def group_l2_data():
print('group_l2_data')
train_dir = '/mnt/hard-ext/yomkiru/Data/Strawberries/l2_train'
test_dir = '/mnt/hard-ext/yomkiru/Data/Strawberries/l2_test'
utils.remake_dir(train_dir)
utils.remake_dir(test_dir)
data_dir = '/mnt/hard-ext/yomkiru/Data/Strawberries/l2_data'
images = fnmatch.filter(os.listdir(data_dir), '*.png')
train_count = 0
test_count = 0
for idx, imgname in enumerate(images):
fullname = os.path.join(data_dir, imgname)
if idx < len(images) * 0.1:
shutil.copy(fullname, os.path.join(test_dir, imgname))
shutil.copy(fullname[:-3] + 'out',
os.path.join(test_dir, imgname[:-3] + 'out'))
test_count += 1
else:
shutil.copy(fullname, os.path.join(train_dir, imgname))
shutil.copy(fullname[:-3] + 'out',
os.path.join(train_dir, imgname[:-3] + 'out'))
train_count += 1
print(train_count, test_count)
def test_sampling():
print('test_sampling')
target_dir = 'fig_rst'
utils.remake_dir('fig_rst')
sample_dir = '/mnt/hard-ext/yomkiru/Data/Strawberries/seg_sampling'
files = os.listdir(sample_dir)
fig = utils.init_figure_with_idx(1, figsize=[4, 4])
for idx, tname in enumerate(files):
if not tname.endswith('.png'):
continue
img_name = os.path.join(sample_dir, tname)
img_org = misc.imread(img_name)
img = misc.imresize(img_org, [144, 144, 3])
gt_file = open(img_name[:-3] + 'out', 'r')
gt = np.load(gt_file)
gt_file.close()
fig.clf()
draw_results_plot(img, gt)
utils.save_fig_in_dir(fig, dirname=target_dir,
filename=tname)
def gen_l2_data():
print('gen_l2_data')
target_dir = '/mnt/hard-ext/yomkiru/Data/Strawberries/l2_data'
utils.remake_dir(target_dir)
sample_dir = '/mnt/hard-ext/yomkiru/Data/Strawberries/seg_sampling'
files = os.listdir(sample_dir)
rot_options = np.linspace(0, 360, 36, endpoint=False)
flip_options = [False, True]
for idx, tname in enumerate(files):
if not tname.endswith('.png'):
continue
img_name = os.path.join(sample_dir, tname)
img_org = misc.imread(img_name)
img = misc.imresize(img_org, [144, 144, 3])
gt_file = open(img_name[:-3] + 'out', 'r')
gt = np.load(gt_file)
gt_file.close()
for t_flip in flip_options:
for t_rot in rot_options:
t_gt = copy.deepcopy(gt)
t_img = copy.deepcopy(img)
if t_flip:
t_img = t_img[:, ::-1]
t_gt[0] = (t_img.shape[1] -
t_gt[0])
t_img = utils.rotate_in_degrees(t_img, -t_rot)
rotate_point(t_gt, math.radians(t_rot), t_img.shape)
outfile_name = '%s_%d_%s' % (tname[:-4], t_rot,
'F' if t_flip else 'N')
outfile_name = os.path.join(target_dir, outfile_name)
misc.imsave(outfile_name + '.png', t_img)
outfile = open(outfile_name + '.out', 'w')
np.save(outfile, t_gt)
outfile.close()
print('created: %s' % outfile_name)
test_img = misc.imread('img_sample/test_1.png')
rmax, cmax, _ = test_img.shape
rsize, csize = 110, 110
box_list = list()
img_list_1 = list()
for ri in range(0, rmax - rsize + 20, 20):
for ci in range(0, cmax - csize + 20, 20):
t_img = test_img[ri:ri + rsize, ci:ci + csize]
img_list_1.append(t_img)
box_list.append(SlidingBox(ri, ci))
rst_1 = layer1.run_network(img_list_1)
rst_dir_l1 = 'l1_rst'
utils.remake_dir(rst_dir_l1)
fig1 = utils.init_figure_with_idx(0, figsize=[10, 6])
sp1 = utils.imshow_in_subplot(1, 1, 1, test_img)
img_list_2 = list()
box_list_2 = list()
for idx in range(len(img_list_1)):
if rst_1[idx][0] > rst_1[idx][1]: # good
img_list_2.append(img_list_1[idx])
box_list_2.append(box_list[idx])
sp1.add_patch(
patches.Rectangle((box_list[idx].ci, box_list[idx].ri),
csize,
rsize,
linewidth=1,
def group_data(l1_g_dir, l1_ng_dir, l1_train_dir, l1_test_dir):
print('group_data')
print(l1_g_dir, l1_ng_dir, l1_train_dir, l1_test_dir)
utils.remake_dir(l1_train_dir)
utils.remake_dir(os.path.join(l1_train_dir, 'g'))
utils.remake_dir(os.path.join(l1_train_dir, 'ng'))
utils.remake_dir(l1_test_dir)
utils.remake_dir(os.path.join(l1_test_dir, 'g'))
utils.remake_dir(os.path.join(l1_test_dir, 'ng'))
g_files = os.listdir(l1_g_dir)
ng_files = os.listdir(l1_ng_dir)
for fidx, gf_name in enumerate(g_files):
if fidx < len(g_files) * 0.1:
shutil.copy(os.path.join(l1_g_dir, gf_name),
os.path.join(l1_test_dir, 'g', gf_name))
else:
shutil.copy(os.path.join(l1_g_dir, gf_name),
os.path.join(l1_train_dir, 'g', gf_name))
for fidx, ngf_name in enumerate(ng_files):
if fidx < len(ng_files) * 0.1:
shutil.copy(os.path.join(l1_ng_dir, ngf_name),
os.path.join(l1_test_dir, 'ng', ngf_name))
else:
shutil.copy(os.path.join(l1_ng_dir, ngf_name),
os.path.join(l1_train_dir, 'ng', ngf_name))