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https://github.com/serengil/deepface.git
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1078be9f12
we were handling resizing in extract faces. with this commit we moved it to representation module to provide seperation of concern.
106 lines
3.3 KiB
Python
106 lines
3.3 KiB
Python
import matplotlib.pyplot as plt
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from deepface import DeepFace
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from deepface.commons.logger import Logger
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logger = Logger()
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# some models (e.g. Dlib) and detectors (e.g. retinaface) do not have test cases
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# because they require to install huge packages
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# this module is for local runs
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model_names = [
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"VGG-Face",
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"Facenet",
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"Facenet512",
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"OpenFace",
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"DeepFace",
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"DeepID",
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"Dlib",
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"ArcFace",
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"SFace",
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"GhostFaceNet",
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]
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detector_backends = [
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"opencv",
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"ssd",
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"dlib",
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"mtcnn",
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"fastmtcnn",
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# "mediapipe", # crashed in mac
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"retinaface",
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"yunet",
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"yolov8",
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]
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# verification
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for model_name in model_names:
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obj = DeepFace.verify(
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img1_path="dataset/img1.jpg", img2_path="dataset/img2.jpg", model_name=model_name
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)
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logger.info(obj)
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logger.info("---------------------")
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# represent
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for model_name in model_names:
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embedding_objs = DeepFace.represent(img_path="dataset/img1.jpg", model_name=model_name)
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for embedding_obj in embedding_objs:
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embedding = embedding_obj["embedding"]
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logger.info(f"{model_name} produced {len(embedding)}D vector")
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# find
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dfs = DeepFace.find(
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img_path="dataset/img1.jpg", db_path="dataset", model_name="Facenet", detector_backend="mtcnn"
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)
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for df in dfs:
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logger.info(df)
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expand_areas = [0]
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img_paths = ["dataset/img11.jpg", "dataset/img11_reflection.jpg"]
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for expand_area in expand_areas:
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for img_path in img_paths:
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# extract faces
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for detector_backend in detector_backends:
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face_objs = DeepFace.extract_faces(
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img_path=img_path,
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detector_backend=detector_backend,
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align=True,
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expand_percentage=expand_area,
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)
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for face_obj in face_objs:
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face = face_obj["face"]
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logger.info(detector_backend)
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logger.info(face_obj["facial_area"])
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logger.info(face_obj["confidence"])
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# we know opencv sometimes cannot find eyes
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if face_obj["facial_area"]["left_eye"] is not None:
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assert isinstance(face_obj["facial_area"]["left_eye"], tuple)
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assert isinstance(face_obj["facial_area"]["left_eye"][0], int)
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assert isinstance(face_obj["facial_area"]["left_eye"][1], int)
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if face_obj["facial_area"]["right_eye"] is not None:
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assert isinstance(face_obj["facial_area"]["right_eye"], tuple)
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assert isinstance(face_obj["facial_area"]["right_eye"][0], int)
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assert isinstance(face_obj["facial_area"]["right_eye"][1], int)
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# left eye is really the left eye of the person
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if (
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face_obj["facial_area"]["left_eye"] is not None
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and face_obj["facial_area"]["right_eye"] is not None
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):
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re_x = face_obj["facial_area"]["right_eye"][0]
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le_x = face_obj["facial_area"]["left_eye"][0]
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assert re_x < le_x, "right eye must be the right eye of the person"
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assert isinstance(face_obj["confidence"], float)
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assert face_obj["confidence"] <= 1
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plt.imshow(face)
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plt.axis("off")
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plt.show()
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logger.info("-----------")
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