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@tkan
Last active November 10, 2017 08:59
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A small project to get a digital punch clock where the face serves as fist
from PIL import Image
import face_recognition
import time
import datetime
import sqlite3
from sqlite3 import Error
import os
import logging
import subprocess
timestamp = datetime.datetime.now()
date = timestamp.strftime('%d-%m-%Y')
webcam_file = os.path.join(os.path.dirname(os.path.realpath(__file__)), "webcam.jpg")
#~ save_file = os.path.join(os.path.dirname(os.path.realpath(__file__)), "sf_")
log_file = os.path.join(os.path.dirname(os.path.realpath(__file__)), "timetrack.log")
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger()
handler = logging.FileHandler(log_file)
handler.setLevel(logging.DEBUG)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
handler.setFormatter(formatter)
logger.addHandler(handler)
db_file = os.path.join(os.path.dirname(os.path.realpath(__file__)), "timetrack.db")
sql_create_table = """ CREATE TABLE IF NOT EXISTS entries (
id integer PRIMARY KEY,
date text NOT NULL,
timestamp text,
comment text); """
try:
conn = sqlite3.connect(db_file)
try:
c = conn.cursor()
c.execute(sql_create_table)
except Error as e:
print(e)
except Error as e:
logger.debug(e)
finally:
conn.close()
subprocess.call("fswebcam -q -r 640x480 --jpeg 85 {0}".format(webcam_file), shell=True, stderr=subprocess.STDOUT)
# Load the jpg file into a numpy array
image = face_recognition.load_image_file(webcam_file)
# Find all the faces in the image using a pre-trained convolutional neural network.
# This method is more accurate than the default HOG model, but it's slower
# unless you have an nvidia GPU and dlib compiled with CUDA extensions. But if you do,
# this will use GPU acceleration and perform well.
# See also: find_faces_in_picture.py
face_locations = face_recognition.face_locations(image, number_of_times_to_upsample=0, model="cnn")
#print("I found {} face(s) in this photograph.".format(len(face_locations)))
for face_location in face_locations:
#~ # Print the location of each face in this image
#~ top, right, bottom, left = face_location
#~ # print("A face is located at pixel location Top: {}, Left: {}, Bottom: {}, Right: {}".format(top, left, bottom, right))
#~ # You can access the actual face itself like this:
#~ face_image = image[top:bottom, left:right]
#~ pil_image = Image.fromarray(face_image)
#~ pil_image.save(str(save_file) + str(int(time.time())) + ".jpg")
comment = "user present"
logger.info('DB INSERT: user present')
data = [date, timestamp, comment]
sql_new_entry = """INSERT INTO entries(date, timestamp, comment)
VALUES (?,?,?); """
conn = sqlite3.connect(db_file)
try:
c = conn.cursor()
c.execute(sql_new_entry, data)
conn.commit()
except Error as e:
logger.debug(e)
finally:
conn.close()
if len(face_locations) == 0:
comment = "empty"
logger.info('DB INSERT: place is empty')
data = [date, timestamp, comment]
sql_new_entry = """INSERT INTO entries(date, timestamp, comment)
VALUES (?,?,?); """
conn = sqlite3.connect(db_file)
try:
c = conn.cursor()
c.execute(sql_new_entry, data)
conn.commit()
except Error as e:
logger.debug(e)
finally:
conn.close()
sqlite3 -header -csv timetrack.db < timetrack_export.sql > out.csv
with xxx as (
select date as break_date, count(comment), min(time(datetime(timestamp))) as "break_in", max(time(datetime(timestamp))) as "break_out" from entries
where comment like 'empty'
and (time(datetime(timestamp)) >= '11:50:00' and time(datetime(timestamp)) <= '13:00:00')
group by date
)
select date,round(substr(min(strftime('%H:%M',datetime(timestamp))),1,2) + (CAST(substr(min(strftime('%H:%M',datetime(timestamp))),4,2) as float)/60),1) as "in",
round(substr(xxx.break_in,1,2) + (CAST(substr(xxx.break_in,4,2) as float)/60),1) as break_in,
round(substr(xxx.break_out,1,2) + (CAST(substr(xxx.break_out,4,2) as float)/60),1) as break_out,
round(substr(max(strftime('%H:%M',datetime(timestamp))),1,2) + (CAST(substr(max(strftime('%H:%M',datetime(timestamp))),4,2) as float)/60),1) as "out"
from entries
left join xxx
on xxx.break_date = date
where comment like 'user present'
group by date
order by datetime(substr(date, 7,4) || '-' || substr(date, 4, 2)|| '-' || substr(date, 1, 2)); --order by date
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