def make_efficient_example(ex,
further_expansion_factor=1,
further_scale_up=1,
dir_suffix=''):
"""Make example by storing the image in a cropped and resized version for efficient loading"""
# Determine which area we will need from the image
# This is a bit larger than the tight crop because of the geometric augmentations
max_rotate = np.pi / 6
padding_factor = 1 / 0.85
scale_up_factor = 1 / 0.85 * further_scale_up
scale_down_factor = 1 / 0.85
shift_factor = 1.1
base_dst_side = 256
box_center = boxlib.center(ex.bbox)
s, c = np.sin(max_rotate), np.cos(max_rotate)
w, h = ex.bbox[2:]
rot_bbox_side = max(c * w + s * h, c * h + s * w)
rot_bbox = boxlib.box_around(box_center, rot_bbox_side)
scale_factor = min(base_dst_side / np.max(ex.bbox[2:]) * scale_up_factor,
1)
expansion_factor = (padding_factor * shift_factor * scale_down_factor *
further_expansion_factor)
expanded_bbox = boxlib.expand(rot_bbox, expansion_factor)
expanded_bbox = boxlib.intersect(expanded_bbox,
np.array([0, 0, 1000, 1000]))
new_camera = copy.deepcopy(ex.camera)
new_camera.intrinsic_matrix[:2, 2] -= expanded_bbox[:2]
new_camera.scale_output(scale_factor)
new_camera.undistort()
new_im_relpath = ex.image_path.replace('h36m',
f'h36m_downscaled{dir_suffix}')
new_im_path = f'{paths.DATA_ROOT}/{new_im_relpath}'
if not (util.is_file_newer(new_im_path, "2019-11-14T23:33:14")
and improc.is_image_readable(new_im_path)):
im = improc.imread_jpeg(ex.image_path)
dst_shape = improc.rounded_int_tuple(scale_factor *
expanded_bbox[[3, 2]])
new_im = cameralib.reproject_image(im, ex.camera, new_camera,
dst_shape)
util.ensure_path_exists(new_im_path)
imageio.imwrite(new_im_path, new_im)
new_bbox_topleft = cameralib.reproject_image_points(
ex.bbox[:2], ex.camera, new_camera)
new_bbox = np.concatenate([new_bbox_topleft, ex.bbox[2:] * scale_factor])
ex = ps3d.Pose3DExample(new_im_relpath,
ex.world_coords,
new_bbox,
new_camera,
activity_name=ex.activity_name)
return ex
def make_efficient_example(ex, root_muco, i_person):
image_relpath = ex.image_path
max_rotate = np.pi / 6
padding_factor = 1 / 0.85
scale_up_factor = 1 / 0.85
scale_down_factor = 1 / 0.85
shift_factor = 1.2
base_dst_side = 256
box_center = boxlib.center(ex.bbox)
s = np.sin(max_rotate)
c = np.cos(max_rotate)
rot_bbox_size = (np.array([[c, s], [s, c]]) @ ex.bbox[2:, np.newaxis])[:, 0]
side = np.max(rot_bbox_size)
rot_bbox_size = np.array([side, side])
rot_bbox = boxlib.box_around(box_center, rot_bbox_size)
scale_factor = min(base_dst_side / np.max(ex.bbox[2:]) * scale_up_factor, 1)
expansion_factor = padding_factor * shift_factor * scale_down_factor
expanded_bbox = boxlib.expand(rot_bbox, expansion_factor)
expanded_bbox = boxlib.intersect(expanded_bbox, boxlib.full_box([2048, 2048]))
new_camera = ex.camera.copy()
new_camera.intrinsic_matrix[:2, 2] -= expanded_bbox[:2]
new_camera.scale_output(scale_factor)
new_camera.undistort()
dst_shape = improc.rounded_int_tuple(scale_factor * expanded_bbox[[3, 2]])
new_im_path = f'{root_muco}_downscaled/{image_relpath[:-4]}_{i_person:01d}.jpg'
if not (util.is_file_newer(new_im_path, "2020-02-15T23:28:26")):
im = improc.imread_jpeg(f'{root_muco}/{image_relpath}')
new_im = cameralib.reproject_image(im, ex.camera, new_camera, dst_shape, antialias_factor=4)
util.ensure_path_exists(new_im_path)
imageio.imwrite(new_im_path, new_im, quality=95)
new_bbox_topleft = cameralib.reproject_image_points(ex.bbox[:2], ex.camera, new_camera)
new_bbox = np.concatenate([new_bbox_topleft, ex.bbox[2:] * scale_factor])
if ex.mask is None:
noext, ext = os.path.splitext(image_relpath[:-4])
noext = noext.replace('unaugmented_set_001/', '')
mask = improc.decode_mask(util.load_pickle(f'{root_muco}/masks/{noext}.pkl'))
else:
mask = ex.mask
if mask is False:
new_mask_encoded = None
else:
new_mask = cameralib.reproject_image(mask, ex.camera, new_camera, dst_shape)
new_mask_encoded = improc.encode_mask(new_mask)
return p3ds.Pose3DExample(
os.path.relpath(new_im_path, paths.DATA_ROOT), ex.world_coords.astype(np.float32),
new_bbox.astype(np.float32), new_camera, mask=new_mask_encoded,
univ_coords=ex.univ_coords.astype(np.float32))
def get_expanded_crop_box(bbox, full_box, further_expansion_factor):
max_rotate = np.pi / 6
padding_factor = 1 / 0.85
scale_down_factor = 1 / 0.85
shift_factor = 1.1
s, c = np.sin(max_rotate), np.cos(max_rotate)
w, h = bbox[2:]
box_center = boxlib.center(bbox)
rot_bbox_side = max(c * w + s * h, c * h + s * w)
rot_bbox = boxlib.box_around(box_center, rot_bbox_side)
expansion_factor = (padding_factor * shift_factor * scale_down_factor *
further_expansion_factor)
expanded_bbox = boxlib.intersect(boxlib.expand(rot_bbox, expansion_factor),
full_box)
return expanded_bbox
def make_efficient_example(ex):
image_relpath = ex.image_path
max_rotate = np.pi / 6
padding_factor = 1 / 0.85
scale_up_factor = 1 / 0.85
scale_down_factor = 1 / 0.85
shift_factor = 1.2
base_dst_side = 256
box_center = boxlib.center(ex.bbox)
s, c = np.sin(max_rotate), np.cos(max_rotate)
w, h = ex.bbox[2:]
rot_bbox_side = max(c * w + s * h, c * h + s * w)
rot_bbox = boxlib.box_around(box_center, rot_bbox_side)
scale_factor = min(base_dst_side / np.max(ex.bbox[2:]) * scale_up_factor,
1)
expansion_factor = padding_factor * shift_factor * scale_down_factor
expanded_bbox = boxlib.expand(rot_bbox, expansion_factor)
expanded_bbox = boxlib.intersect(expanded_bbox,
np.array([0, 0, 2048, 2048]))
new_camera = ex.camera.copy()
new_camera.intrinsic_matrix[:2, 2] -= expanded_bbox[:2]
new_camera.scale_output(scale_factor)
new_camera.undistort()
dst_shape = improc.rounded_int_tuple(scale_factor * expanded_bbox[[3, 2]])
new_im_relpath = ex.image_path.replace('3dhp', f'3dhp_downscaled')
new_im_path = os.path.join(paths.DATA_ROOT, new_im_relpath)
if not (util.is_file_newer(new_im_path, "2019-11-14T23:32:07")
and improc.is_image_readable(new_im_path)):
im = improc.imread_jpeg(f'{paths.DATA_ROOT}/{image_relpath}')
new_im = cameralib.reproject_image(im, ex.camera, new_camera,
dst_shape)
util.ensure_path_exists(new_im_path)
imageio.imwrite(new_im_path, new_im)
new_bbox_topleft = cameralib.reproject_image_points(
ex.bbox[:2], ex.camera, new_camera)
new_bbox = np.concatenate([new_bbox_topleft, ex.bbox[2:] * scale_factor])
mask_rle_relpath = new_im_path.replace('Images', 'FGmaskImages').replace(
'.jpg', '.pkl')
mask_rle_path = os.path.join(paths.DATA_ROOT, mask_rle_relpath)
if util.is_file_newer(mask_rle_path, "2020-03-11T20:46:46"):
mask_runlength = util.load_pickle(mask_rle_path)
else:
mask_relpath = ex.image_path.replace('Images', 'FGmaskImages').replace(
'.jpg', '.png')
mask = imageio.imread(os.path.join(paths.DATA_ROOT, mask_relpath))
mask_reproj = cameralib.reproject_image(mask, ex.camera, new_camera,
dst_shape)
mask_runlength = get_mask_with_highest_iou(mask_reproj, new_bbox)
util.dump_pickle(mask_runlength, mask_rle_path)
return p3ds.Pose3DExample(new_im_relpath,
ex.world_coords,
new_bbox,
new_camera,
mask=mask_runlength,
univ_coords=ex.univ_coords)