 @@ import gradio as gr
 def greet(name):
     return "Hello " + name + "!!"
 
+iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+iface.launch()
+
 
-# Model to use
-net_path = 'fire.pth'
+# # Model to use
+# net_path = 'fire.pth'
 
-# CPU / GPU
-device = 'cpu'
+# # CPU / GPU
+# device = 'cpu'
 
-# Images will be downscaled to this size prior processing with the network
-image_size = 1024
+# # Images will be downscaled to this size prior processing with the network
+# image_size = 1024
 
-# Wrapper
-def generate_matching_superfeatures(im1, im2, scale=6):
+# # Wrapper
+# def generate_matching_superfeatures(im1, im2, scale=6):
     
-    # Possible Scales for multiscale inference
-    scales = [2.0, 1.414, 1.0, 0.707, 0.5, 0.353, 0.25] 
-
-
-# GRADIO APP
-title = "Visualizing Super-features"
-description = "TBD"
-article = "<p style='text-align: center'><a href='https://github.com/naver/fire' target='_blank'>Original Github Repo</a></p>"
-
-
-iface = gr.Interface(
-    fn=generate_matching_superfeatures,
-    inputs=[
-        gr.inputs.Image(shape=(240, 240), type="pil"),
-        gr.inputs.Image(shape=(240, 240), type="pil"),
-        gr.inputs.Slider(minimum=1, maximum=7, step=1, default=2, label="Scale")],
-    outputs="plot",
-    enable_queue=True,
-    title=title,
-    description=description,
-    article=article,
-    examples=[["chateau_1.png", "chateau_2.png", 6]],
-)
-iface.launch()
+#     # Possible Scales for multiscale inference
+#     scales = [2.0, 1.414, 1.0, 0.707, 0.5, 0.353, 0.25] 
+
+
+# # GRADIO APP
+# title = "Visualizing Super-features"
+# description = "TBD"
+# article = "<p style='text-align: center'><a href='https://github.com/naver/fire' target='_blank'>Original Github Repo</a></p>"
+
+
+# iface = gr.Interface(
+#     fn=generate_matching_superfeatures,
+#     inputs=[
+#         gr.inputs.Image(shape=(240, 240), type="pil"),
+#         gr.inputs.Image(shape=(240, 240), type="pil"),
+#         gr.inputs.Slider(minimum=1, maximum=7, step=1, default=2, label="Scale")],
+#     outputs="plot",
+#     enable_queue=True,
+#     title=title,
+#     description=description,
+#     article=article,
+#     examples=[["chateau_1.png", "chateau_2.png", 6]],
+# )
+# iface.launch()