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app.py

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+import gradio as gr
+from fastai.vision.all import *
+from huggingface_hub import from_pretrained_fastai
+
+repo_id = "hugginglearners/kvasir-seg"
+learn = from_pretrained_fastai(repo_id)
+#labels = learn.dls.vocab
+
+def predict(img):
+    img = PILImage.create(img)
+    pred, _, _ = learn.predict(img)
+    return PILMask.create(pred*255)
+
+interface_options = {
+    "title": "kvasir-seg fastai segmentation",
+    "description": "tbd",
+    "interpretation": "default",
+    "layout": "horizontal",
+#    "examples": [
+#        "100098.jpg",
+#        "100002.jpg",
+#        "100048.jpg"
+    ],
+    "allow_flagging": "never",
+}
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(224, 224)),
+    outputs=gr.inputs.Image(shape=(224, 224)),
+    **interface_options,
+)
+
+launch_options = {
+    "enable_queue": True,
+    "share": False,
+}
+
+demo.launch(**launch_options)