From 7c672b2aa95a5ecf493e699bd0f88a90dc619a4f Mon Sep 17 00:00:00 2001
From: gdamms <damguillotin@gmail.com>
Date: Tue, 25 Jun 2024 10:44:42 +0200
Subject: haar cascade

---
 utils.py | 32 ++++++++++++++++++++++++++++++--
 1 file changed, 30 insertions(+), 2 deletions(-)

diff --git a/utils.py b/utils.py
index 509bd11..9935d16 100644
--- a/utils.py
+++ b/utils.py
@@ -1,6 +1,6 @@
 import numpy as np
 import scipy.linalg
-import matplotlib.pyplot as plt
+import cv2
 
 
 def fid(reals, fakes):
@@ -77,4 +77,32 @@ def jsd(reals, fakes):
 
     hist_avg = (hist_real + hist_fake) / 2
 
-    return 0.5 * (np.mean(np.log(hist_real / hist_avg)) + np.mean(np.log(hist_fake / hist_avg)))
\ No newline at end of file
+    return 0.5 * (np.mean(np.log(hist_real / hist_avg)) + np.mean(np.log(hist_fake / hist_avg)))
+
+
+def haar(image):
+    # Load the Haar cascade for face detection
+    face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
+
+    # Convert the image to grayscale
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    # Perform face detection
+    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=4)
+
+    # Draw rectangles around the detected faces
+    for (x, y, w, h) in faces:
+        cv2.rectangle(image, (x, y), (x+w, y+h), (255, 0, 0), 2)
+
+    # Display the result
+    cv2.imshow('Face Detection', image)
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()
+
+
+if __name__ == '__main__':
+    # Load the image
+    image = cv2.imread('data/edface/500/03120500_000.png')
+
+    # Perform face detection
+    haar(image)
\ No newline at end of file
-- 
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