Image Processing: Implement a Streaming Image Filter Pipeline

Question

## Problem

Design an image processing pipeline that applies a sequence of filters to a 2D pixel grid. Each filter is a function `(grid) -> grid`. Filters include: `grayscale`, `blur(radius)`, `threshold(value)`, and `crop(x1,y1,x2,y2)`. The pipeline must be lazy — filters are composed but not applied until `execute()` is called.

```python
class ImagePipeline:
    def __init__(self, image: list[list[int]]): ...
    def add_filter(self, name: str, **kwargs) -> 'ImagePipeline': ...
    def execute(self) -> list[list[int]]: ...
```

## Example

```
Input image (grayscale): 4x4 grid of pixel values 0-255

pipeline = ImagePipeline(image)
result = (
    pipeline
    .add_filter("blur", radius=1)
    .add_filter("threshold", value=128)
    .add_filter("crop", x1=1, y1=1, x2=3, y2=3)
    .execute()
)
# result is a 2x2 grid with filters applied in order
```

## Follow-ups

1. How would you parallelize the blur filter across rows or tiles?
2. If the image doesn't fit in memory, how do you apply filters in a streaming fashion?
3. How would you optimize a pipeline where two consecutive filters can be fused?
4. What interface changes are needed to support color (RGB) images?

Image Processing: Implement a Streaming Image Filter Pipeline

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