KaneAI - World’s First E2E Software Testing Agent.Book a Demo Join TestMu Conference

How to use image_import method in tempest

Best Python code snippet using tempest_python

Entregable_Final.py

Source:Entregable_Final.py

1from tkinter.font import BOLD2import cv23from matplotlib import pyplot as plt4from static_functions import *5from tkinter import *6from tkinter import filedialog7from PIL import Image8from PIL import ImageTk9from time import time10import os11import imutils12from kalmanfilter import KalmanFilter13eye_detector = EyeDetector()14kf = KalmanFilter()15global saved16saved = []17################# GUI#########################18def visualizar():19    global cap,ojo1_x,ojo1_y,ojo2_x,ojo2_y,path,save,img___,path_img, saved_img,change20    global scaled_eye_x,scaled_eye_y21    global previous_time,current_time,count,init_time22    ret,frame = cap.read()23    if ret == True:24        eyes = eye_detector.eye_coords(frame)25        if eyes is not None:26            ( (ojo1_x, ojo1_y), (ojo2_x, ojo2_y) ), ( scaled_eye_x, scaled_eye_y) = eyes27            scaled_eye_x = 1-scaled_eye_x28            29            frame = cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)30            #### resize frame 31            frame = cv2.resize(frame,(75,50))32            ###########33            34            im = Image.fromarray(frame)35            img = ImageTk.PhotoImage(image=im)36            lblvideo.configure(image=img)37            lblvideo.image=img38        39            ##### modificaciÃ³n de parametros de imagen importada    40            #### leer la imagen41            42            current_time=time()43            if count==0:44                saved_img = None45            if count!=0:46                change=write_to_file(scaled_eye_x,scaled_eye_y,count,change,current_time,init_time)47            48            49            if (current_time-previous_time>7) and (count<6):50                51                path_img = path +img___[count]52                count +=153                change=True54                saved_img = None55                previous_time = time()56                elegir_img()57            if (count==6) and ((current_time-previous_time>7)):58                print('finalizar')59                finalizar()60            else:61                if saved_img is None:62                    image_imported =cv2.imread(path_img)63                    64                    image_imported = cv2.resize(image_imported,(screen_width,screen_height))65                    image_imported = imutils.resize(image_imported,height=screen_height) #"""height=400"""66                    #### visualizar la imagen de entrada en la GUI67                    image_imported = imutils.resize(image_imported,width=screen_width)68                    image_imported = cv2.cvtColor(image_imported,cv2.COLOR_BGR2RGB)69                    saved_img = image_imported.copy()70                else:71                    image_imported = saved_img.copy()72                predicted = kf.predict(screen_width*scaled_eye_x,screen_height*scaled_eye_y)73                image_import = cv2.circle(image_imported,(int(predicted[0]),int(predicted[1])),5,(0,0,255),4)74                saved = []75                76                im = Image.fromarray(image_import)77                img = ImageTk.PhotoImage(image=im)78                lblInputImage.configure(image=img)79                lblInputImage.image = img80                cv2.waitKey(0)81                lblInputImage.configure(image=img)82                lblInputImage.image = img83                ojo1_value_x.configure(text='{:.2f}'.format(ojo1_x),font=BOLD)84                ojo1_value_y.configure(text="{:.2f}".format(ojo1_y),font=BOLD)85                ojo2_value_x.configure(text='{:.2f}'.format(ojo2_x),font=BOLD)86                ojo2_value_y.configure(text='{:.2f}'.format(ojo2_y),font=BOLD)87            lblvideo.after(1,visualizar)88    else:89        lblvideo.image = ''90        lblInfoVideoPath.configure(text='')91        rad1.configure(state='active')92        rad2.configure(state='active')93        selected.set(0) ### esto es para que no este seleccionado ningujo 94            #### de las redondas95        boton_end.configure(state='active')96        cap.release()97def elegir_img():98    global path_img,path,img___99    global ojo1_x,ojo1_y100  101    if len(path_img) >0:102        103        #### leer la imagen104        105        image_imported =cv2.imread(path_img)106        image_imported = cv2.resize(image_imported,(screen_width,screen_height))107        image_imported = imutils.resize(image_imported,height=screen_height) #"""height=400"""108        #### visualizar la imagen de entrada en la GUI109        image_imported = imutils.resize(image_imported,width=screen_width)#width=800)110       111        image_imported = cv2.cvtColor(image_imported,cv2.COLOR_BGR2RGB)112        image_import = cv2.circle(image_imported,((int(screen_width/2)),(int(screen_height/2)-50)),7,(0,0,255),4)113        im = Image.fromarray(image_import)114        img = ImageTk.PhotoImage(image=im)115        lblInputImage.configure(image=img)116        lblInputImage.image = img117    return118def video_de_entrada(): #Aqui esta el array de fotos119    global cap,threshold,image_imported,path,img___,path_img120    global ojo1_value_x,ojo1_value_y,ojo2_value_x,ojo2_value_y121    global previous_time,current_time,count,init_time122    path = os.path.join(os.getcwd(),"img_prototype")123    img___ = [124        "/001.jpg",125        "/002.jpg",126        "/003.jpg",127        "/004.jpg",128        "/005.jpg",129        "/006.jpg"130    ]131    #image_imported =cv2.imread()132    if selected.get() == 1: 133        boton_end.configure(state='active')134        path_img=path+img___[0]135        elegir_img()136        previous_time = time() ### tiempo inicial 137        count = 0 ## contando el nÃºmero de imagenes138        139    if selected.get() == 2: 140        rad1.configure(state='disabled')141        rad2.configure(state='disabled')142        boton_end.configure(state='active')143        lblInfoVideoPath.configure(text='')144        cap = cv2.VideoCapture(0)145        init_time = time()146        visualizar()147def finalizar():148    global init_time,current_time149    print('finalizar')150    lblInfoVideoPath.configure(text='')151    lblvideo.image=''152    lblInfoVideoPath.configure(text='')153    154    rad1.configure(state='active')155    rad2.configure(state='active')156    boton_end.configure(state='disabled')157    lblInputImage.image = ''158    selected.set(0)159    cap.release()160    ojo1_value_x.configure(text='0')161    ojo1_value_y.configure(text='0')162    ojo2_value_x.configure(text='0')163    ojo2_value_y.configure(text='0')164    write_to_file(screen_width,screen_height,50,current=current_time,previous=init_time,change=True,)165    #guardar_images()166def guardar_images():167    f = open("logs.txt",'r')168    variable= True169    all_data ={}170    for i in range(7):171        imagen=[]172        while variable:173            line = f.readline()174            if line=="\n":175                break176            177            if line[0]!='I' and line[0]!='T':      178                dato=line.split(sep='\n')[0].split(sep=',')179                imagen.append([float(dato[0]),float(dato[1])])180            # print('dato')181            if i==6 and (line[0]!='I' and line[0]!='T'):182                dato=line.split(sep='\n')[0].split(sep=',')183                imagen.append([float(dato[0]),float(dato[1])])184                variable=False185        variable=True186        all_data[i]=imagen187    ### filtro de informaciÃ³n188    print(all_data)189    screen_width=all_data[6][0][0]190    screen_height=all_data[6][0][1]191    path = os.path.join(os.getcwd(),"img_prototype")192    img___ = [193        "/001.jpg",194        "/002.jpg",195        "/003.jpg",196        "/004.jpg",197        "/005.jpg",198        "/006.jpg"199    ]200    for i in range(len(img___)):201        #### leer la imagen202        print(path+img___[i])203        image_imported =cv2.imread(path+img___[i])204        print(image_imported)205        image_imported = cv2.resize(image_imported,(int(screen_width),int(screen_height)))206        image_imported = imutils.resize(image_imported,height=int(screen_height)) #"""height=400"""207        #### visualizar la imagen de entrada en la GUI208        image_imported = imutils.resize(image_imported,width=int(screen_width))#width=800)209        210        #image_imported = cv2.cvtColor(image_imported,cv2.COLOR_BGR2RGB)211        212        #image_import = cv2.circle(image_imported,((int(screen_width/2)),(int(screen_height/2)-50)),7,(0,0,255),cv2.FILLED) #4213        image_import = None214        for j in range(len(all_data[i])):215            x = all_data[i][j][0]216            y = all_data[i][j][1]217            218            if j==0:219                image_import = cv2.circle(image_imported,((int(screen_width*x)),(int(screen_height*y))),7,(0,255,0),4)220            else:221                image_import = cv2.circle(image_import,((int(screen_width*x)),(int(screen_height*y))),7,(0,255,0),4)222        cv2.imwrite(f'{i} '+'view.jpg',image_import)223def gui():224    global cap,selected,IblInfo1,lblInfoVideoPath,rad1,rad2,boton_end,boton_upload_file,boton_upload_file225    global lblInputImage,lblvideo,entrada_1,threshold226    global cap,ojo1_x,ojo1_y,ojo2_x,ojo2_y227    global screen_width,screen_height ### obtenciÃ³n de tamaÃ±o de pantalla228    global ojo1_value_x,ojo1_value_y,ojo2_value_x,ojo2_value_y,change,init_time229    ojo1_x=0230    ojo1_y=0231    ojo2_x=0232    ojo2_y=0233    234    change=True ### el valor de cambio inicial para imagenes235    cap = None236    root = Tk()237    IblInfo1 = Label(root,text='Entrada de Video',font='Bold')238    IblInfo1.grid(column=0,row=0,columnspan=1)239    240    selected = IntVar()241    rad1 = Radiobutton( ### para adjuntar imagen242        root,243        text='Inicializar visualizaciÃ³n',244        width=20,245        variable=selected,246        value=1,247        command=video_de_entrada248    )249    rad2 = Radiobutton( ## para poder visualizar la imagen de video250        root, 251        text='Ver Video en Vivo',252        width=20,253        variable=selected,254        value=2,255        command=video_de_entrada256    )257    rad1.grid(column=0,row=1,padx=0)258    rad2.grid(column=0,row=2,padx=0)259    ########## mostrar el pad del videos260    lblInfoVideoPath = Label(root,text='',width=20)261    lblInfoVideoPath.grid(column=2,row=1)262    lblvideo = Label(root)263    lblvideo.grid(column=2,row=0,columnspan=2,rowspan=3)264    ################### segmentar donde se mostrarÃ¡ la imagen################265    lblInputImage=Label(root)266    lblInputImage.grid(column=0, row=3,pady=0,columnspan=5)267    ############ mostrar el botÃ³n para finalizar visualizaciÃ³n###########268    boton_end = Button(269        root,270        text='Finalizar VisualizaciÃ³n y limpiar',271        state='active',272        command=finalizar273        )274    boton_end.grid(column=1,row=0)275    ########## labels para ojo 1 y ojo 2 276    ojo_1_label = Label(root,text='Ojo 1')277    ojo_1_label.grid(column=2,row=0)278    ojo_2_label=Label(root,text='Ojo 2')279    ojo_2_label.grid(column=2,row=1)280    ####### visualizar posicion de ojos x e y   281    ojo1_value_x = Label(root,text=f'{ojo1_x}')282    ojo1_value_y = Label(root,text=f'{ojo1_y}')283    ojo2_value_x = Label(root,text=f'{ojo2_x}')284    ojo2_value_y = Label(root,text=f'{ojo2_y}')285    286    ojo1_value_x.grid(column=3,row=0)287    ojo1_value_y.grid(column=4,row=0)288    ojo2_value_x.grid(column=3,row=1)289    ojo2_value_y.grid(column=4,row=1)290    #### tamaÃ±o de la pantalla obtenciÃ³n de datos291    screen_width = root.winfo_screenwidth()292    screen_height = root.winfo_screenheight() -150293    ################ Visualizando los valores en ojo izquierdo y ojo derecho ##############294    root.mainloop()...

Option_4_Num_3_4.py

Source:Option_4_Num_3_4.py

12import matplotlib.pyplot as plt3import matplotlib.image as mpimg4from keras.models import load_model5from keras.preprocessing.image import load_img6from keras.preprocessing.image import img_to_array78#################################################[RESOURCES]#################################################9# CIFAR-10 tutorial and database                                                                            #10# https://machinelearningmastery.com/how-to-develop-a-cnn-from-scratch-for-cifar-10-photo-classification/   #11# https://www.cs.toronto.edu/~kriz/cifar.html                                                               #12#############################################################################################################1314# load and prepare the image15def load_image(filename):16    img = load_img(filename, target_size=(32, 32))                 # Load the target image17    img = img_to_array(img)                                        # Convert the image to an array18    img = img.reshape(1, 32, 32, 3)                                # Reshape into a 3-channel sample19    img = img.astype('float32')                                    # Prepare pixel data20    img = img / 255.021    22    return img2324# This function allows multiple images to be processed 25def multiprocessing():26    while(True):  27        run_example()28        plt.show(block=True)29        30        exit_statement=input("Enter 'q' if you would like to quit or press any key to continue.")31        32        if (exit_statement.lower()=='q'):33            break34        else:35            print("Program will continue")36            37    return None3839# This function calculates the percent match of each image for each category40def getPercentage(prediction_class,index):41    42    i = index43    percentage = round(prediction_class[0][i]*100,3)44                       45    return percentage4647# This function loads the chosen image and makes a prediction of what the image is48def run_example():49    print("Please make a selection on the menu below\n")       # Displays the menu and takes user input50    choose = input('''\t\tMenu:                                51              -----------------------------------52              1: Airplane_1_database_processed53              2: Airplane_2_database_processed54              3: Automobile_1_database_processed55              4: Automobile_2_database_processed56              5: Bird_1_database_processed57              6: Bird_2_database_processed58              7: Cat_1_database_processed59              8: Cat_2_database_processed60              9: Deer_1_database_processed61             10: Deer_2_database_processed62             11: Dog_1_database_processed63             12: Dog_2_database_processed64             13: Frog_1_database_processed65             14: Frog_2_database_processed66             15: Horse_1_database_processed67             16: Horse_2_database_processed68             17: Ship-1_database_processed69             18: Ship_2_database_processed70             19: Truck_1_database_processed71             20: Truck_2_database_processed72            -------------------------------------73            Enter here:''')            7475    try:                                                           # try block to check valid user input76        options=int(choose)        77        if (options == 1):78            image_import ='Airplane_1_database_processed'79        if (options == 2):80            image_import ='Airplane_2_database_processed'    81        if (options == 3):82            image_import ='Automobile_1_database_processed'83        if (options == 4):84            image_import ='Automobile_2_database_processed'           85        if (options == 5):86            image_import ='Bird_1_database_processed'87        if (options == 6):88            image_import ='Bird_2_database_processed'    89        if (options == 7):90            image_import ='Cat_1_database_processed'91        if (options == 8):92            image_import ='Cat_2_database_processed'93        if (options == 9):94            image_import ='Deer_1_database_processed'95        if (options == 10):96            image_import ='Deer_2_database_processed'    97        if (options == 11):98            image_import ='Dog_1_database_processed'99        if (options == 12):100            image_import ='Dog_2_database_processed'           101        if (options == 13):102            image_import ='Frog_1_database_processed'103        if (options == 14):104            image_import ='Frog_2_database_processed'    105        if (options == 15):106            image_import ='Horse_1_database_processed'107        if (options == 16):108            image_import ='Horse_2_database_processed'109        if (options == 17):110            image_import ='Ship_1_database_processed'111        if (options == 18):112            image_import ='Ship_2_database_processed'    113        if (options == 19):114            image_import ='Truck_1_database_processed'115        if (options == 20):116            image_import='Truck_2_database_processed'         117        118        image = load_image(''+image_import+'.png')                  # Call the load_image function 119        model = load_model('final_model.h5')                        # Load the model using keras120        result = model.predict_classes(image)                       # Predict the class the image falls into121        plt.imshow(mpimg.imread(''+image_import+'.png'))122        prediction_class = model.predict_proba(image)               # Calculate the class probability for the object123        124# Call the getPercentage function for each category125######################################################################################################################126        airplane_stats = getPercentage(prediction_class,0)       127        automobile_stats = getPercentage(prediction_class,1)128        bird_stats = getPercentage(prediction_class,2)129        cat_stats = getPercentage(prediction_class,3)130        deer_stats = getPercentage(prediction_class,4)131        dog_stats = getPercentage(prediction_class,5)132        frog_stats = getPercentage(prediction_class,6)133        horse_stats = getPercentage(prediction_class,7)134        ship_stats = getPercentage(prediction_class,8)135        truck_stats = getPercentage(prediction_class,9)136######################################################################################################################137        138# Display the results in the console window139######################################################################################################################140        print("\nImage:",image_import,"\nMaking Prediction....\n")141        print("Image Prediction:")142        print(f"Airplane: {airplane_stats}%")143        print(f"Automobile: {automobile_stats}%")144        print(f"Bird: {bird_stats}%")145        print(f"Cat: {cat_stats}%")146        print(f"Deer: {deer_stats}%")147        print(f"Dog: {dog_stats}%")148        print(f"Frog: {frog_stats}%")149        print(f"Horse: {horse_stats}%")150        print(f"Ship: {ship_stats }%")151        print(f"Truck: {truck_stats}%")152######################################################################################################################153        154        print("\nClasses: ['airplane','automobile','bird','cat','deer','dog','frog','horse','ship','truck']")155        print("Class:",result[0],'\n')156    157        placeMarker = int(result[0])158        159        if (placeMarker == 0):160            print("This is an airplane")        161        if (placeMarker == 1):162            print("This is an automobile")       163        if (placeMarker == 2):164            print("This is a bird")       165        if (placeMarker == 3):166            print("This is a cat.")        167        if (placeMarker == 4):168            print("This is a deer.")        169        if (placeMarker == 5):170            print("This is a dog.")       171        if (placeMarker == 6):172            print("This is a frog.")        173        if (placeMarker == 7):174            print("This is a horse.")        175        if (placeMarker == 8):176            print("This is a ship.")        177        if (placeMarker == 9):178            print("This is a truck.")179180    except ValueError:  181        print("Error: a non-integer value was entered.\n"182              "Please only enter a valid integer between 1 and 20")183    except UnboundLocalError:184        print("Error: This integer is out of the given range.\n"185              "Please only enter a valid integer between 1 and 20")186        187    return None188def main():189     190    user_choice = input("Would you like to enable multi-image processing? Type: 'y', or type 'n' for single image processing:")191192    if(user_choice.lower()=='y'):193        multiprocessing()    194    elif(user_choice.lower()=='n'):195        run_example()196    else:197        print("Please make a valid selection")198        main()199        200if __name__ == '__main__':
...

test.py

Source:test.py

1# -*- coding: utf-8 -*-2import vtk3import numpy as np4import libtiff as lt5class MyStyle(vtk.vtkInteractorStyleImage):6    def __init__(self, parent=None):7        print "ddd"8        self.AddObserver("LeftButtonPressEvent", self.leftButtonDown)9        self.AddObserver("MouseWheelForwardEvent", self.forward_fun)10        self.AddObserver("MouseWheelBackwardEvent", self.backward_fun)11        12        13    def forward_fun(self, *arg):14        s = imageViewer.GetSlice()15        n = s + 116        if n > 511:17            n = 018        imageViewer.SetSlice(n)19    20    def backward_fun(self, *arg):21        s = imageViewer.GetSlice()22        n = s - 123        if n < 0:24            n = 51125        imageViewer.SetSlice(n)26    27    def leftButtonDown(self, *arg):28        inter1 = self.GetInteractor()29        click_pos = inter1.GetEventPosition()30        s = imageViewer.GetSlice()31#        print imageViewer.GetSize()32#        print imageViewer.GetImageActor().GetBounds()33#        image_data.SetScalarComponentFromFloat(click_pos[0], click_pos[1], s, 0, 255.0)34#        image_data.SetScalarComponentFromFloat(click_pos[0] + 1, click_pos[1], s, 0, 255.0)35#        image_data.SetScalarComponentFromFloat(click_pos[0], click_pos[1] + 1, s, 0, 255.0)36#        image_data.SetScalarComponentFromFloat(click_pos[0] - 1, click_pos[1], s, 0, 255.0)37#        image_data.SetScalarComponentFromFloat(click_pos[0], click_pos[1] - 1, s, 0, 255.0)38#        image_import.Modified()39#        image_import.Update()40#        imageViewer.SetInput(image_import.GetOutput())41#        imageViewer.Render()42        picker = vtk.vtkCellPicker()43        picker.Pick(click_pos[0], click_pos[1], s, imageViewer.GetRenderer())44        pos = picker.GetPickPosition()45        print pos46        sphereSource = vtk.vtkSphereSource()47        sphereSource.SetCenter(pos[0], pos[1], pos[2])48        sphereSource.SetRadius(1)49        sphereMapper = vtk.vtkPolyDataMapper()50        sphereMapper.SetInputConnection(sphereSource.GetOutputPort())51        sphereActor = vtk.vtkActor()52        sphereActor.SetMapper(sphereMapper)53        sphereActor.GetProperty().SetColor(255.0, 0.0, 0.0)54        imageViewer.GetRenderer().AddActor(sphereActor)55        imageViewer.Render()56def fun1():57    print "ddddd"58global i, imageViewer59i = 10060Tiff = lt.TIFF3D.open('G:\\sulei\\workplace\\Swc\\res\\22_24_12.tif', 'r')61images = Tiff.read_image()62image_import  = vtk.vtkImageImport()63images = np.require(images, dtype=np.uint8)64images_string = images.tostring()65image_import.CopyImportVoidPointer(images_string, len(images_string))66image_import.SetDataScalarTypeToUnsignedChar()67image_import.SetDataExtent(0, 511, 0, 511, 0, 511)68image_import.SetWholeExtent(0, 511, 0, 511, 0, 511)69image_import.SetNumberOfScalarComponents(1)70image_import.Update()71image_data = image_import.GetOutput()72#image_data1 = vtk.vtkImageData()73#image_data1.DeepCopy(image_data)74style = MyStyle()75irenWin = vtk.vtkRenderWindowInteractor()76   77#style = vtk.vtkInteractorStyleImage()78#style.SetInteractionModeToImageSlicing()79#style.AddObserver("LeftButtonPressEvent", fun1)80#irenWin.SetInteractorStyle(style)81imageViewer = vtk.vtkImageViewer2()82imageViewer.SetInput(image_data)83imageViewer.SetupInteractor(irenWin)84imageViewer.SetColorLevel(50)85imageViewer.SetColorWindow(100)86imageViewer.SetSlice(i)87imageViewer.SetSliceOrientationToXY()88imageViewer.Render()89irenWin.SetInteractorStyle(style)                                    #the location is important...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.