📑 Circus of Programming Tricks 01. Super Resolution

tricks_01.html

xxxxxxxxxx

 

1

!python3 -m pip install --upgrade pip \

2

--user --quiet --no-warn-script-location

3

!python3 -m pip install tensorflow_hub \

4

--user --quiet --no-warn-script-location

5

#!python3 -m pip install tensorflow==2.6.0 \

6

#--user --quiet --no-warn-script-location

7

path='/home/sc_work/.sage/local/lib/python3.9/site-packages'

8

import sys,warnings; sys.path.append(path)

9

warnings.filterwarnings('ignore')

10

import numpy as np,tensorflow as tf,tensorflow_hub as hub

11

super_hub_path='https://tfhub.dev/captain-pool/esrgan-tf2/1'

12

os.environ['TFHUB_MODEL_LOAD_FORMAT']='COMPRESSED'

13

file_path='https://raw.githubusercontent.com/'+\

14

          'OlgaBelitskaya/data_kitchen/main/'

15

file_name='Pictograms64.h5'

16

img_size=int(64); lr_size=int(50)

17

super_model=hub.load(super_hub_path)

18

func=super_model.signatures[tf.saved_model\

19

.DEFAULT_SERVING_SIGNATURE_DEF_KEY]

20

func.inputs[0].set_shape([1,lr_size,lr_size,3])

21

converter=tf.lite.TFLiteConverter.from_concrete_functions([func])

22

converter.optimizations=[tf.lite.Optimize.DEFAULT]

23

tflite_super_model=converter.convert()

24

with tf.io.gfile.GFile('ESRGAN.tflite','wb') as f: 

25

    f.write(tflite_super_model)

26

esrgan_model_path='./ESRGAN.tflite'

Language: Sage Gap GP HTML Macaulay2 Maxima Octave Python R Singular

---

Messages

xxxxxxxxxx

 

1

input_file=urllib.request.urlopen(file_path+file_name)

2

output_file=open(file_name,'wb')

3

output_file.write(input_file.read())

4

output_file.close(); input_file.close()

5

with h5py.File(file_name,'r') as f:

6

    keys=list(f.keys())

7

    images=np.array(f[keys[int(0)]])

8

    labels=np.array(f[keys[int(1)]])

9

    names=[[el.decode('utf-8') for el in f[keys[i]]] 

10

           for i in range(int(2),len(keys))]

11

    f.close(); os.remove(file_name)

12

N=images.shape[0]; shuffle_ids=np.arange(N)

13

np.random.RandomState(12).shuffle(shuffle_ids)

14

images=images[shuffle_ids]

15

labels=np.array([labels[i][shuffle_ids] 

16

                 for i in range(labels.shape[int(0)])])

17

@interact(layout=dict(

18

    top=[['original_type','original_object']]))

19

def _pictograms(original_type=selector(names[0],default='pictogram'),

20

                original_object=selector(names[1],default='bird')):

21

    global names,images,labels,esrgan_model_path,lr_size

22

    original_names=[names[0].index(original_type),

23

                    names[1].index(original_object)]

24

    original_cond=np.intersect1d(

25

        np.where(labels[0]==original_names[0]),

26

        np.where(labels[1]==original_names[1]))

27

    original_images=images[original_cond]

28

    original_len=original_images.shape[0]

29

    original_img=original_images[randint(0,original_len-1)]

30

    lr=tf.image.resize(original_img,[lr_size,lr_size])

31

    lr=tf.expand_dims(lr.numpy()[:,:,:int(3)],axis=int(0))

32

    lr=tf.cast(lr*int(255),tf.float32)

33

    interpreter=tf.lite.Interpreter(model_path=esrgan_model_path)

34

    interpreter.allocate_tensors()

35

    input_details=interpreter.get_input_details()

36

    output_details=interpreter.get_output_details()

37

    interpreter.set_tensor(input_details[int(0)]['index'],lr)

38

    interpreter.invoke()

39

    output_data=interpreter.get_tensor(output_details[0]['index'])

40

    sr=tf.squeeze(output_data,axis=int(0))

41

    sr=tf.clip_by_value(sr,int(0),int(255))

42

    sr=tf.cast(tf.round(sr),tf.uint8)

43

    lr=tf.cast(tf.squeeze(lr,axis=int(0)),tf.uint8)

44

    print('original 64x64 '+' lower resolution 50x50 '+\

45

          ' higher resolution 200x200\n')

46

    for img in [original_img,lr/int(255),sr/int(255)]: 

47

        matrix_plot(img,frame=True,figsize=3.8).show()

Language: Sage Gap GP HTML Macaulay2 Maxima Octave Python R Singular

---

Messages