Function cpp_preprocess

tests/compare_preprocessing.py:14–55

Replicate C++ sam3_preprocess_image exactly. C++ does: 1. Bilinear resize to img_size x img_size (half-pixel center mapping) 2. Quantize back to uint8 with rounding 3. Normalize: (pixel/255.0 - 0.5) / 0.5 4. Layout: CHW

(image_path, img_size=1008)

def cpp_preprocess(image_path, img_size=1008):
    """Replicate C++ sam3_preprocess_image exactly.

    C++ does:
    1. Bilinear resize to img_size x img_size (half-pixel center mapping)
    2. Quantize back to uint8 with rounding
    3. Normalize: (pixel/255.0 - 0.5) / 0.5
    4. Layout: CHW
    """
    img = Image.open(image_path).convert("RGB")
    src = np.array(img, dtype=np.float32)  # [H, W, 3]
    src_h, src_w = src.shape[:2]

    # C++ bilinear resize (half-pixel center mapping)
    dst = np.zeros((img_size, img_size, 3), dtype=np.uint8)
    sx = src_w / img_size
    sy = src_h / img_size

    for y in range(img_size):
        fy = (y + 0.5) * sy - 0.5
        y0 = max(0, int(fy))
        y1 = min(src_h - 1, y0 + 1)
        wy = fy - y0
        for x in range(img_size):
            fx = (x + 0.5) * sx - 0.5
            x0 = max(0, int(fx))
            x1 = min(src_w - 1, x0 + 1)
            wx = fx - x0
            for c in range(3):
                v = ((1 - wy) * ((1 - wx) * src[y0, x0, c] + wx * src[y0, x1, c]) +
                     wy * ((1 - wx) * src[y1, x0, c] + wx * src[y1, x1, c]))
                dst[y, x, c] = min(255, max(0, int(v + 0.5)))

    # Normalize and convert to CHW
    result = np.zeros((3, img_size, img_size), dtype=np.float32)
    for c in range(3):
        for y in range(img_size):
            for x in range(img_size):
                v = dst[y, x, c] / 255.0
                result[c, y, x] = (v - 0.5) / 0.5

    return result, dst


def python_preprocess(image_path, img_size=1008):