def loading_data(pickle_data):
if path.isfile(pickle_data):
Colors.print_infos("[LOADING] Loading Data Serialised...")
# Load the serialised Data
data = pickle.loads(open(pickle_data, "rb").read())
Colors.print_sucess("[LOADING] Loading Data Completed\n")
return data
else:
Colors.print_error("[ERROR] File Not Found : " + str(pickle_data))
return None
def run(self, fd, obj, pickle_data):
# Get list of files in Folder
data = Serializer.format_data(glob.glob("IMAGE_DB_RAW/*"))
# *======================*
# | Create Database Tree |
# *======================*
Colors.print_infos("[INFO] Create Folders of databases...\n")
for name in data.name:
if not os.path.isdir("Data/IMAGE_DB/" + name):
os.mkdir("Data/IMAGE_DB/" + name)
# *=======================*
# | Extract Faces Process |
# *=======================*
cpt = 0
t2 = time.time()
for img_path in data.image:
Colors.print_infos("\n[PROCESSING] Try to Detect a Person...")
# *===================*
# | Performed Process |
# *===================*
yolo_result = obj.run(img_path)
if re.match('person', yolo_result):
Colors.print_sucess("[PROCESSING] Person Detected !")
Colors.print_infos("[PROCESSING] Running Extract Faces Processing...")
# print(img_path)
Colors.print_infos("[PROCESSING] Extract Faces {}/{}".format(cpt + 1, len(data.image)))
t1 = time.time()
result = fd.ExtractFace(cv2.imread(img_path), "Data/IMAGE_DB/" + str(data.name[cpt]) + "/result_" + str(cpt))
Colors.print_infos("[PROCESSING] Faces Detected : {} in {} s".format(result, time.time() - t1))
del t1
del result
else:
Colors.print_error("[PROCESSING] No Face Detected !")
cpt += 1
Colors.print_infos("[INFO] Remove file in IMG_DB_RAW...")
os.system("rm -rfv IMAGE_DB_RAW/*")
Colors.print_sucess("\n[SUCCESS] Extraction Completed in " + str(round(time.time()-t2, 4)) + " s\n")
# Cleanning RAM
del data
del fd
del cpt
del t2
data = Serializer.format_data(glob.glob("Data/IMAGE_DB/*"))
# Saving Data
Serializer.saving_data(data, pickle_data)
def __init__(self,
user='******',
passwd='zmpass',
host='localhost',
database='zm'):
try:
self._db = mysql.connector.connect(host=host,
user=user,
passwd=passwd,
database=database)
except mysql.connector.Error as err:
Colors.print_error("\n[ERROR] Could not connect to " + host + "\n")
traceback.print_exc()
exit(1)
def _load_and_align_images(self, filepaths):
aligned_images = []
for filepath in filepaths:
# print(filepath)
img = cv2.imread(filepath)
if img is not None:
aligned = self._align_face(img)
aligned = (aligned / 255.).astype(np.float32)
aligned = np.expand_dims(aligned, axis=0)
aligned_images.append(aligned)
else:
Colors.print_error("[ERROR] File Not Found in ImageDatabases: " + filepath)
return np.array(aligned_images)
if "car" in yolo_result.Result[
cpt] or "truck" in yolo_result.Result[cpt]:
if yolo_result.Result[cpt] not in result_voit:
result_voit += " " + yolo_result.Result[cpt]
# *======================================*
# | Remove Images that nothings detected |
# *======================================*
cpt = 0
# sql = SQLHelpers()
for im1 in images:
for im2 in yolo_result.Images:
if im1 not in im2:
id = re.findall(r'\b\d+\b', im1)
if len(id) == 2:
Colors.print_error("[DELETE] Delete Images : " + im1 +
" With Id : " + str(id[1]))
# sql.delete_frames(str(id[0]), str(id[1]))
os.system("rm -rfv " + im1)
cpt += 1
if result_pers:
Colors.print_sucess("Person Detected : " + result_pers)
if result_voit:
Colors.print_sucess("Voiture Detected : " + result_voit)
Colors.print_sucess("\n[SUCCESS] Finished with Total processing time : " +
str(round(time.time() - t1, 3)) + " s")
_remove_lock()
del images