def post():
print("saving image...")
print("base64 image")
data = _child_parser.parse_args()
image = data['photo']
img_name = str(uuid.uuid4()) + '.jpg'
create_new_folder(os.path.join(real_path, 'images'))
saved_path = os.path.join(os.path.join(real_path, 'images'), img_name)
with open(saved_path, "wb") as fh:
fh.write(base64.decodebytes(image.encode()))
# section for saving child info into database
child = ChildModel(data['name'], data['address'], data['parent_name'],
data['phone'], img_name)
child.save_to_db()
print("cropping face...")
id = child.id # get this value from database(child record id)
if not crop_face(saved_path,
os.path.join(os.getcwd(),
'croped_images/' + str(id))):
return {"message": "face not found in image"}, 404
print("generating multiple images...")
# generating multiple image from uploaded image
datagen = ImageDataGenerator(rotation_range=40,
width_shift_range=0.2,
height_shift_range=0.2,
shear_range=0.2,
zoom_range=0.2,
horizontal_flip=True,
fill_mode='nearest')
img = load_img(
os.path.join(os.getcwd(), 'croped_images/' + str(id) +
'/1.jpg')) # this is a PIL image
x = img_to_array(img) # this is a Numpy array with shape (3, 150, 150)
x = x.reshape(
(1, ) +
x.shape) # this is a Numpy array with shape (1, 3, 150, 150)
# the .flow() command below generates batches of randomly transformed images
# and saves the results to the `preview/` directory
if not os.path.exists(os.path.join(os.getcwd(), 'train/' + str(id))):
os.makedirs(os.path.join(os.getcwd(), 'train/' + str(id)))
i = 0
for batch in datagen.flow(x,
batch_size=1,
save_to_dir=os.path.join(
os.getcwd(), 'train/' + str(id)),
save_prefix='image',
save_format='jpg'):
i += 1
if i > 5:
break
# training
print("training...")
train(id)
return {"message": "success"}
def post(self):
data = attributes.parse_args()
parents_id = list(data['parents'].split(","))
if len(parents_id) > 2:
return {"message": "Child cannot have more than 2 Parents"}
child = ChildModel(**data)
child.save_child()
return {"message": "Child cread successfully!"}, 201
def get(child_id):
print("Deleting...")
child = ChildModel.find_user_by_id(child_id)
if child:
try:
print("removing from db...")
child.remove_from_db()
except:
print("error occured")
try:
print("deleting from csv...")
df = pd.read_csv("data.csv", header=None)
df = df.set_index(0)
df = df.drop(child_id)
df.to_csv("data.csv", header=None)
except:
print("error occurred")
try:
print("deleting from images folder")
child_image_name = child.image
path = os.path.join(real_path, 'images', child_image_name)
os.remove(path)
except:
print("error occurred")
try:
print("deleting from train folder")
path = os.path.join(os.getcwd(), 'train', str(child_id))
shutil.rmtree(path)
except:
print("error occurred")
try:
print("deleting from croped_images folder")
path = os.path.join(os.getcwd(), 'croped_images',
str(child_id))
shutil.rmtree(path)
except:
print("error occurred")
try:
print("Training Model...")
data = pd.read_csv(os.path.join(real_path, 'data.csv'),
header=None)
labels = data.loc[:, 0].to_numpy()
data = data.loc[:, 1:].to_numpy()
clf = svm.SVC(probability=True)
clf.fit(data, labels)
pickle.dump(clf, open("svm_model.sav", 'wb'))
except:
print("error occured")
return {"message": "success"}
else:
print("child not found")
return {"message": "Child Doesn't Exists."}
def get(self):
user_id = get_jwt_identity()
children = [child.json() for child in ChildModel.find_all()]
if user_id:
return {'children': children}, 200
return {
'message': 'no data available unless you log in.',
'error': 'token expired'
}, 401
def get(self, parents):
childs = ChildModel.childs()
data = []
if childs:
for child in childs:
if len(child.parents) == parents:
data.appen(child)
return data
return {'message': 'There are no registered childs'}, 404
def put(self, id):
data = attributes.parse_args()
parents_id = list(data['parents'].split(","))
if len(parents_id) > 2:
return {"message": "Child cannot have more than 2 Parents"}
child = ChildModel.find_child(id)
if child:
child.update_child(data)
return {'message': 'Updated child'}
return {'message': 'Child not found'}, 404
def get(self):
childs = ChildModel.childs()
temp_childs = []
if childs:
for child in childs:
data = {
'id': child.id,
'name': child.name,
'child': child.child,
'createdAt': str(child.createdAt),
'updatedAt': str(child.updatedAt)
}
temp_childs.append(data)
return temp_childs
return {'message': 'There are no registered childs'}, 404
def post(self):
print("getting image...")
if request.files.get("image"):
print("image file..")
img = request.files['image']
img_name = str(uuid.uuid4()) + '.jpg'
create_new_folder(os.path.join(real_path, 'temp_images'))
saved_path = os.path.join(os.path.join(real_path, 'temp_images'),
img_name)
img.save(saved_path)
else:
print("base64 image..")
data = _child_search_parser.parse_args()
img_name = str(uuid.uuid4()) + '.jpg'
create_new_folder(os.path.join(real_path, 'temp_images'))
saved_path = os.path.join(os.path.join(real_path, 'temp_images'),
img_name)
with open(saved_path, "wb") as fh:
fh.write(base64.decodebytes(data['image'].encode()))
print("cropping face...")
if not crop_face(saved_path,
os.path.join(os.getcwd(), 'temp_croped_images')):
return {"message": "face not found in image"}, 404
print("finding matching image...")
try:
model_path = os.path.join(real_path, "model.h5")
vgg_face_descriptor = load_model(model_path)
svm_model = pickle.load(
open(os.path.join(real_path, "svm_model.sav"), 'rb'))
x = vgg_face_descriptor.predict(
preprocess_image(
os.path.join(real_path, 'temp_croped_images/1.jpg')))
print("Probability: " + str(np.max(svm_model.predict_proba(x))))
if np.max(svm_model.predict_proba(x)) < 0.6:
return {"message": "Child not found"}, 404
res = svm_model.predict(x)
child = ChildModel.find_user_by_id(res[0])
print(child)
if child:
return {"message": "success", "data": child.json()}, 200
else:
return {"message": "Child not found"}, 404
except:
return {"message": "Child not found"}, 404
def post(self, child_id):
data = parser.parse_args()
if ChildModel.find_by_name(data['first_name'], data['last_name'], data['dob']):
return {"message": "Child with that name already exists."}, 400
child = ChildModel(**data)
try:
child.save_to_db()
except:
return {"message": "An error occurred adding the child."}, 500
return child.json(), 201
def get():
children = ChildModel.find_all()
return children, 200
def delete(cls, child_id):
child = ChildModel.find_by_id(child_id)
if not child:
return {'message': 'Child not found.'}, 404
child.delete_from_db()
return {'message': 'Child deleted.'}, 200
def get(cls, child_id):
child = ChildModel.find_by_id(child_id)
if not child:
return {'message': 'Child not found.'}, 404
return child.json()
def delete(self, id):
child = ChildModel.find_child(id)
if child:
child.delete_child()
return {'message': 'Child deleted'}
return {'message': 'Child not found'}, 404
def get(self, id):
child = ChildModel.find_child(id)
if child:
return child.json()
return {'message': 'Child not found'}, 404