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Unlinted changes
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.vscode/settings.json
vendored
4
.vscode/settings.json
vendored
@ -9,5 +9,7 @@
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"python.formatting.provider": "black",
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"python.formatting.blackArgs": ["--line-length=100"],
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"editor.fontWeight": "normal",
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"python.analysis.extraPaths": ["./deepface"]
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"python.analysis.extraPaths": ["./deepface"],
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"stylelint.autoFixOnSave": false,
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"standard.autoFixOnSave": false
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}
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@ -41,7 +41,6 @@ if tf_version == 2:
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def build_model(model_name):
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"""
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This function builds a deepface model
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Parameters:
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@ -96,7 +95,6 @@ def verify(
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align=True,
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normalization="base",
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):
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"""
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This function verifies an image pair is same person or different persons. In the background,
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verification function represents facial images as vectors and then calculates the similarity
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@ -119,9 +117,9 @@ def verify(
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detector_backend (string): set face detector backend to opencv, retinaface, mtcnn, ssd,
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dlib or mediapipe
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align (boolean): alignment according to the eye positions.
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normalization (string): normalize the input image before feeding to model
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Returns:
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@ -235,9 +233,8 @@ def analyze(
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align=True,
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silent=False,
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):
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"""
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This function analyzes facial attributes including age, gender, emotion and race.
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This function analyze facial attributes including age, gender, emotion and race.
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In the background, analysis function builds convolutional neural network models to
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classify age, gender, emotion and race of the input image.
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@ -255,7 +252,7 @@ def analyze(
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detector_backend (string): set face detector backend to opencv, retinaface, mtcnn, ssd,
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dlib or mediapipe.
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align (boolean): alignment according to the eye positions.
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silent (boolean): disable (some) log messages
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@ -300,6 +297,16 @@ def analyze(
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actions = (actions,)
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actions = list(actions)
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if not actions:
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raise ValueError("`actions` must be a list of strings.")
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for action in actions:
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if action not in ("emotion", "age", "gender", "race"):
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raise ValueError(
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f"Invalid action passed ({action})). "
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"Valid actions are `emotion`, `age`, `gender`, `race`."
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)
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# ---------------------------------
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# build models
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models = {}
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@ -398,7 +405,6 @@ def find(
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normalization="base",
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silent=False,
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):
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"""
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This function applies verification several times and find the identities in a database
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@ -422,9 +428,9 @@ def find(
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detector_backend (string): set face detector backend to opencv, retinaface, mtcnn, ssd,
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dlib or mediapipe
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align (boolean): alignment according to the eye positions.
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normalization (string): normalize the input image before feeding to model
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silent (boolean): disable some logging and progress bars
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@ -448,7 +454,6 @@ def find(
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file_name = file_name.replace("-", "_").lower()
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if path.exists(db_path + "/" + file_name):
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if not silent:
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print(
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f"WARNING: Representations for images in {db_path} folder were previously stored"
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@ -616,7 +621,6 @@ def represent(
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align=True,
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normalization="base",
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):
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"""
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This function represents facial images as vectors. The function uses convolutional neural
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networks models to generate vector embeddings.
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@ -710,7 +714,6 @@ def stream(
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time_threshold=5,
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frame_threshold=5,
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):
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"""
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This function applies real time face recognition and facial attribute analysis
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@ -765,7 +768,6 @@ def extract_faces(
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align=True,
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grayscale=False,
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):
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"""
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This function applies pre-processing stages of a face recognition pipeline
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including detection and alignment
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@ -830,7 +832,7 @@ def detectFace(
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):
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"""
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Deprecated function. Use extract_faces for same functionality.
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This function applies pre-processing stages of a face recognition pipeline
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including detection and alignment
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@ -855,7 +857,7 @@ def detectFace(
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Returns:
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detected and aligned face as numpy array
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"""
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print("⚠️ Function detectFace is deprecated. Use extract_faces instead.")
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face_objs = extract_faces(
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