Commit 5591b717 authored by Oleg Dzhimiev's avatar Oleg Dzhimiev
Browse files

preparing to feed nn

parent c21e72b7

pack_tile.py

+38 −0
Original line number Original line Diff line number Diff line
@@ -67,3 +67,41 @@ def pack_tile(tile,lut): 
    out = np.append(out,layer)

    out = np.append(out,layer)





  return out

  return out



# tiles are already packed

def get_tile_with_neighbors(tiles,i,j,radius):



  out = np.array([])

  # max

  Y,X = tiles.shape[0:2]

  #print(str(Y)+" "+str(X))



  for k in range(2*radius+1):



    y = i+k-radius

    if   y<0:

      y = 0

    elif y>(Y-1):

      y = Y-1



    for l in range(2*radius+1):



      x = j+l-radius

      if   x<0:

        x = 0

      elif x>(X-1):

        x = X-1



      out = np.append(out,tiles[y,x])



  return out

test_nn_feed.py

+107 −14
Original line number Original line Diff line number Diff line
@@ -8,6 +8,8 @@ __email__ = "oleg@elphel.com" 
Open all tiffs in a folder, combine a single tiff from randomly selected

Open all tiffs in a folder, combine a single tiff from randomly selected

tiles from originals

tiles from originals

'''

'''

import tensorflow as tf

#import tensorflow.contrib.slim as slim





from PIL import Image

from PIL import Image
@@ -21,32 +23,49 @@ import pack_tile as pile 
import numpy as np

import numpy as np

import itertools

import itertools





import time



sys.exit()



#http://stackoverflow.com/questions/287871/print-in-terminal-with-colors-using-python

class bcolors:

    HEADER = '\033[95m'

    OKBLUE = '\033[94m'

    OKGREEN = '\033[92m'

    WARNING = '\033[38;5;214m'

    FAIL = '\033[91m'

    ENDC = '\033[0m'

    BOLD = '\033[1m'

    BOLDWHITE = '\033[1;37m'

    UNDERLINE = '\033[4m'





def print_time():

  print(bcolors.BOLDWHITE+"time: "+str(time.time())+bcolors.ENDC)



# USAGE: python3 test_3.py some-path

# USAGE: python3 test_3.py some-path





VALUES_LAYER_NAME = 'other'

VALUES_LAYER_NAME = 'other'

LAYERS_OF_INTEREST = ['diagm-pair', 'diago-pair', 'hor-pairs', 'vert-pairs']

RADIUS = 1





try:

try:

  src = sys.argv[1]

  src = sys.argv[1]

except IndexError:

except IndexError:

  src = "."

  src = "."





print_time()



tlist = glob.glob(src+"/*.tiff")

tlist = glob.glob(src+"/*.tiff")





print("Found "+str(len(tlist))+" tiff files:")

print("Found "+str(len(tlist))+" preprocessed tiff files:")

print("\n".join(tlist))

print("\n".join(tlist))



print_time()

''' WARNING, assuming:

''' WARNING, assuming:

      - timestamps and part of names match

      - timestamps and part of names match

      - layer order and names are identical

      - layer order and names are identical

'''

'''





# CONSTANTS



RADIUS = 1

LAYERS_OF_INTEREST = ['diagm-pair','diago-pair']







# open the first one to get dimensions and other info

# open the first one to get dimensions and other info

tiff = ijt.imagej_tiff(tlist[0])

tiff = ijt.imagej_tiff(tlist[0])

#del tlist[0]

#del tlist[0]
@@ -59,14 +78,17 @@ labels = tiff.labels.copy() 
labels.remove(VALUES_LAYER_NAME)

labels.remove(VALUES_LAYER_NAME)





print("Image data layers:  "+str(labels))

print("Image data layers:  "+str(labels))

print("Layers of interest: "+str(LAYERS_OF_INTEREST))

print("Values layer: "+str([VALUES_LAYER_NAME]))

print("Values layer: "+str([VALUES_LAYER_NAME]))





# create copies

# create copies

tiles  = np.copy(tiff.getstack(labels,shape_as_tiles=True))

tiles  = np.copy(tiff.getstack(labels,shape_as_tiles=True))

tiles_bkp = np.copy(tiles)

values = np.copy(tiff.getvalues(label=VALUES_LAYER_NAME))

values = np.copy(tiff.getvalues(label=VALUES_LAYER_NAME))





print("Tiled tiff shape: "+str(tiles.shape))

#gt = values[:,:,1:3]



print("Mixed tiled input data shape: "+str(tiles.shape))

#print_time()





# now generate a layer of indices to get other tiles

# now generate a layer of indices to get other tiles

indices = np.random.random_integers(0,len(tlist)-1,size=(tiles.shape[0],tiles.shape[1]))

indices = np.random.random_integers(0,len(tlist)-1,size=(tiles.shape[0],tiles.shape[1]))
@@ -97,7 +119,8 @@ for i in range(1,len(tlist)): 
for i in range(1,len(shuffle_counter)):

for i in range(1,len(shuffle_counter)):

  shuffle_counter[0] -= shuffle_counter[i]

  shuffle_counter[0] -= shuffle_counter[i]





print("Tiffs shuffle counter = "+str(shuffle_counter))

print("Tiff files parts count in the mixed input = "+str(shuffle_counter))

print_time()





# test later

# test later
@@ -107,7 +130,77 @@ print("Tiffs shuffle counter = "+str(shuffle_counter)) 
# Parse packing table

# Parse packing table

# packing table name

# packing table name

ptab_name = "tile_packing_table.xml"

ptab_name = "tile_packing_table.xml"

pt = pile.PackingTable(ptab_name,LAYERS_OF_INTEREST).lut

ptab = pile.PackingTable(ptab_name,LAYERS_OF_INTEREST).lut



# might not need it because going to loop through anyway

packed_tiles = np.array([[pile.pack_tile(tiles[i,j],ptab) for j in range(tiles.shape[1])] for i in range(tiles.shape[0])])



packed_tiles = np.dstack((packed_tiles,values[:,:,0]))



print("Packed (81x4 -> 1x(25*4+1)) tiled input shape: "+str(packed_tiles.shape))

print_time()



#for i in range(tiles.shape[0]):

#  for j in range(tiles.shape[1]):

#    nn_input = pile.get_tile_with_neighbors(tiles,i,j,RADIUS)

#    print("tile: "+str(i)+", "+str(j)+": shape = "+str(nn_input.shape))

#print_time()



result_dir = './result/'

save_freq = 500



def lrelu(x):

    return tf.maximum(x*0.2,x)



def network(input):



  fc1 = slim.fully_connected(input,42,activation_fn=lrelu,scope='g_fc1')

  fc2 = slim.fully_connected(fc1,  21,activation_fn=lrelu,scope='g_fc2')

  fc3 = slim.fully_connected(fc2,   1,activation_fn=lrelu,scope='g_fc3')



  return fc3





sess = tf.session()



in_tile = tf.placeholder(tf.float32,[None,None,101])

gt      = tf.placeholder(tf.float32,[None,None,2])

out = network(in_tile)



G_loss = tf.reduce_mean(tf.abs(out[:,0]-gt[:,0]))

t_vars=tf.trainable_variables()

lr=tf.placeholder(tf.float32)

G_opt=tf.train.AdamOptimizer(learning_rate=lr).minimize(G_loss,var_list=[var for var in t_vars if var.name.startswith('g_')])



saver=tf.train.Saver()

sess.run(tf.global_variables_initializer())

ckpt=tf.train.get_checkpoint_state(checkpoint_dir)



if ckpt:

  print('loaded '+ckpt.model_checkpoint_path)

  saver.restore(sess,ckpt.model_checkpoint_path)





allfolders = glob.glob('./result/*0')

lastepoch = 0

for folder in allfolders:

  lastepoch = np.maximum(lastepoch, int(folder[-4:]))



#g_loss = np.zeros((,1))



learning_rate = 1e-4

for epoch in range(lastepoch,4001):

  if os.path.isdir("result/%04d"%epoch):

    continue

  cnt=0

  if epoch > 2000:

    learning_rate = 1e-5



  for ind in np.random.permutation(tiles.shape[0]*tiles.shape[1]):



    input_patch = tiles[i,j]

    gt_patch = values[i,j,1:2]

test_tf_setup.py

0 → 100644
+58 −0
Original line number Original line Diff line number Diff line 
#!/usr/bin/env python3



__copyright__ = "Copyright 2018, Elphel, Inc."

__license__   = "GPL-3.0+"

__email__     = "oleg@elphel.com"



'''

Test:

  nvidia graphic card

  cuda installation

  tensorflow



Comment:

  With nvidia + tensorflow - any software update casually breaks everything



'''



import subprocess

import re



#http://stackoverflow.com/questions/287871/print-in-terminal-with-colors-using-python

class bcolors:

    HEADER = '\033[95m'

    OKBLUE = '\033[94m'

    OKGREEN = '\033[92m'

    WARNING = '\033[38;5;214m'

    FAIL = '\033[91m'

    ENDC = '\033[0m'

    BOLD = '\033[1m'

    BOLDWHITE = '\033[1;37m'

    UNDERLINE = '\033[4m'







# STEP 1: print nvidia model

print(bcolors.BOLDWHITE+"NVIDIA devices:"+bcolors.ENDC)



p = subprocess.run("lspci | grep NVIDIA",shell=True,stdout=subprocess.PIPE)

out = p.stdout.strip().decode()

if len(out)==0:

  print(bcolors.FAIL+" not found (try 'lspci')"+bcolors.ENDC)

else:

  print(out)



# STEP 2: nvidia driver version

print(bcolors.BOLDWHITE+"NVIDIA driver version:"+bcolors.ENDC)

p = subprocess.run("cat /proc/driver/nvidia/version",shell=True,stdout=subprocess.PIPE)

out = p.stdout.strip().decode()

print(out)



# STEP 3: nvidia-smi - also some information about the graphics card and the driver

print(bcolors.BOLDWHITE+"Some more info from 'nvidia-smi':"+bcolors.ENDC)

p = subprocess.run("nvidia-smi",shell=True,stdout=subprocess.PIPE)

out = p.stdout.strip().decode()

print(out)





print(bcolors.OKGREEN+"END"+bcolors.ENDC)
 
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tile_packing_table.xml

+54 −0
Original line number Original line Diff line number Diff line
@@ -53,4 +53,58 @@ 
    <tr row='23'>[(66,1.0), (67,1.0), (68,1.0)]</tr>

    <tr row='23'>[(66,1.0), (67,1.0), (68,1.0)]</tr>

    <tr row='24'>[(74,1.0), (75,1.0), (76,1.0), (77,1.0), (78,1.0)]</tr>

    <tr row='24'>[(74,1.0), (75,1.0), (76,1.0), (77,1.0), (78,1.0)]</tr>

  </table>

  </table>

  <table layer='hor-pairs'>

    <tr row='0' >[(2,1.0),   (3,1.0),  (4,1.0),  (5,1.0), (6,1.0)]</tr>

    <tr row='1' >[(10,1.0), (11,1.0), (19,1.0), (20,1.0)]</tr>

    <tr row='2' >[(12,1.0), (13,1.0), (14,1.0)]</tr>

    <tr row='3' >[(15,1.0), (16,1.0), (24,1.0), (25, 1.0)]</tr>

    <tr row='4' >[(18,1.0), (27,1.0), (36,1.0), (45,1.0), (54,1.0)]</tr>

    <tr row='5' >[(21,1.0), (22,1.0), (23,1.0)]</tr>

    <tr row='6' >[(26,1.0), (35,1.0), (44,1.0), (53,1.0), (62,1.0)]</tr>

    <tr row='7' >[(28,1.0), (37,1.0), (46,1.0)]</tr>

    <tr row='8' >[(29,1.0), (38,1.0), (47,1.0)]</tr>

    <tr row='9' >[(30,1.0)]</tr>

    <tr row='10'>[(31,1.0)]</tr>

    <tr row='11'>[(32,1.0)]</tr>

    <tr row='12'>[(33,1.0), (42,1.0), (51,1.0)]</tr>

    <tr row='13'>[(34,1.0), (43,1.0), (52,1.0)]</tr>

    <tr row='14'>[(39,1.0)]</tr>

    <tr row='15'>[(40,1.0)]</tr>

    <tr row='16'>[(41,1.0)]</tr>

    <tr row='17'>[(48,1.0)]</tr>

    <tr row='18'>[(49,1.0)]</tr>

    <tr row='19'>[(50,1.0)]</tr>

    <tr row='20'>[(55,1.0), (56,1.0), (64,1.0), (65,1.0)]</tr>

    <tr row='21'>[(57,1.0), (58,1.0), (59,1.0)]</tr>

    <tr row='22'>[(60,1.0), (61,1.0), (69,1.0), (70,1.0)]</tr>

    <tr row='23'>[(66,1.0), (67,1.0), (68,1.0)]</tr>

    <tr row='24'>[(74,1.0), (75,1.0), (76,1.0), (77,1.0), (78,1.0)]</tr>

  </table>

  <table layer='vert-pairs'>

    <tr row='0' >[(2,1.0),   (3,1.0),  (4,1.0),  (5,1.0), (6,1.0)]</tr>

    <tr row='1' >[(10,1.0), (11,1.0), (19,1.0), (20,1.0)]</tr>

    <tr row='2' >[(12,1.0), (13,1.0), (14,1.0)]</tr>

    <tr row='3' >[(15,1.0), (16,1.0), (24,1.0), (25, 1.0)]</tr>

    <tr row='4' >[(18,1.0), (27,1.0), (36,1.0), (45,1.0), (54,1.0)]</tr>

    <tr row='5' >[(21,1.0), (22,1.0), (23,1.0)]</tr>

    <tr row='6' >[(26,1.0), (35,1.0), (44,1.0), (53,1.0), (62,1.0)]</tr>

    <tr row='7' >[(28,1.0), (37,1.0), (46,1.0)]</tr>

    <tr row='8' >[(29,1.0), (38,1.0), (47,1.0)]</tr>

    <tr row='9' >[(30,1.0)]</tr>

    <tr row='10'>[(31,1.0)]</tr>

    <tr row='11'>[(32,1.0)]</tr>

    <tr row='12'>[(33,1.0), (42,1.0), (51,1.0)]</tr>

    <tr row='13'>[(34,1.0), (43,1.0), (52,1.0)]</tr>

    <tr row='14'>[(39,1.0)]</tr>

    <tr row='15'>[(40,1.0)]</tr>

    <tr row='16'>[(41,1.0)]</tr>

    <tr row='17'>[(48,1.0)]</tr>

    <tr row='18'>[(49,1.0)]</tr>

    <tr row='19'>[(50,1.0)]</tr>

    <tr row='20'>[(55,1.0), (56,1.0), (64,1.0), (65,1.0)]</tr>

    <tr row='21'>[(57,1.0), (58,1.0), (59,1.0)]</tr>

    <tr row='22'>[(60,1.0), (61,1.0), (69,1.0), (70,1.0)]</tr>

    <tr row='23'>[(66,1.0), (67,1.0), (68,1.0)]</tr>

    <tr row='24'>[(74,1.0), (75,1.0), (76,1.0), (77,1.0), (78,1.0)]</tr>

  </table>

</Document>
 
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