def im_detect_keypoints_hflip(model, im, target_scale, target_max_size, boxes):
    """Computes keypoint predictions on the horizontally flipped image.
    Function signature is the same as for im_detect_keypoints_aug.
    """
    # Compute keypoints for the flipped image
    im_hf = im[:, ::-1, :]
    boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])

    blob_conv, im_scale = im_conv_body_only(model, im_hf, target_scale, target_max_size)
    heatmaps_hf = im_detect_keypoints(model, im_scale, boxes_hf, blob_conv)

    # Invert the predicted keypoints
    heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)

    return heatmaps_inv 

def im_detect_keypoints_hflip(model, im, target_scale, target_max_size, boxes):
    """Computes keypoint predictions on the horizontally flipped image.
    Function signature is the same as for im_detect_keypoints_aug.
    """
    # Compute keypoints for the flipped image
    im_hf = im[:, ::-1, :]
    boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])

    blob_conv, im_scale = im_conv_body_only(model, im_hf, target_scale, target_max_size)
    heatmaps_hf = im_detect_keypoints(model, im_scale, boxes_hf, blob_conv)

    # Invert the predicted keypoints
    heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)

    return heatmaps_inv 

def im_detect_keypoints_hflip(model, im, target_scale, target_max_size, boxes):
    """Computes keypoint predictions on the horizontally flipped image.
    Function signature is the same as for im_detect_keypoints_aug.
    """
    # Compute keypoints for the flipped image
    im_hf = im[:, ::-1, :]
    boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])

    blob_conv, im_scale = im_conv_body_only(model, im_hf, target_scale, target_max_size)
    heatmaps_hf = im_detect_keypoints(model, im_scale, boxes_hf, blob_conv)

    # Invert the predicted keypoints
    heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)

    return heatmaps_inv 

def im_detect_keypoints_hflip(model, im, target_scale, target_max_size, boxes):
    """Computes keypoint predictions on the horizontally flipped image.
    Function signature is the same as for im_detect_keypoints_aug.
    """
    # Compute keypoints for the flipped image
    im_hf = im[:, ::-1, :]
    boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])

    blob_conv, im_scale = im_conv_body_only(model, im_hf, target_scale, target_max_size)
    heatmaps_hf = im_detect_keypoints(model, im_scale, boxes_hf, blob_conv)

    # Invert the predicted keypoints
    heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)

    return heatmaps_inv 

def im_detect_keypoints_hflip(model, im, target_scale, target_max_size, boxes):
    """Computes keypoint predictions on the horizontally flipped image.
    Function signature is the same as for im_detect_keypoints_aug.
    """
    # Compute keypoints for the flipped image
    im_hf = im[:, ::-1, :]
    boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])

    blob_conv, im_scale = im_conv_body_only(model, im_hf, target_scale, target_max_size)
    heatmaps_hf = im_detect_keypoints(model, im_scale, boxes_hf, blob_conv)

    # Invert the predicted keypoints
    heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)

    return heatmaps_inv 

def im_detect_keypoints_hflip(model, im, target_scale, target_max_size, boxes):
    """Computes keypoint predictions on the horizontally flipped image.
    Function signature is the same as for im_detect_keypoints_aug.
    """
    # Compute keypoints for the flipped image
    im_hf = im[:, ::-1, :]
    boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])

    im_scale = im_conv_body_only(model, im_hf, target_scale, target_max_size)
    heatmaps_hf = im_detect_keypoints(model, im_scale, boxes_hf)

    # Invert the predicted keypoints
    heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)

    return heatmaps_inv 

def im_detect_keypoints_hflip(model, im, target_scale, target_max_size, boxes):
    """Computes keypoint predictions on the horizontally flipped image.
    Function signature is the same as for im_detect_keypoints_aug.
    """
    # Compute keypoints for the flipped image
    im_hf = im[:, ::-1, :]
    boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])

    blob_conv, im_scale = im_conv_body_only(model, im_hf, target_scale, target_max_size)
    heatmaps_hf = im_detect_keypoints(model, im_scale, boxes_hf, blob_conv)

    # Invert the predicted keypoints
    heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)

    return heatmaps_inv 

def im_detect_keypoints_hflip(model, im, boxes):
    """Computes keypoint predictions on the horizontally flipped image.
    Function signature is the same as for im_detect_keypoints_aug.
    """
    # Compute keypoints for the flipped image
    im_hf = im[:, ::-1, :]
    boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])

    im_scales = im_conv_body_only(model, im_hf)
    heatmaps_hf = im_detect_keypoints(model, im_scales, boxes_hf)

    # Invert the predicted keypoints
    heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)

    return heatmaps_inv 

def im_detect_keypoints_hflip(model, im, target_scale, target_max_size, boxes):
    """Computes keypoint predictions on the horizontally flipped image.
    Function signature is the same as for im_detect_keypoints_aug.
    """
    # Compute keypoints for the flipped image
    im_hf = im[:, ::-1, :]
    boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])

    blob_conv, im_scale = im_conv_body_only(model, im_hf, target_scale, target_max_size)
    heatmaps_hf = im_detect_keypoints(model, im_scale, boxes_hf, blob_conv)

    # Invert the predicted keypoints
    heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)

    return heatmaps_inv 

def im_detect_keypoints_hflip(model, im, target_scale, target_max_size, boxes):
    """Computes keypoint predictions on the horizontally flipped image.
    Function signature is the same as for im_detect_keypoints_aug.
    """
    # Compute keypoints for the flipped image
    im_hf = im[:, ::-1, :]
    boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])

    blob_conv, im_scale = im_conv_body_only(model, im_hf, target_scale, target_max_size)
    heatmaps_hf = im_detect_keypoints(model, im_scale, boxes_hf, blob_conv)

    # Invert the predicted keypoints
    heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)

    return heatmaps_inv 

def im_detect_keypoints_hflip(model, im, boxes):
    """Computes keypoint predictions on the horizontally flipped image.
    Function signature is the same as for im_detect_keypoints_aug.
    """
    # Compute keypoints for the flipped image
    im_hf = im[:, ::-1, :]
    boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])

    im_scales = im_conv_body_only(model, im_hf)
    heatmaps_hf = im_detect_keypoints(model, im_scales, boxes_hf)

    # Invert the predicted keypoints
    heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)

    return heatmaps_inv 

def im_detect_keypoints_hflip(model, im, boxes):
    """Computes keypoint predictions on the horizontally flipped image.
    Function signature is the same as for im_detect_keypoints_aug.
    """
    # Compute keypoints for the flipped image
    im_hf = im[:, ::-1, :]
    boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])

    im_scales = im_conv_body_only(model, im_hf)
    heatmaps_hf = im_detect_keypoints(model, im_scales, boxes_hf)

    # Invert the predicted keypoints
    heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)

    return heatmaps_inv