Files
PY_CK/app.py
T
2024-10-05 21:37:46 +02:00

67 lines
2.1 KiB
Python

import cv2
import time
import os
import requests
import json
treashold = float(os.getenv('FACE_TRASHOLD', '0.5'))
sever = os.getenv('API_ROOT', 'localhost:8000')
root_api_url = 'http://{}/local'.format(sever)
base_path = '/app/data/'
print(str(root_api_url))
#try:
while True:
r = requests.get('{}/anonymize'.format(root_api_url))
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
response = r.json()
for detection in response:
img_path = "{}{}".format(base_path, detection['source_image_path'])
#Skip Non existing files
if (not os.path.exists(img_path)):
continue
img = cv2.imread(img_path)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces, rejects, weights = face_cascade.detectMultiScale3(gray, 1.1, 4, outputRejectLevels = 1)
#Count faces is null dont anonimize file
if (len(faces) < 0):
continue
i = 0
for (x, y, w, h) in faces:
confidence = float(weights[i])
if (confidence > treashold):
face_roi = img[y:y+h, x:x+w]
blurred_face = cv2.GaussianBlur(face_roi, (99, 99), 50)
img[y:y+h, x:x+w] = blurred_face
print(weights[i])
text = "{}".format(weights[i])
#cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)
#cv2.putText(img, text, (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.45, (0, 0, 255), 2)
i = i +1
extension = img_path[img_path.index(".")+1:]
new_img_path = img_path.replace((".{}".format(extension)), ('_anonym.{}'.format(extension)))
cv2.imwrite(new_img_path, img)
data = {
"id": detection['id'],
"source_image_path": new_img_path.replace(base_path,"")
}
response = requests.post('{}/anonymize'.format(root_api_url), json=data)
time.sleep(900)
# except Exception as e:
# print("An exception occurred")
# print(str(e))
# data = {"trace": str(e)}
# response = requests.post('{}/log'.format(root_api_url), json=data)