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load image either from json or form data
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@ -1,31 +1,86 @@
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# built-in dependencies
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from typing import Union
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# 3rd party dependencies
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from flask import Blueprint, request
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import numpy as np
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# project dependencies
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from deepface import DeepFace
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from deepface.api.src.modules.core import service
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from deepface.commons import image_utils
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from deepface.commons.logger import Logger
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logger = Logger()
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blueprint = Blueprint("routes", __name__)
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# pylint: disable=no-else-return, broad-except
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@blueprint.route("/")
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def home():
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return f"<h1>Welcome to DeepFace API v{DeepFace.__version__}!</h1>"
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def extract_image_from_request(img_key: str) -> Union[str, np.ndarray]:
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"""
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Extracts an image from the request either from json or a multipart/form-data file.
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Args:
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img_key (str): The key used to retrieve the image data
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from the request (e.g., 'img1').
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Returns:
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img (str or np.ndarray): Given image detail (base64 encoded string, image path or url)
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or the decoded image as a numpy array.
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"""
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# Check if the request is multipart/form-data (file input)
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if request.files:
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# request.files is instance of werkzeug.datastructures.ImmutableMultiDict
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# file is instance of werkzeug.datastructures.FileStorage
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file = request.files.get(img_key)
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if file is None:
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raise ValueError(f"Request form data doesn't have {img_key}")
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if file.filename == "":
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raise ValueError(f"No file uploaded for '{img_key}'")
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img = image_utils.load_image_from_file_storage(file)
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return img
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# Check if the request is coming as base64, file path or url from json or form data
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elif request.is_json or request.form:
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input_args = request.get_json() or request.form.to_dict()
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if input_args is None:
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raise ValueError("empty input set passed")
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# this can be base64 encoded image, and image path or url
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img = input_args.get(img_key)
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if not img:
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raise ValueError(f"'{img_key}' not found in either json or form data request")
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return img
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# If neither JSON nor file input is present
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raise ValueError(f"'{img_key}' not found in request in either json or form data")
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@blueprint.route("/represent", methods=["POST"])
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def represent():
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input_args = request.get_json()
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input_args = request.get_json() or request.form.to_dict()
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if input_args is None:
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return {"message": "empty input set passed"}
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img_path = input_args.get("img") or input_args.get("img_path")
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if img_path is None:
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return {"message": "you must pass img_path input"}
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try:
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img = extract_image_from_request("img")
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except Exception as err:
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return {"exception": str(err)}, 400
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obj = service.represent(
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img_path=img_path,
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img_path=img,
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model_name=input_args.get("model_name", "VGG-Face"),
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detector_backend=input_args.get("detector_backend", "opencv"),
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enforce_detection=input_args.get("enforce_detection", True),
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@ -41,23 +96,21 @@ def represent():
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@blueprint.route("/verify", methods=["POST"])
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def verify():
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input_args = request.get_json()
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input_args = request.get_json() or request.form.to_dict()
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if input_args is None:
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return {"message": "empty input set passed"}
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try:
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img1 = extract_image_from_request("img1")
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except Exception as err:
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return {"exception": str(err)}, 400
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img1_path = input_args.get("img1") or input_args.get("img1_path")
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img2_path = input_args.get("img2") or input_args.get("img2_path")
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if img1_path is None:
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return {"message": "you must pass img1_path input"}
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if img2_path is None:
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return {"message": "you must pass img2_path input"}
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try:
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img2 = extract_image_from_request("img2")
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except Exception as err:
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return {"exception": str(err)}, 400
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verification = service.verify(
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img1_path=img1_path,
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img2_path=img2_path,
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img1_path=img1,
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img2_path=img2,
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model_name=input_args.get("model_name", "VGG-Face"),
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detector_backend=input_args.get("detector_backend", "opencv"),
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distance_metric=input_args.get("distance_metric", "cosine"),
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@ -73,18 +126,31 @@ def verify():
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@blueprint.route("/analyze", methods=["POST"])
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def analyze():
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input_args = request.get_json()
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input_args = request.get_json() or request.form.to_dict()
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if input_args is None:
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return {"message": "empty input set passed"}
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try:
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img = extract_image_from_request("img")
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except Exception as err:
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return {"exception": str(err)}, 400
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img_path = input_args.get("img") or input_args.get("img_path")
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if img_path is None:
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return {"message": "you must pass img_path input"}
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actions = input_args.get("actions", ["age", "gender", "emotion", "race"])
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# actions is the only argument instance of list or tuple
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# if request is form data, input args can either be text or file
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if isinstance(actions, str):
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actions = (
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actions.replace("[", "")
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.replace("]", "")
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.replace("(", "")
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.replace(")", "")
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.replace('"', "")
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.replace("'", "")
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.replace(" ", "")
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.split(",")
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)
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demographies = service.analyze(
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img_path=img_path,
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actions=input_args.get("actions", ["age", "gender", "emotion", "race"]),
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img_path=img,
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actions=actions,
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detector_backend=input_args.get("detector_backend", "opencv"),
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enforce_detection=input_args.get("enforce_detection", True),
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align=input_args.get("align", True),
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