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Merge pull request #1126 from serengil/feat-task-1903-bugs-and-enhancements
Feat task 1903 bugs and enhancements
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commit
de2f08fe5c
@ -4,6 +4,11 @@ import warnings
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import logging
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from typing import Any, Dict, List, Tuple, Union, Optional
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# this has to be set before importing tensorflow
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os.environ["TF_USE_LEGACY_KERAS"] = "1"
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# pylint: disable=wrong-import-position
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# 3rd party dependencies
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import numpy as np
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import pandas as pd
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@ -28,6 +33,9 @@ logger = Logger(module="DeepFace")
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# -----------------------------------
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# configurations for dependencies
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# users should install tf_keras package if they are using tf 2.16 or later versions
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package_utils.validate_for_keras3()
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warnings.filterwarnings("ignore")
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os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
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tf_version = package_utils.get_tf_major_version()
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@ -23,6 +23,7 @@ if tf_major == 1:
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Flatten,
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Dense,
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Dropout,
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LocallyConnected2D,
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)
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else:
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from tensorflow.keras.models import Model, Sequential
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@ -32,6 +33,7 @@ else:
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Flatten,
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Dense,
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Dropout,
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LocallyConnected2D,
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)
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@ -43,14 +45,6 @@ class DeepFaceClient(FacialRecognition):
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"""
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def __init__(self):
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# DeepFace requires tf 2.12 or less
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if tf_major == 2 and tf_minor > 12:
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# Ref: https://github.com/serengil/deepface/pull/1079
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raise ValueError(
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"DeepFace model requires LocallyConnected2D but it is no longer supported"
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f" after tf 2.12 but you have {tf_major}.{tf_minor}. You need to downgrade your tf."
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)
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self.model = load_model()
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self.model_name = "DeepFace"
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self.input_shape = (152, 152)
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@ -75,13 +69,6 @@ def load_model(
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"""
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Construct DeepFace model, download its weights and load
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"""
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# we have some checks for this dependency in the init of client
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# putting this in global causes library initialization
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if tf_major == 1:
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from keras.layers import LocallyConnected2D
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else:
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from tensorflow.keras.layers import LocallyConnected2D
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base_model = Sequential()
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base_model.add(
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Convolution2D(32, (11, 11), activation="relu", name="C1", input_shape=(152, 152, 3))
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@ -50,3 +50,24 @@ def find_hash_of_file(file_path: str) -> str:
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hasher = hashlib.sha1()
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hasher.update(properties.encode("utf-8"))
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return hasher.hexdigest()
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def validate_for_keras3():
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tf_major = get_tf_major_version()
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tf_minor = get_tf_minor_version()
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# tf_keras is a must dependency after tf 2.16
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if tf_major == 1 or (tf_major == 2 and tf_minor < 16):
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return
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try:
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import tf_keras
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logger.debug(f"tf_keras is already available - {tf_keras.__version__}")
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except ImportError as err:
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# you may consider to install that package here
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raise ValueError(
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f"You have tensorflow {tf.__version__} and this requires "
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"tf-keras package. Please run `pip install tf-keras` "
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"or downgrade your tensorflow."
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) from err
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@ -53,6 +53,14 @@ class OpenCvClient(Detector):
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for (x, y, w, h), confidence in zip(faces, scores):
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detected_face = img[int(y) : int(y + h), int(x) : int(x + w)]
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left_eye, right_eye = self.find_eyes(img=detected_face)
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# eyes found in the detected face instead image itself
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# detected face's coordinates should be added
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if left_eye is not None:
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left_eye = (int(x + left_eye[0]), int(y + left_eye[1]))
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if right_eye is not None:
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right_eye = (int(x + right_eye[0]), int(y + right_eye[1]))
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facial_area = FacialAreaRegion(
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x=x,
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y=y,
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@ -132,6 +132,13 @@ class SsdClient(Detector):
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left_eye, right_eye = opencv_module.find_eyes(detected_face)
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# eyes found in the detected face instead image itself
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# detected face's coordinates should be added
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if left_eye is not None:
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left_eye = (int(x + left_eye[0]), int(y + left_eye[1]))
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if right_eye is not None:
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right_eye = (int(x + right_eye[0]), int(y + right_eye[1]))
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facial_area = FacialAreaRegion(
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x=x,
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y=y,
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