Create app.py

app.py

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+from PIL import Image
+import matplotlib.pyplot as plt
+from diffusers import DiffusionPipeline
+
+# Load the pre-trained model
+pipeline = DiffusionPipeline.from_pretrained("ankush-003/retinal_fundus")
+# pipeline.to("cuda")
+# gradio function for generating image
+def generate_image():
+    image = pipeline().images[0]
+    image.save("trial.png")
+    img = Image.open("trial.png")
+    # plt.imshow(img)
+    # plt.axis("off")
+    # plt.show()
+    return img
+
+# gradio interface
+import gradio as gr
+iface = gr.Interface(fn=generate_image, inputs=None, outputs="image")
+iface.launch(debug=True)