Writing output to a text file

[marasate]

Hi,

I am new to the programming world. Can you please help to write the code which writes your output to the output.txt file?
I tried doing but wasn't able to get the full output.

Thank you

[kokou-sekpona]

supposed that we have this code in main.py:

import cv2
import numpy as np

Imports the Google Cloud client library

from google.cloud import vision

#Emotions
emo = ['Angry', 'Surprised','Sad', 'Happy', "Under Exposed", "Blurred", "Headwear"]
likelihood_name = ('UNKNOWN', 'VERY_UNLIKELY', 'UNLIKELY', 'POSSIBLE',
'LIKELY', 'VERY_LIKELY')

############## Spanish version #################
#emo = ['Bravo', 'Sorprendido','Triste', 'Feliz']
#string = 'Sin emocion'

#from google.oauth2 import service_account
#credentials = service_account.Credentials.from_service_account_file('VisionApp-9cb3e521631b.json')

Instantiates a client

vision_client = vision.ImageAnnotatorClient.from_service_account_file("key.json")

cv2.imshow('Video', np.empty((5,5),dtype=float))
compressRate = 1
while cv2.getWindowProperty('Video', 0) >= 0:
video_capture = cv2.VideoCapture(0)
ret, img = video_capture.read()
img = cv2.resize(img, (0,0), fx=compressRate , fy=compressRate )

ok, buf = cv2.imencode(".jpeg",img)
image = vision.types.Image(content=buf.tostring())

response = vision_client.face_detection(image=image)
faces = response.face_annotations
print('Number of faces: ', len(faces))
for face in faces:
    x = face.bounding_poly.vertices[0].x
    y = face.bounding_poly.vertices[0].y
    x2 = face.bounding_poly.vertices[2].x
    y2 = face.bounding_poly.vertices[2].y
    cv2.rectangle(img, (x, y), (x2, y2), (0, 255, 0), 2)

    sentiment = [likelihood_name[face.anger_likelihood],
                likelihood_name[face.surprise_likelihood],
                likelihood_name[face.sorrow_likelihood],
                likelihood_name[face.joy_likelihood],
                likelihood_name[face.under_exposed_likelihood],
                likelihood_name[face.blurred_likelihood],
                likelihood_name[face.headwear_likelihood]]

    for item, item2 in zip(emo, sentiment):
        print(item, ": ", item2)

    string = 'No sentiment'

    if not (all( item == 'VERY_UNLIKELY' for item in sentiment) ):
        if any( item == 'VERY_LIKELY' for item in sentiment):
            state = sentiment.index('VERY_LIKELY')
            # the order of enum type Likelihood is:
            #'LIKELY', 'POSSIBLE', 'UNKNOWN', 'UNLIKELY', 'VERY_LIKELY', 'VERY_UNLIKELY'
            # it makes sense to do argmin if VERY_LIKELY is not present, one would espect that VERY_LIKELY
            # would be the first in the order, but that's not the case, so this special case must be added
        else:
            state = np.argmin(sentiment)

        string = emo[state]

    cv2.putText(img,string, (x,y-5), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0,0,255), 2)

cv2.imshow("Video", img)
cv2.waitKey(1)
video_capture.release()

When everything is done, release the capture

cv2.destroyAllWindows()

The output is the string. So we will juste doing something like that just after this line :
cv2.putText(img,string, (x,y-5), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0,0,255), 2)
with open("new_file.txt", "w") as f:
f.write()

--------------or-------------------
....
cv2.putText(img,string, (x,y-5), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0,0,255), 2)
with open("new_file.txt", "ab") as f: #if you what to append new output result to existing lines in thhe txt file.
f.write()

I hope it will be helpfull