Update app.py

app.py

@@ -1,41 +1,20 @@
-# import gradio as gr
-# import numpy as np
-
-
-# def gennerateImage(input_array,eps):
-#     eps = eps / 100
-#     mask = np.random.random(input_array.shape)
-#     mask = mask * 2 - 1 # 将mask的值转换为-1到1之间
-#     noise_img = (input_array * (1 + mask * eps)).astype(np.uint8) % 255
-#     return noise_img
-
-# demo = gr.Interface(
-#     gennerateImage, 
-#     inputs=[
-#         gr.Image(),
-#         gr.Slider(1, 10, 3)
-#     ],
-#     outputs="image"
-#     )
-
-# demo.launch(share=True)
-
 import gradio as gr
+import numpy as np
 import time
 
-def slowly_reverse(word, progress=gr.Progress()):
-    progress(0, desc="Starting")
-    time.sleep(1)
-    progress(0.05)
-    new_string = ""
-    for letter in progress.tqdm(word, desc="Reversing"):
-        time.sleep(0.25)
-        new_string = letter + new_string
-    return new_string
+# 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://gradio-builds.s3.amazonaws.com/diffusion_image/cute_dog.jpg"
+    yield image
 
-demo = gr.Interface(slowly_reverse, gr.Text(), gr.Text())
 
-if __name__ == "__main__":
-    demo.queue(concurrency_count=10).launch(share=True)
+demo = gr.Interface(fake_diffusion, inputs=gr.Slider(1, 10, 3), outputs="image")
 
+# define queue - required for generators
+demo.queue()
 
+demo.launch()