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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def overlay_mask(self, image, predictions):
 """ Adds the instances contours for each predicted object. Each label has a different color. Arguments: image (np.ndarray):
 an image as returned by OpenCV predictions (BoxList):
 the result of the computation by the model. It should contain the field `mask` and `labels`. """

        masks = predictions.get_field("mask").numpy()
        labels = predictions.get_field("labels")

        colors = self.compute_colors_for_labels(labels).tolist()

        for mask, color in zip(masks, colors):
            thresh = mask[0, :, :, None]
            contours, hierarchy = cv2_util.findContours(
                thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE
            )
            image = cv2.drawContours(image, contours, -1, color, 3)

        composite = image

        return composite