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DESCRIPTION.md

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+This demo uses a fake model to showcase iterative output. The Image output will update every time a generator is returned until the final image.

README.md

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+
 ---
-title: Fake Diffusion Main
-emoji: 🚀
-colorFrom: red
-colorTo: red
+title: fake_diffusion_main 
+emoji: 🔥
+colorFrom: indigo
+colorTo: indigo
 sdk: gradio
 sdk_version: 3.6
-app_file: app.py
+app_file: run.py
 pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

requirements.txt

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+numpy
+https://gradio-main-build.s3.amazonaws.com/c3bec6153737855510542e8154391f328ac72606/gradio-3.6-py3-none-any.whl

run.py

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+import gradio as gr
+import numpy as np
+import time
+
+# define core fn, which returns a generator {steps} times before returning the image
+def fake_diffusion(steps):
+    for _ in range(steps):
+        time.sleep(1)
+        image = np.random.random((600, 600, 3))
+        yield image
+
+    image = "https://i.picsum.photos/id/867/600/600.jpg?hmac=qE7QFJwLmlE_WKI7zMH6SgH5iY5fx8ec6ZJQBwKRT44" 
+    yield image
+
+demo = gr.Interface(fake_diffusion, 
+                    inputs=gr.Slider(1, 10, 3), 
+                    outputs="image")
+
+# define queue - required for generators
+demo.queue()
+
+demo.launch()