Added gradio app code

app.py

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+from transformers import pipeline
+import gradio as gr
+import numpy as np
+
+
+def predict(image):
+    result = pipe(image)
+    return image, [
+        (
+            np.array(subsection["mask"]) / 255,
+            subsection["label"],
+        )
+        for subsection in result
+    ]
+
+
+pipe = pipeline(
+    "image-segmentation",
+    model="SatwikKambham/segformer-b0-finetuned-suim",
+)
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.AnnotatedImage(
+        color_map={
+            "Background (waterbody)": "#000000",
+            "Human divers": "#0000FF",
+            "Aquatic plants and sea-grass": "#00FF00",
+            "Wrecks and ruins": "#FF0000",
+            "Robots (AUVs/ROVs/instruments)": "#FFFF00",
+            "Reefs and invertebrates": "#00FFFF",
+            "Fish and vertebrates": "#FF00FF",
+            "Sea-floor and rocks": "#FFFFFF",
+        }
+    ),
+    examples="examples",
+)
+
+demo.launch()

requirements.txt

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+transformers
+numpy