{
  "context": "This criteria evaluates how well the engineer uses PyOpenCL's image and texture capabilities to create images from numpy arrays, read image data back to the host, and query supported image formats.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Image creation",
      "description": "Uses pyopencl.Image or pyopencl.image_from_array to create OpenCL image objects from numpy arrays",
      "max_score": 25
    },
    {
      "name": "Channel order handling",
      "description": "Correctly specifies channel_order (e.g., pyopencl.channel_order.RGB or pyopencl.channel_order.RGBA) based on the input array's channel count",
      "max_score": 15
    },
    {
      "name": "Channel type specification",
      "description": "Correctly specifies channel_type (e.g., pyopencl.channel_type.UNORM_INT8) appropriate for uint8 data",
      "max_score": 10
    },
    {
      "name": "Image reading",
      "description": "Uses pyopencl.enqueue_copy or pyopencl.enqueue_read_image to read image data from GPU to host memory",
      "max_score": 20
    },
    {
      "name": "Origin and region",
      "description": "Correctly specifies origin and region parameters when reading images (origin=(0,0,0) and region=(width, height, 1))",
      "max_score": 10
    },
    {
      "name": "Format querying",
      "description": "Uses context.get_supported_image_formats to query available image formats for the device",
      "max_score": 15
    },
    {
      "name": "Memory flags",
      "description": "Properly specifies memory flags (e.g., pyopencl.mem_flags.READ_ONLY or READ_WRITE) when creating images",
      "max_score": 5
    }
  ]
}