Commit 03a86da7 authored by Oleg Dzhimiev's avatar Oleg Dzhimiev

Merge branch 'master' of git.elphel.com:Elphel/python3-imagej-tiff

parents f4b16af0 825bd240
......@@ -70,6 +70,45 @@ def readTFRewcordsEpoch(train_filename):
gt_ds = np.array(gt_ds_list)
return corr2d, target_disparity, gt_ds
def writeTFRewcordsImageTiles(img_path, tfr_filename): # test_set=False):
# train_filename = 'train.tfrecords' # address to save the TFRecords file
# open the TFRecords file
num_tiles = 242*324 # fixme
all_image_tiles = np.array(range(num_tiles))
corr_layers = ['hor-pairs', 'vert-pairs','diagm-pair', 'diago-pair']
img = ijt.imagej_tiff(test_corr, corr_layers, all_image_tiles)
corr2d = img.corr2d.reshape((num_tiles,-1))
target_disparity = img.target_disparity.reshape((num_tiles,-1))
gt_ds = img.gt_ds.reshape((num_tiles,-1))
if not '.tfrecords' in tfr_filename:
tfr_filename += '.tfrecords'
tfr_filename=tfr_filename.replace(' ','_')
try:
os.makedirs(os.path.dirname(tfr_filename))
except:
pass
writer = tf.python_io.TFRecordWriter(tfr_filename)
dtype_feature_corr2d = _dtype_feature(corr2d)
dtype_target_disparity = _dtype_feature(target_disparity)
dtype_feature_gt_ds = _dtype_feature(gt_ds)
for i in range(num_tiles):
x = corr2d[i].astype(np.float32)
y = target_disparity[i].astype(np.float32)
z = gt_ds[i].astype(np.float32)
d_feature = {'corr2d': dtype_feature_corr2d(x),
'target_disparity':dtype_target_disparity(y),
'gt_ds': dtype_feature_gt_ds(z)}
example = tf.train.Example(features=tf.train.Features(feature=d_feature))
writer.write(example.SerializeToString())
pass
writer.close()
sys.stdout.flush()
class ExploreData:
PATTERN = "*-DSI_COMBO.tiff"
......@@ -142,10 +181,6 @@ class ExploreData:
strength = np.nan_to_num(strength, copy = False) # likely should never happen
np.clip(disparity, disparity_min_clip, disparity_max_clip, out = disparity)
np.clip(strength, strength_min_clip, strength_max_clip, out = strength)
# if no_histogram:
# strength *= good_tiles[ids]
# if no_histogram:
# return None # no histogram, just condition data
good_tiles_list.append(good_tiles)
combo_rds = np.concatenate(list_rds)
hist, xedges, yedges = np.histogram2d( # xedges, yedges - just for debugging
......@@ -157,8 +192,6 @@ class ExploreData:
weights= np.concatenate(good_tiles_list).flatten())
for i, combo_rds in enumerate(list_rds):
for ids in range (combo_rds.shape[0]): #iterate over all scenes ds[2][rows][cols]
# strength = combo_rds[ids][...,1]
# strength *= good_tiles_list[i][ids]
combo_rds[ids][...,1]*= good_tiles_list[i][ids]
return hist, xedges, yedges
......@@ -636,6 +669,9 @@ class ExploreData:
print("Scene %d of %d -> %s"%(nscene, len(seed_list), tfr_filename))
writer.close()
sys.stdout.flush()
def showVariance(self,
rds_list, # list of disparity/strength files, suchas training, testing
......@@ -721,6 +757,20 @@ if __name__ == "__main__":
ml_subdir = sys.argv[4]
except IndexError:
ml_subdir = "ml"
# pathTFR = "/mnt/dde6f983-d149-435e-b4a2-88749245cc6c/home/eyesis/x3d_data/data_sets/tf_data_3x3b" #no trailing "/"
test_corr = '/home/eyesis/x3d_data/models/var_main/www/html/x3domlet/models/all-clean/overlook/1527257933_150165/v04/mlr32_18a/1527257933_150165-ML_DATA-32B-O-FZ0.05-MAIN.tiff'
scene = os.path.basename(test_corr)[:17]
scene_version= os.path.basename(os.path.dirname(os.path.dirname(test_corr)))
fname =scene+'-'+scene_version
img_filenameTFR = os.path.join(pathTFR,'img',fname)
writeTFRewcordsImageTiles(test_corr, img_filenameTFR)
pass
exit(0)
#Parameters to generate neighbors data. Set radius to 0 to generate single-tile
RADIUS = 1
......
This diff is collapsed.
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment