Commit 69def1b5 authored by Andrey Filippov's avatar Andrey Filippov
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parent f964c4f2

explore_data3.py

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nn_ds_neibs15.py

+1 −10
Original line number Original line Diff line number Diff line
@@ -199,8 +199,6 @@ def getMoreFiles(fpaths,rslt): 
                print_time("Done")

                print_time("Done")

        rslt.append(dataset)

        rslt.append(dataset)





   



#from http://warmspringwinds.github.io/tensorflow/tf-slim/2016/12/21/tfrecords-guide/

#from http://warmspringwinds.github.io/tensorflow/tf-slim/2016/12/21/tfrecords-guide/

def read_and_decode(filename_queue):

def read_and_decode(filename_queue):

    reader = tf.TFRecordReader()

    reader = tf.TFRecordReader()
@@ -262,8 +260,6 @@ def extend_img_to_clusters(datasets_img,radius): 
        rec['gt_ds'] =            add_neibs(add_margins(rec['gt_ds'].reshape((height,width,-1)), radius, np.nan), radius).reshape((num_tiles,-1))

        rec['gt_ds'] =            add_neibs(add_margins(rec['gt_ds'].reshape((height,width,-1)), radius, np.nan), radius).reshape((num_tiles,-1))

        pass

        pass









def reformat_to_clusters(datasets_data):

def reformat_to_clusters(datasets_data):

    cluster_size = (2 * CLUSTER_RADIUS + 1) * (2 * CLUSTER_RADIUS + 1)

    cluster_size = (2 * CLUSTER_RADIUS + 1) * (2 * CLUSTER_RADIUS + 1)

# Reformat input data

# Reformat input data
@@ -302,7 +298,6 @@ TILE_SIZE = TILE_SIDE* TILE_SIDE # == 81 
        rec['target_disparity'] = target_disparity.reshape((target_disparity.shape[0],-1)) 

        rec['target_disparity'] = target_disparity.reshape((target_disparity.shape[0],-1)) 

        rec['gt_ds'] =            gt_ds.reshape((gt_ds.shape[0],-1))

        rec['gt_ds'] =            gt_ds.reshape((gt_ds.shape[0],-1))







def replace_nan(datasets_data):

def replace_nan(datasets_data):

    cluster_size = (2 * CLUSTER_RADIUS + 1) * (2 * CLUSTER_RADIUS + 1)

    cluster_size = (2 * CLUSTER_RADIUS + 1) * (2 * CLUSTER_RADIUS + 1)

# Reformat input data

# Reformat input data
@@ -353,7 +348,6 @@ def shuffle_chunks_in_place(datasets_data, tiles_groups_per_chunk): 
        ds['target_disparity'] = ds['target_disparity'].reshape((chunks_per_file,-1))[permut].reshape((groups_per_file,-1))

        ds['target_disparity'] = ds['target_disparity'].reshape((chunks_per_file,-1))[permut].reshape((groups_per_file,-1))

        ds['gt_ds'] =            ds['gt_ds'].           reshape((chunks_per_file,-1))[permut].reshape((groups_per_file,-1))

        ds['gt_ds'] =            ds['gt_ds'].           reshape((chunks_per_file,-1))[permut].reshape((groups_per_file,-1))







def _setFileSlot(train_next,files):

def _setFileSlot(train_next,files):

    train_next['files'] = files

    train_next['files'] = files

    train_next['slots'] = min(train_next['files'], MAX_FILES_PER_GROUP)

    train_next['slots'] = min(train_next['files'], MAX_FILES_PER_GROUP)
@@ -377,8 +371,6 @@ def replaceDataset(datasets_data, new_dataset, nset, period, findx): 
    datasets_data[findx]['gt_ds']           [nset::period] =  new_dataset['gt_ds'] 

    datasets_data[findx]['gt_ds']           [nset::period] =  new_dataset['gt_ds'] 

    

    





    



def zip_lvar_hvar(datasets_all_data, del_src = True):

def zip_lvar_hvar(datasets_all_data, del_src = True):

#    cluster_size = (2 * CLUSTER_RADIUS + 1) * (2 * CLUSTER_RADIUS + 1)

#    cluster_size = (2 * CLUSTER_RADIUS + 1) * (2 * CLUSTER_RADIUS + 1)

# Reformat input data

# Reformat input data
@@ -416,7 +408,6 @@ def reduce_tile_size(datasets_data, num_tile_layers, reduced_tile_side): 
                                 [..., offs:offs+reduced_tile_side, offs:offs+reduced_tile_side].

                                 [..., offs:offs+reduced_tile_side, offs:offs+reduced_tile_side].

                                 reshape(-1,num_tile_layers*reduced_tile_side*reduced_tile_side))

                                 reshape(-1,num_tile_layers*reduced_tile_side*reduced_tile_side))

            

            

            

def result_npy_to_tiff(npy_path, absolute, fix_nan):

def result_npy_to_tiff(npy_path, absolute, fix_nan):

    

    

    """

    """