cog.yaml

# Configuration for Cog ⚙️
# Reference: https://cog.run/yaml

build:
  # set to true if your model requires a GPU
  gpu: false

  # a list of ubuntu apt packages to install
  # system_packages:
  #   - "libgl1-mesa-glx"
  #   - "libglib2.0-0"

  # python version in the form '3.11' or '3.11.4'
  python_version: "3.11"

  # path to a Python requirements.txt file
  python_requirements: requirements.txt

  # enable fast boots
  fast: false

  # 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

# Prediction interface for Cog ⚙️
# https://cog.run/python

from cog import BasePredictor, Input, Path
from PIL import Image
import os
import tempfile


class Predictor(BasePredictor):
    def predict(
        self,
        images: list[Path] = Input(description="A list of images to scale"),
        scale: float = Input(
            description="Factor to scale image by", ge=0, le=10, default=1.5
        ),
    ) -> list[Path]:
        """Run a single prediction on the model"""
        scaled_images = []

        for image_path in images:
            with Image.open(image_path) as img:
                original_width, original_height = img.size
                new_width = int(original_width * scale)
                new_height = int(original_height * scale)

                scaled_img = img.resize((new_width, new_height), Image.LANCZOS)

                # Create a temporary file for the scaled image
                with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(str(image_path))[1]) as temp_file:
                    scaled_img.save(temp_file.name)
                    scaled_images.append(Path(temp_file.name))

        return scaled_images

requirements.txt

# This is a normal Python requirements.txt file.

# You can add dependencies directly from PyPI:

Pillow==10.2.0