Execution speed seriously bothers application developers and users for wearable devices such as Google Glass. Intensive applications like 3D games suffer from significant delays when CPU is busy. Energy is another concern when the devices are in low battery level, but users need them for urgency use. To ease such pains, one approach is to expand the computational power by cloud offloading. This paradigm works well when the available Internet access has enough bandwidth. Another way is to leverage nearby devices for computation-offloading, which is known as device-to-device (D2D) offloading. In this paper, we present Dandelion, a unified code offloading system for wearable computing. Such applications can leverage both the nearby devices and cloud for performance acceleration and energy efficiency. Dandelion is a novel generic code offloading system for wearable computing with a reference implementation on Google Glass. Dandelion includes a programmer-friendly framework based on Java annotation, a lightweight offloading service, and a runtime task scheduler to make offloading decisions. We design some wearable applications and several parallel execution benchmark methods for Dandelion performance evaluation. Extensive experiments on a testbed of Google Glass and Android phones demonstrate that Dandelion generally achieves over 5X execution speedup for local execution and can quickly recover from errors caused by network disruption.