print("Failed to get response from jobserver")
time.sleep(1)
continue
if(response['processed'] == 1):
print("response is processed")
time.sleep(1)
filename = response['filename']
realFilename = filename
if(filename[:2] == "._"):
filename = filename[2:]
process_start_time = datetime.datetime.utcnow()
if(not dbHelper.getImageFromAzureBlob(filename, PICTURE_DIR + filename)):
print("Failed to get image", filename)
continue
download_end_time = datetime.datetime.utcnow()
print("Got image: ", filename, " from blob " + "in " + str((download_end_time - process_start_time).total_seconds()))
img = cv2.imread(PICTURE_DIR + filename)
os.remove(PICTURE_DIR + filename)
if img is None:
print("Image is none!")
continue
cascade = cv2.CascadeClassifier('./haarcascade_frontalface_default.xml')
eyeCascade = cv2.CascadeClassifier('./haarcascade_eye.xml')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
if (response == False):
print("Failed to get response from jobserver")
time.sleep(1)
continue
if (response['processed'] == 1):
time.sleep(1)
filename = response['filename']
realFilename = filename
if (filename[:2] == "._"):
filename = filename[2:]
dbHelper.getImageFromAzureBlob(filename, "/app/Pics/" + filename)
print("Got image: ", filename, " from blob")
img = cv2.imread("/app/Pics/" + filename)
cascade = cv2.CascadeClassifier('/app/haarcascade_frontalface_default.xml')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray = cv2.equalizeHist(gray)
rects = detect(gray, cascade)
if rects != []:
sys.stderr.write(
'\ntrue rect') # Count the number of images with faces
sendRes(jobserver_url, realFilename, "true")