📑 Exercises with White Flowers` Images

🌐   DL_PP7_1_SMC.html

📑 Deep Learning. Practice Project 7_1:
Exercises with White Flowers` Images

✒️ Code Modules, Helpful Functions, & Settings

xxxxxxxxxx

 

1

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

2

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

3

!python3 -m pip install tensorflow_hub \

4

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

5

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

6

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

7

warnings.filterwarnings('ignore')

8

from IPython.display import display,HTML

9

from IPython.core.magic import register_line_magic

10

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

11

import os,h5py,urllib,cv2,pandas as pd,pylab as pl

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

---

Messages

xxxxxxxxxx

 

1

def get_data(file_path,file_name,img_size):

2

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

3

    output_file=open(file_name,'wb')

4

    output_file.write(input_file.read())

5

    output_file.close(); input_file.close()

6

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

7

        keys=list(f.keys())

8

        pretty_print(html('<p>file keys: '+', '.join(keys)+'</p>'))

9

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

10

        images=tf.image.resize(images,[img_size,img_size]).numpy()

11

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

12

        names=[el.decode('utf-8') for el in f[keys[2]]]

13

        f.close()

14

    pretty_print(html('<p>%s'%names+'</p>'))

15

    return images,labels,names

16

def display_imgs(images,labels,names,start):

17

    fig=pl.figure(figsize=(6,3)); n=randint(0,start-1)

18

    for i in range(n,n+6):

19

        ax=fig.add_subplot(2,3,i-n+1,xticks=[],yticks=[])

20

        ax.set_title(

21

            names[labels[i]],color='slategray',

22

            fontdict={'fontsize':'large'})

23

        ax.imshow((images[i]))

24

    pl.tight_layout(); pl.show()

25

def get_file(file_path,file_name):

26

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

27

    output_file=open(file_name,'wb')

28

    output_file.write(input_file.read())

29

    output_file.close(); input_file.close()

30

def highpass_xy(img):

31

    x_var=img[:,:,int(1):,:]-img[:,:,:-int(1),:]

32

    y_var=img[:,int(1):,:,:]-img[:,:-int(1),:,:]

33

    return x_var,y_var

34

def clip01(img):

35

    return tf.clip_by_value(

36

        img,clip_value_min=float(0.),clip_value_max=float(1.))

37

def load_img(file_name,max_dim=int(512)):

38

    img=tf.io.read_file(file_name)

39

    img=tf.image.decode_image(img,channels=int(3))

40

    img=tf.image.convert_image_dtype(img,tf.float32)

41

    shape=tf.cast(tf.shape(img)[:-int(1)],tf.float32)

42

    scale=max_dim/max(shape)

43

    new_shape=tf.cast(shape*scale,tf.int32)

44

    img=tf.image.resize(img,new_shape)

45

    return img[tf.newaxis,:]

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

---

Messages

✒️ Data Loading

xxxxxxxxxx

 

1

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

2

          'OlgaBelitskaya/data_kitchen/main/'

3

file_name='WhiteFlowers128.h5'; img_size=int(64)

4

images,labels,names=get_data(file_path,file_name,img_size)

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

---

Messages

✒️ Data Processing

xxxxxxxxxx

 

1

N=labels.shape[0]; n=int(.1*N)

2

num_classes=len(names); start=int(100) 

3

shuffle_ids=np.arange(N)

4

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

5

images=images[shuffle_ids]; labels=labels[shuffle_ids]

6

x_test,x_valid,x_train=images[:n],images[n:2*n],images[2*n:]

7

y_test,y_valid,y_train=labels[:n],labels[n:2*n],labels[2*n:]

8

df=pd.DataFrame(

9

    [[x_train.shape,x_valid.shape,x_test.shape],

10

     [x_train.dtype,x_valid.dtype,x_test.dtype],

11

     [y_train.shape,y_valid.shape,y_test.shape],

12

     [y_train.dtype,y_valid.dtype,y_test.dtype]],

13

    columns=['train','valid','test'],

14

    index=['image shape','image type','label shape','label type'])

15

display_imgs(images,labels,names,start); display(df)

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

---

Messages

✒️ Super Resolution

xxxxxxxxxx

 

1

def esrgantf2_superresolution(img,img_size=int(50)):

2

    model=hub.load('https://tfhub.dev/captain-pool/esrgan-tf2/1')

3

    func=model.signatures[tf.saved_model\

4

    .DEFAULT_SERVING_SIGNATURE_DEF_KEY]

5

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

6

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

7

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

8

    tflite_model=converter.convert()

9

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

10

        f.write(tflite_model)

11

    esrgan_model_path='./ESRGAN.tflite'

12

    if img.mean()<float(1): img=img*float(255)

13

    lr=tf.image.resize(img,[img_size,img_size])

14

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

15

    lr=tf.cast(lr,tf.float32)

16

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

17

    interpreter.allocate_tensors()

18

    input_details=interpreter.get_input_details()

19

    output_details=interpreter.get_output_details()

20

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

21

    interpreter.invoke()

22

    output_data=interpreter.get_tensor(

23

        output_details[int(0)]['index'])

24

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

25

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

26

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

27

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

28

    return lr,sr

29

lr,sr=esrgantf2_superresolution(images[start],img_size)

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

---

Messages

xxxxxxxxxx

 

1

def low2superbicubic_imgs(lr,sr):

2

    pl.figure(figsize=(6,3)); pl.title(f'lr')

3

    pl.imshow(lr.numpy()); pl.show()

4

    pl.figure(figsize=(6,3))

5

    pl.subplot(1,2,1); pl.title(f'esrgan x4')

6

    pl.imshow(sr.numpy())

7

    img_size=lr.shape[int(1)]

8

    bicubic=tf.image.resize(

9

        lr,[img_size*int(4),img_size*int(4)],

10

        tf.image.ResizeMethod.BICUBIC)

11

    bicubic_contrast=tf.image.adjust_contrast(bicubic,float(.8))

12

    bicubic_contrast=tf.cast(bicubic_contrast,tf.uint8)

13

    pl.subplot(1,2,2); pl.title(f'bicubic & contrast')

14

    pl.imshow(bicubic_contrast.numpy())

15

    pl.tight_layout(); pl.show()

16

low2superbicubic_imgs(lr,sr)

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

---

Messages

✒️ OpenCV Image Manipulations

xxxxxxxxxx

 

1

file_path2='https://raw.githubusercontent.com/'+\

2

           'OlgaBelitskaya/data/main/white_flowers/'

3

file_name2='01_036.png'

4

get_file(file_path2,file_name2)

5

img=cv2.imread(file_name2)

6

img=cv2.resize(img,(int(256),int(192)))

7

gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

8

rgb=cv2.cvtColor(img,cv2.COLOR_BGR2RGB)

9

hsv=cv2.cvtColor(img,cv2.COLOR_BGR2HSV)

10

edge_img=rgb.copy()

11

edge=cv2.Canny(gray,int(80),int(210))

12

edge_img[edge!=0]=(255,0,255) 

13

lower=np.array([10,200,150]); upper=np.array([30,255,255])

14

mask=cv2.inRange(hsv,lower,upper)

15

result=cv2.bitwise_and(img,img,mask=mask)

16

kernel=np.ones((11,11),np.uint8)

17

gradient=cv2.morphologyEx(img,cv2.MORPH_GRADIENT,kernel)

18

sobel=cv2.Sobel(

19

    gray,cv2.CV_64F,int(1),int(0),ksize=int(27))

20

laplacian=cv2.Laplacian(img,cv2.CV_64F)

21

pl.figure(figsize=(6,10)); pl.subplot(521)

22

pl.imshow(cv2.bitwise_not(rgb))

23

pl.title('bitwise_not'),pl.subplot(522)

24

pl.imshow(cv2.cvtColor(hsv,cv2.COLOR_HSV2RGB))

25

pl.title('hsv2rgb'),pl.subplot(523)

26

pl.imshow(gray,cmap='bone')

27

pl.title('gray2bone'),pl.subplot(524)

28

pl.imshow(edge_img)

29

pl.title('edges2magenta'),pl.subplot(525)

30

pl.imshow(edge,cmap='flag_r')

31

pl.title('edges2flag_r'),pl.subplot(526)

32

pl.imshow(gradient)

33

pl.title('morphology_gradient'),pl.subplot(527)

34

pl.imshow(cv2.cvtColor(result,cv2.COLOR_BGR2RGB))

35

pl.title('hsv_mask'),pl.subplot(528)

36

pl.imshow(sobel,cmap='bone')

37

pl.title('sobel'),pl.subplot(529)

38

pl.imshow(laplacian,cmap='bone')

39

pl.title('laplacian'),pl.tight_layout(); pl.show()

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

---

Messages

xxxxxxxxxx

 

1

values=[0,1,..,255]

2

@interact

3

def _(red=slider(values,default=15),

4

      green=slider(values,default=127),

5

      blue=slider(values,default=15),

6

      step=[15,14,..,1]):

7

    [r,g,b]=[red,green,blue]

8

    min_rgb=[max(0,x-4*step) for x in [r,g,b]]

9

    max_rgb=[min(255,x+4*step) for x in [r,g,b]]

10

    pretty_print('min rgb: %s; \n'%str(min_rgb)+\

11

                 'rgb: %s; \n'%str([r,g,b])+\

12

                 'max rgb: %s; '%str(max_rgb))

13

    m=[[[r+i*step,g,b] for i in range(-4,5,1)],

14

       [[r,g+i*step,b] for i in range(-4,5,1)],

15

       [[r,g,b+i*step] for i in range(-4,5,1)],

16

       [[r+i*step,g+i*step,b] for i in range(-4,5,1)],

17

       [[r,g+i*step,b+i*step] for i in range(-4,5,1)],

18

       [[r+i*step,g,b+i*step] for i in range(-4,5,1)],

19

       [[r+i*step,g+i*step,b+i*step] for i in range(-4,5,1)]]

20

    tf=[[-4,-3,-2,-1,0,1,2,3,4],['r','g','b','rg','gb','rb','rgb']]

21

    p=matrix_plot(np.array(m)/255,

22

                  ticks=[[0..8],[0..6]],tick_formatter=tf)

23

    p.show()

24

    hsv=cv2.cvtColor(np.uint8([[[r,g,b]]]),cv2.COLOR_BGR2HSV)

25

    min_hsv=cv2.cvtColor(np.uint8([[min_rgb]]),cv2.COLOR_BGR2HSV)

26

    max_hsv=cv2.cvtColor(np.uint8([[max_rgb]]),cv2.COLOR_BGR2HSV)

27

    pretty_print('min rgb -> hsv: %s; \n'%str(min_hsv[0][0])+\

28

                 'rgb -> hsv: %s; \n'%str(hsv[0][0])+\

29

                 'max rgb -> hsv: %s; '%str(max_hsv[0][0]))

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

---

Messages

xxxxxxxxxx

 

1

@interact(layout=dict(

2

    top=[['file'],['lower_red','lower_green','lower_blue'],

3

         ['upper_red','upper_green','upper_blue']]))

4

def _rgb2hsv(file=[1,2,3,6,7],

5

             lower_red=slider(values,default=0),

6

             lower_green=slider(values,default=0),

7

             lower_blue=slider(values,default=0),

8

             upper_red=slider(values,default=50),

9

             upper_green=slider(values,default=127),

10

             upper_blue=slider(values,default=50)):

11

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

12

              'OlgaBelitskaya/data/main/white_flowers/'

13

    file_name='01_00%s'%(file)+'.png'

14

    get_file(file_path,file_name)

15

    img=cv2.imread(file_name)

16

    rgb=cv2.cvtColor(img,cv2.COLOR_BGR2RGB)

17

    hsv=cv2.cvtColor(img,cv2.COLOR_BGR2HSV)

18

    [lr,lg,lb]=[lower_red,lower_green,lower_blue]

19

    [ur,ug,ub]=[upper_red,upper_green,upper_blue]

20

    lower_hsv=cv2.cvtColor(

21

        np.uint8([[[lr,lg,lb]]]),cv2.COLOR_BGR2HSV)[0][0]

22

    upper_hsv=cv2.cvtColor(

23

        np.uint8([[[ur,ug,ub]]]),cv2.COLOR_BGR2HSV)[0][0]

24

    mask=cv2.inRange(hsv,np.array(lower_hsv),np.array(upper_hsv))   

25

    result=cv2.bitwise_and(img,img,mask=mask)

26

    result_rgb=cv2.cvtColor(result,cv2.COLOR_BGR2RGB)

27

    pretty_print('lower rgb -> hsv: %s; '%str(lower_hsv)+\

28

                 'upper rgb -> hsv: %s; '%str(upper_hsv))

29

    for el in [rgb,mask,result_rgb]:

30

         matrix_plot(el/255).show(frame=False,figsize=(3.5,3.5))

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

---

Messages

✒️ TensorFlow Image Manipulations

xxxxxxxxxx

 

1

@interact(layout=dict(top=[['file'],['contrast','brightness']]))

2

def _tfimg(file=slider([1..60],default=30),

3

           contrast=slider([.05,.1,..,1.95],default=1.5),

4

           brightness=slider([.05,.1,..,1.05],default=.5)):

5

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

6

              'OlgaBelitskaya/data/main/white_flowers/'

7

    file_name='02_%03d'%(file)+'.png'

8

    get_file(file_path,file_name)

9

    original_img=load_img(file_name)

10

    gray_img=np.dot(original_img[...,:int(3)],[.299,.587,.114])

11

    contrast_img=tf.image.adjust_contrast(

12

        original_img,float(contrast))

13

    brightness_img=tf.image.adjust_brightness(

14

        original_img,float(brightness))

15

    x_deltas,y_deltas=highpass_xy(original_img)

16

    sobel=tf.image.sobel_edges(original_img)

17

    pl.figure(figsize=(6,10))

18

    pl.subplot(4,2,1),pl.imshow(tf.squeeze(clip01(original_img)))

19

    pl.title('rgb || original')

20

    pl.subplot(4,2,2)

21

    pl.imshow(tf.squeeze(clip01(gray_img)),cmap='bone')

22

    pl.title('gray || original')

23

    pl.subplot(4,2,3),pl.imshow(tf.squeeze(clip01(brightness_img)))

24

    pl.title('brightness || original')

25

    pl.subplot(4,2,4),pl.imshow(tf.squeeze(clip01(contrast_img)))

26

    pl.title('contrast || original')

27

    pl.subplot(4,2,5)

28

    pl.imshow(tf.squeeze(clip01(int(2)*y_deltas+float(.5))))

29

    pl.title('horizontal deltas || original')

30

    pl.subplot(4,2,6)

31

    pl.imshow(tf.squeeze(clip01(int(2)*x_deltas+float(.5))))

32

    pl.title('vertical deltas || original')

33

    pl.subplot(4,2,7)

34

    pl.imshow(tf.squeeze(clip01(sobel[...,int(0)]/int(4)+float(.5))))

35

    pl.title('horizontal sobel-edges')

36

    pl.subplot(4,2,8)

37

    pl.imshow(tf.squeeze(clip01(sobel[...,int(1)]/int(4)+float(.5))))

38

    pl.title('vertical sobel-edges');

39

    pl.tight_layout(); pl.show()

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

---

Messages