{ "cells": [ { "cell_type": "markdown", "id": "88d5f7fd-e30e-474e-ab44-01dbed16fd70", "metadata": { "tags": [] }, "source": [ "# Compatibility with cupy" ] }, { "cell_type": "code", "execution_count": 1, "id": "8b74ef1e-4753-449a-9e10-7cb3d25c2b7d", "metadata": { "tags": [] }, "outputs": [], "source": [ "import cupy\n", "import numpy as np\n", "import stackview" ] }, { "cell_type": "code", "execution_count": 2, "id": "0eba88e8-c6da-4b36-a8be-4095652c9e53", "metadata": { "tags": [] }, "outputs": [], "source": [ "image = np.random.random((100,100))" ] }, { "cell_type": "code", "execution_count": 3, "id": "74ae019e-78df-4958-8396-22d20ca6e059", "metadata": { "tags": [] }, "outputs": [], "source": [ "cp_image = cupy.asarray(image)" ] }, { "cell_type": "code", "execution_count": 4, "id": "ffe39017-c92f-4742-991d-b479cb7354e6", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
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