simple blur model

.gitignore

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+output.png
+.cog
+__pycache__
+.DS_Store

cog.yaml

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+# Configuration for Cog ⚙️
+# Reference: https://github.com/replicate/cog/blob/main/docs/yaml.md
+
+build:
+  # set to true if your model requires a GPU
+  gpu: false
+
+  # a list of ubuntu apt packages to install
+  system_packages:
+    - "libpng-dev"
+    - "libjpeg-dev"
+    # - "libgl1-mesa-glx"
+    # - "libglib2.0-0"
+
+  # python version in the form '3.8' or '3.8.12'
+  python_version: "3.8"
+
+  # a list of packages in the format <package-name>==<version>
+  python_packages:
+    - "pillow==8.2.0"
+    # - "numpy==1.19.4"
+    # - "torch==1.8.0"
+    # - "torchvision==0.9.0"
+
+  # commands run after the environment is setup
+  # run:
+    # - "echo env is ready!"
+    # - "echo another command if needed"
+
+# predict.py defines how predictions are run on your model
+predict: "predict.py:Predictor"

predict.py

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+# Prediction interface for Cog ⚙️
+# https://github.com/replicate/cog/blob/main/docs/python.md
+
+import tempfile
+
+from cog import BasePredictor, Input, Path
+from PIL import Image, ImageFilter
+
+
+class Predictor(BasePredictor):
+    def predict(
+        self,
+        image: Path = Input(description="Input image"),
+        blur: float = Input(description="Blur radius", default=5),
+    ) -> Path:
+        if blur == 0:
+            return input
+        im = Image.open(str(image))
+        im = im.filter(ImageFilter.BoxBlur(blur))
+        out_path = Path(tempfile.mkdtemp()) / "out.png"
+        im.save(str(out_path))
+        return out_path