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from flask import Blueprint, request , jsonify
from deepface.api.src.modules.core import service
from deepface.commons.logger import Logger
from deepface.commons.os_path import os_path
import json
import os
logger = Logger(module="api/src/routes.py")
blueprint = Blueprint("routes", __name__)
@blueprint.route("/")
def home():
return "<h1>Welcome to DeepFace API!</h1>"
@blueprint.route("/represent", methods=["POST"])
def represent():
input_args = request.get_json()
if input_args is None:
return {"message": "empty input set passed"}
img_path = input_args.get("img") or input_args.get("img_path")
if img_path is None:
return {"message": "you must pass img_path input"}
model_name = input_args.get("model_name", "VGG-Face")
detector_backend = input_args.get("detector_backend", "opencv")
enforce_detection = input_args.get("enforce_detection", True)
align = input_args.get("align", True)
obj = service.represent(
img_path=img_path,
model_name=model_name,
detector_backend=detector_backend,
enforce_detection=enforce_detection,
align=align,
)
logger.debug(obj)
return obj
@blueprint.route("/verify", methods=["POST"])
def verify():
input_args = request.get_json()
if input_args is None:
return {"message": "empty input set passed"}
img1_path = input_args.get("img1") or input_args.get("img1_path")
img2_path = input_args.get("img2") or input_args.get("img2_path")
if img1_path is None:
return {"message": "you must pass img1_path input"}
if img2_path is None:
return {"message": "you must pass img2_path input"}
model_name = input_args.get("model_name", "VGG-Face")
detector_backend = input_args.get("detector_backend", "opencv")
enforce_detection = input_args.get("enforce_detection", True)
distance_metric = input_args.get("distance_metric", "cosine")
align = input_args.get("align", True)
verification = service.verify(
img1_path=img1_path,
img2_path=img2_path,
model_name=model_name,
detector_backend=detector_backend,
distance_metric=distance_metric,
align=align,
enforce_detection=enforce_detection,
)
logger.debug(verification)
return verification
@blueprint.route("/analyze", methods=["POST"])
def analyze():
input_args = request.get_json()
if input_args is None:
return {"message": "empty input set passed"}
img_path = input_args.get("img") or input_args.get("img_path")
if img_path is None:
return {"message": "you must pass img_path input"}
detector_backend = input_args.get("detector_backend", "opencv")
enforce_detection = input_args.get("enforce_detection", True)
align = input_args.get("align", True)
actions = input_args.get("actions", ["age", "gender", "emotion", "race"])
demographies = service.analyze(
img_path=img_path,
actions=actions,
detector_backend=detector_backend,
enforce_detection=enforce_detection,
align=align,
)
logger.debug(demographies)
return demographies
@blueprint.route("/find", methods=["POST"])
def find():
input_args = request.get_json()
if input_args is None:
response = jsonify({'error': 'empty input set passed'})
response.status_code = 500
return response
img_name = input_args.get("img") or input_args.get("img_name")
img_type = input_args.get("img_type")
if img_name is None:
response = jsonify({'error': 'you must pass img_name input'})
response.status_code = 404
return response
if img_type == "missing" or img_type == "missing_person" or img_type == "missing_people" or img_type == "missing person" or img_type == "missing people" :
img_path = os.path.join( os_path.get_main_directory() , 'mafqoud' , 'images' , "missing_people" , img_name)
db_path = os.path.join( os_path.get_main_directory() , 'mafqoud' , 'images' , "founded_people")
elif img_type == "founded" or img_type == "founded_person" or img_type == "founded_people" or img_type == "founded person" or img_type == "founded people" :
img_path = os.path.join( os_path.get_main_directory() , 'mafqoud' , 'images' , "founded_people" , img_name)
db_path = os.path.join( os_path.get_main_directory() , 'mafqoud' , 'images' , "missing_people")
else :
response = jsonify({'error': 'the type of the image is not correct and it should be one of those : ( missing , missing_people , missing_people , missing person , missing people ) or ( founded , founded_people , founded_people , founded person , founded people )'})
response.status_code = 400
return response
print(img_path)
if not os.path.exists(img_path) or not os.path.isfile(img_path):
# If the image does not exist, return a JSON response with status code 404
response = jsonify({'error': 'Image not found'})
response.status_code = 404
return response
model_name = input_args.get("model_name", "Facenet512")
detector_backend = input_args.get("detector_backend", "mtcnn")
enforce_detection = input_args.get("enforce_detection", True)
distance_metric = input_args.get("distance_metric", "euclidean_l2")
align = input_args.get("align", True)
if img_name is None:
return {"message": "you must pass img1_path input"}
if db_path is None:
dataset_path = os.path.join(path.get_parent_path(), 'dataset')
if img_type == "missing_person":
img_path = os.path.join(dataset_path, 'missing_people', img_name)
db_path = os.path.join(dataset_path, 'founded_people')
elif img_type == "founded_people":
img_path = os.path.join(dataset_path, 'founded_people', img_name)
db_path = os.path.join(dataset_path, 'missing_people')
results = service.find(
img_path=img_path,
db_path=db_path,
model_name=model_name,
detector_backend=detector_backend,
distance_metric=distance_metric,
align=align,
enforce_detection=enforce_detection,
)
# Calculate similarity_percentage for each row
results[0]['similarity_percentage'] =100 - ((results[0]['distance'] / results[0]['threshold']) * 100)
data = []
for _, row in results[0].iterrows():
data.append({
"identity": row['identity'],
"similarity_percentage": row['similarity_percentage']
})
json_data = json.dumps(data, indent=4)
logger.debug(json_data)
return json_data
@blueprint.route("/dataset/sync", methods=["GET"])
def sync_datasets():
result = service.sync_datasets()
return jsonify(result)
@blueprint.route("/delete/pkls", methods=["GET"])
def delete_pkls():
result = service.delete_pkls()
return jsonify(result) |