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https://github.com/serengil/deepface.git
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Resolve warnings of Logger library
Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
This commit is contained in:
Emmanuel Ferdman
parent
774012ab88
commit
66844b1687
@ -635,7 +635,7 @@ def detectFace(
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Returns:
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img (np.ndarray): detected (and aligned) facial area image as numpy array
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"""
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logger.warn("Function detectFace is deprecated. Use extract_faces instead.")
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logger.warning("Function detectFace is deprecated. Use extract_faces instead.")
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face_objs = extract_faces(
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img_path=img_path,
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detector_backend=detector_backend,
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@ -128,7 +128,7 @@ def extract_faces(
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continue
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if grayscale is True:
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logger.warn("Parameter grayscale is deprecated. Use color_face instead.")
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logger.warning("Parameter grayscale is deprecated. Use color_face instead.")
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current_img = cv2.cvtColor(current_img, cv2.COLOR_BGR2GRAY)
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else:
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if color_face == "rgb":
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@ -226,7 +226,7 @@ def detect_faces(
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# validate expand percentage score
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if expand_percentage < 0:
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logger.warn(
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logger.warning(
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f"Expand percentage cannot be negative but you set it to {expand_percentage}."
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"Overwritten it to 0."
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)
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@ -304,7 +304,7 @@ def extract_face(
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if align is True: # and left_eye is not None and right_eye is not None:
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# we were aligning the original image before, but this comes with an extra cost
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# instead we now focus on the facial area with a margin
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# and align it instead of original image to decrese the cost
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# and align it instead of original image to decrease the cost
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sub_img, relative_x, relative_y = extract_sub_image(img=img, facial_area=(x, y, w, h))
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aligned_sub_img, angle = align_img_wrt_eyes(
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@ -419,7 +419,7 @@ def align_img_wrt_eyes(
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right_eye: Optional[Union[list, tuple]],
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) -> Tuple[np.ndarray, float]:
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"""
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Align a given image horizantally with respect to their left and right eye locations
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Align a given image horizontally with respect to their left and right eye locations
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Args:
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img (np.ndarray): pre-loaded image with detected face
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left_eye (list or tuple): coordinates of left eye with respect to the person itself
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@ -453,7 +453,7 @@ def project_facial_area(
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"""
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Update pre-calculated facial area coordinates after image itself
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rotated with respect to the eyes.
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Inspried from the work of @UmutDeniz26 - github.com/serengil/retinaface/pull/80
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Inspired from the work of @UmutDeniz26 - github.com/serengil/retinaface/pull/80
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Args:
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facial_area (tuple of int): Representing the (x1, y1, x2, y2) of the facial area.
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@ -467,7 +467,7 @@ def project_facial_area(
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(x1, y1, x2, y2) or (x1, y1, x1+w1, y1+h1) of the rotated facial area.
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"""
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# Normalize the witdh of the angle so we don't have to
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# Normalize the width of the angle so we don't have to
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# worry about rotations greater than 360 degrees.
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# We workaround the quirky behavior of the modulo operator
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# for negative angle values.
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@ -142,7 +142,7 @@ def analysis(
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if freeze:
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frame += 1
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# restore raw image to get rid of countdown informtion
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# restore raw image to get rid of countdown information
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img = raw_img.copy()
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# add analyze results into img
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@ -197,7 +197,7 @@ def analysis(
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tic = time.time()
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logger.info("Freeze released")
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# count how many seconds required to relased freezed image in the left up area
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# count how many seconds required to released freezed image in the left up area
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freezed_img = countdown_to_release(img=freezed_img, tic=tic, time_threshold=time_threshold)
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display_img = img if freezed_img is None else freezed_img
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@ -267,7 +267,7 @@ def search_identity(
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)
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except ValueError as err:
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if f"No item found in {db_path}" in str(err):
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logger.warn(
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logger.warning(
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f"No item is found in {db_path}."
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"So, no facial recognition analysis will be performed."
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)
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@ -371,8 +371,8 @@ def countdown_to_freeze(
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Args:
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img (np.ndarray): image itself
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faces_coordinates (list): list of face coordinates as tuple with x, y, w and h
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frame_threshold (int): how many sequantial frames required with face(s) to freeze
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num_frames_with_faces (int): how many sequantial frames do we have with face(s)
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frame_threshold (int): how many sequential frames required with face(s) to freeze
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num_frames_with_faces (int): how many sequential frames do we have with face(s)
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Returns:
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img (np.ndarray): image with counter values
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"""
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@ -503,7 +503,7 @@ def perform_facial_recognition(
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model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512,
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OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face).
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Returns:
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img (np.ndarray): image with identified face informations
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img (np.ndarray): image with identified face information
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"""
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for idx, (x, y, w, h, is_real, antispoof_score) in enumerate(faces_coordinates):
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detected_face = detected_faces[idx]
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@ -598,7 +598,7 @@ def overlay_identified_face(
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w (int): w coordinate of the face on the given image
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h (int): h coordinate of the face on the given image
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Returns:
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img (np.ndarray): image with overlayed identity
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img (np.ndarray): image with overlaid identity
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"""
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try:
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if y - IDENTIFIED_IMG_SIZE > 0 and x + w + IDENTIFIED_IMG_SIZE < img.shape[1]:
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@ -767,7 +767,7 @@ def overlay_identified_face(
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x + w + IDENTIFIED_IMG_SIZE < img.shape[1]
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and y + h + IDENTIFIED_IMG_SIZE < img.shape[0]
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):
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# bottom righ
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# bottom right
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img[
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y + h : y + h + IDENTIFIED_IMG_SIZE,
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x + w : x + w + IDENTIFIED_IMG_SIZE,
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@ -149,7 +149,7 @@ def verify(
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)
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if silent is False:
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logger.warn(
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logger.warning(
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f"You passed {index}-th image as pre-calculated embeddings."
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"Please ensure that embeddings have been calculated"
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f" for the {model_name} model."
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@ -442,7 +442,7 @@ def is_form_data_file_testable() -> bool:
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threshold_version = version.parse("2.0.2")
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is_testable = flask_version <= threshold_version and werkzeus_version <= threshold_version
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if is_testable is False:
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logger.warn(
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logger.warning(
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"sending file in form data is not testable because of flask, werkzeus versions."
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f"Expected <= {threshold_version}, but {flask_version=} and {werkzeus_version}."
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)
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