From 0a65934c562753f5d04be97e6cbc45b211be1106 Mon Sep 17 00:00:00 2001 From: Toys_On_Desk Date: Tue, 1 Jul 2025 14:26:29 +0530 Subject: [PATCH] Refactor: moved is_valid_landmark to closure, improved landmark_sanitization test --- deepface/modules/detection.py | 43 ++++++++++---------------- tests/test_landmark_sanitization.py | 48 ++++++++++++----------------- 2 files changed, 37 insertions(+), 54 deletions(-) diff --git a/deepface/modules/detection.py b/deepface/modules/detection.py index 934216f..f413f60 100644 --- a/deepface/modules/detection.py +++ b/deepface/modules/detection.py @@ -80,30 +80,6 @@ def extract_faces( just available in the result only if anti_spoofing is set to True in input arguments. """ - def is_valid_landmark(coord, width, height): - """ - Check if a landmark coordinate is within valid image bounds - - Args: - coord: (x, y) tuple or None; width; height: image dimensions - Returns True if coord is a valid (x, y) inside the image, else False - - Returns: - bool: True if coordinate is valid and within bounds, False otherwise - """ - if coord is None: - return False - - # handle case where coord might not be a tuple/list - try: - x, y = coord - except (TypeError, ValueError): - return False - - # check if coordinates are within image bounds - return 0 <= x < width and 0 <= y < height - - resp_objs = [] # img might be path, base64 or numpy array. Convert it to numpy whatever it is. @@ -114,6 +90,22 @@ def extract_faces( height, width, _ = img.shape + def is_valid_landmark(coord: Optional[Union[tuple, list]]) -> bool: + """ + Check if a landmark coordinate is within valid image bounds. + + Args: + coord (tuple or list or None): (x, y) coordinate to check. + Returns: + bool: True if coordinate is valid and within bounds, False otherwise. + """ + if coord is None: + return False + if not (isinstance(coord, (tuple, list)) and len(coord) == 2): + return False + x, y = coord + return 0 <= x < width and 0 <= y < height + base_region = FacialAreaRegion(x=0, y=0, w=width, h=height, confidence=0) if detector_backend == "skip": @@ -173,7 +165,6 @@ def extract_faces( w = min(width - x - 1, int(current_region.w)) h = min(height - y - 1, int(current_region.h)) - # landmark vaildation landmarks = { "left_eye":current_region.left_eye, "right_eye":current_region.right_eye, @@ -184,7 +175,7 @@ def extract_faces( # Sanitize landmarks - set invalid ones to None for key, value in landmarks.items(): - if not is_valid_landmark(value, width, height): + if not is_valid_landmark(value): landmarks[key] = None diff --git a/tests/test_landmark_sanitization.py b/tests/test_landmark_sanitization.py index 4fc6e44..1cdf483 100644 --- a/tests/test_landmark_sanitization.py +++ b/tests/test_landmark_sanitization.py @@ -1,17 +1,19 @@ import numpy as np import pytest from deepface.modules.detection import extract_faces, DetectedFace, FacialAreaRegion +from deepface.commons.logger import Logger + +logger = Logger() + +def is_valid_landmark(coord, width, height): + if coord is None: + return False + if not (isinstance(coord, (tuple, list)) and len(coord) == 2): + return False + x, y = coord + return 0 <= x < width and 0 <= y < height def sanitize_landmarks(region, width, height): - def is_valid_landmark(coord, width, height): - if coord is None: - return False - try: - x, y = coord - except (TypeError, ValueError): - return False - return 0 <= x < width and 0 <= y < height - landmarks = { "left_eye": region.left_eye, "right_eye": region.right_eye, @@ -20,11 +22,13 @@ def sanitize_landmarks(region, width, height): "mouth_right": region.mouth_right, } for key, value in landmarks.items(): - if not is_valid_landmark(value, 100, 100): + if not is_valid_landmark(value, width, height): landmarks[key] = None return landmarks def test_sanitize_landmarks(): + img = np.zeros((100, 100, 3), dtype=np.uint8) + height, width = img.shape[:2] region = FacialAreaRegion( x=10, y=10, w=50, h=50, left_eye=(-5, 20), # invalid @@ -34,20 +38,17 @@ def test_sanitize_landmarks(): mouth_right=(20, -10), # invalid confidence=0.9 ) - landmarks = sanitize_landmarks(region, 100, 100) - print("Sanitized landmarks:", landmarks) + landmarks = sanitize_landmarks(region, width, height) + logger.info(f"Sanitized landmarks: {landmarks}") assert landmarks["left_eye"] is None assert landmarks["right_eye"] is None assert landmarks["nose"] == (30, 30) assert landmarks["mouth_left"] is None assert landmarks["mouth_right"] is None - print("Test passed: Invalid landmarks are sanitized to None.") + logger.info("Test passed: Invalid landmarks are sanitized to None.") def test_extract_faces_sanitizes_landmarks(monkeypatch): - # Create a dummy image img = np.zeros((100, 100, 3), dtype=np.uint8) - - # Create a DetectedFace with off-image landmarks facial_area = FacialAreaRegion( x=10, y=10, w=50, h=50, left_eye=(-5, 20), # invalid @@ -58,21 +59,12 @@ def test_extract_faces_sanitizes_landmarks(monkeypatch): confidence=0.9 ) detected_face = DetectedFace(img=img, facial_area=facial_area, confidence=0.9) - - # Patch detect_faces to return our test face - monkeypatch.setattr("f_deepface.deepface.modules.detection.detect_faces", lambda *args, **kwargs: [detected_face]) - - # Use a different backend that will call detect_faces + monkeypatch.setattr("deepface.modules.detection.detect_faces", lambda *args, **kwargs: [detected_face]) result = extract_faces(img, detector_backend="opencv", enforce_detection=False) facial_area_out = result[0]["facial_area"] - - print("Output facial_area:", facial_area_out) # Debug print - + logger.info(f"Output facial_area: {facial_area_out}") assert facial_area_out["left_eye"] is None assert facial_area_out["right_eye"] is None assert facial_area_out.get("nose") == (30, 30) assert facial_area_out.get("mouth_left") is None - assert facial_area_out.get("mouth_right") is None - -if __name__ == "__main__": - test_sanitize_landmarks() \ No newline at end of file + assert facial_area_out.get("mouth_right") is None \ No newline at end of file