def get_im_names(start_index, end_index):
imgset_path, jpg_dir, im_ext = io.get_ims_info()
im_names = ld.get_im_names(imgset_path) ##get all the im_names(always)
im_names = im_names[start_index:end_index + 1] ##trick2
if debug_flag:
print 'imgset_path:', imgset_path
print 'jpgdir_path:', jpg_dir
print 'im_ext:', im_ext
return im_names
def vis_picked_mult_instances():
print '=============================test vis_util================================='
track_mask_dir = io.get_track_mask_info(set_name)
prop_file_path, prop_file_ext = io.get_dets_info(set_name)
prop_arr = ld.load_det_proposals(prop_file_path)
if debug_flag:
print 'track_mask_dir:', track_mask_dir
print 'prop_file_path:', prop_file_path
print 'prop_file_ext:', prop_file_ext
print 'prop_arr.shape:', prop_arr.shape
##0> load image names
imgset_path, jpg_dir, im_ext = io.get_ims_info()
im_names = ld.get_im_names(imgset_path)
im_names = im_names[:test_frm_num]
##1> load color images
rgb_ims = ld.load_color_images(jpg_dir, im_names, im_ext)
vis_proposals_dir = io.get_vis_dir_info(vis_mult_prop_folder)
iter_name = 'iter' + str(4)
## draw bbox per person
frm_ids = np.unique(prop_arr[:, 0]).astype(int)
frm_num = len(frm_ids)
##for debug
for n_id in xrange(
frm_num): ## label is obj_id (42 has some problems, 56)
frm_id = frm_ids[n_id]
row_indexs = np.where(prop_arr[:, 0] == frm_id)[0] ##frame indexes
frm_prop_arr = prop_arr[row_indexs]
frm_labels = frm_prop_arr[:, 1].astype(int)
im = rgb_ims[n_id]
im_name = set_name + '_' + str(frm_ids[n_id] + shift_num).zfill(6)
if len(frm_labels) == 0:
continue
masks = load_frame_masks(track_mask_dir, frm_labels, iter_name,
im_name)
boxes = load_frame_boxes(track_mask_dir, frm_id, frm_labels, iter_name)
if debug_flag:
print 'frm_id:', frm_id
print 'frm_labels:', frm_labels.shape
print 'masks.shape:', len(masks)
print 'boxes.shape:', boxes.shape
vis_proposals_multi_instances(vis_proposals_dir, iter_name, im,
im_name, boxes, masks, frm_labels)
if debug_flag:
print 'track_mask_dir:', track_mask_dir
##print 'im_names:', im_names
print 'vis_proposals_dir:', vis_proposals_dir
def generate_final_vis_imgs():
##vis_picked_mult_instances() ## run this first, and then the following...\
final_vis_dir = '/mnt/phoenix_fastdir/experiments/final_vis'
final_vis_dir = os.path.join(final_vis_dir, set_name)
org_mrcnn_dir = os.path.join(final_vis_dir, 'org_MRCNN')
pickd_mrcnn_dir = os.path.join(final_vis_dir, 'picked_MRCNN')
link_mrcnn_dir = os.path.join(final_vis_dir, 'link_MRCNN')
##0> load image names
imgset_path, jpg_dir, im_ext = io.get_ims_info()
im_names = ld.get_im_names(imgset_path)
im_names = im_names[:test_frm_num]
# if debug_flag:
# print 'imgset_path:',imgset_path
# print 'jpg_dir:', jpg_dir
# print 'im_ext:', im_ext
# print 'im_names:', im_names
vis_link_imgs(im_names, org_mrcnn_dir, pickd_mrcnn_dir, link_mrcnn_dir)
def test_vis_gt_boxes():
imgset_path, jpg_dir, im_ext = io.get_ims_info()
im_names = ld.get_im_names(imgset_path)
ims = ld.load_color_images(jpg_dir, im_names, im_ext)
data_dir = os.path.join(mcfg.DATA.DATA_DIR, set_name)
tud_dets_gt_path = get_dets_annots_path(data_dir)
if debug_flag:
print 'imgset_path:', imgset_path
print 'jpg_dir:', jpg_dir
print 'im_ext:', im_ext
print 'data_dir:', data_dir
print 'tud_dets_gt_path:', tud_dets_gt_path
tud_dets_arr = load_dets_annots(tud_dets_gt_path)
frm_ids = tud_dets_arr[:, 0].astype(int)
obj_ids = tud_dets_arr[:, -1].astype(int)
# uniq_obj_ids=np.sort(np.unique(obj_ids))
# for u_id in uniq_obj_ids:
# label_row_indexes=np.where(obj_ids==u_id)[0]
# label_frm_ids=frm_ids[label_row_indexes]
# print 'u_id:',u_id
# print 'label_frm_ids:', label_frm_ids
# if debug_flag:
# print 'tud_dets_arr.shape:', tud_dets_arr.shape
# print 'frm_ids:', frm_ids
# print 'obj_ids:', obj_ids
# print 'uniq_obj_ids:', uniq_obj_ids
coords = tud_dets_arr[:, 1:5]
##vis_arr=tud_dets_arr[:,5]/100.0 ##make vis range in [0, 1.0]
boxes = coords_to_boxes(coords) ## unnormal
det_dir = mcfg.PROPOSAL.RES_DIR.replace('Continious', 'Discrete')
gt_det_dir = os.path.join(det_dir, 'vis_gt_boxes')
for n_id in xrange(len(im_names)):
im = ims[n_id]
im_name = im_names[n_id]
frm_id = int(im_name.split('_')[1])
row_indexes = np.where(frm_ids == frm_id)[0]
frm_boxes = boxes[row_indexes]
frm_obj_ids = obj_ids[row_indexes]
vis_gt_bboxes(gt_det_dir, im, im_name, frm_boxes, frm_obj_ids)
def load_color_ims(im_names):
imgset_path, jpg_dir, im_ext = io.get_ims_info()
ims = ld.load_color_images(jpg_dir, im_names, im_ext)
return ims
def get_im_names():
imgset_path, jpg_dir, im_ext = io.get_ims_info()
im_names = ld.get_im_names(imgset_path)
return im_names
def get_im_names():
##0> load image names
imgset_path, jpg_dir, im_ext = io.get_ims_info()
im_names = ld.get_im_names(imgset_path)
return im_names
