From eb92b45567dee804e079f2b766b0b48d29d2ec8b Mon Sep 17 00:00:00 2001 From: Alexandre Date: Thu, 9 Feb 2023 08:43:26 +0100 Subject: [PATCH] Commit --- CompletedCode.py | 4 ++-- ProgrammingForFaceDetection.py | 17 +++++++++++++++++ 2 files changed, 19 insertions(+), 2 deletions(-) diff --git a/CompletedCode.py b/CompletedCode.py index 2f92c1c..bc564b7 100644 --- a/CompletedCode.py +++ b/CompletedCode.py @@ -40,8 +40,8 @@ for i in range(num_frames): if len(face) > 0: x, y, w, h = face[0] face = frame[y:y+h, x:x+w] - frame = cv2.rectangle(frame, (int(x*1.15), y), - (x + int(w*0.7), y + h), (0, 255, 0), 3) + frame = cv2.rectangle(frame, (int(x*1.15), int(y*1.15)), + (x + int(w*0.7), y + int(h*0.2)), (0, 255, 0), 3) # Afficher l'image # cv2.imshow("Faces", frame) # cv2.waitKey(0) diff --git a/ProgrammingForFaceDetection.py b/ProgrammingForFaceDetection.py index fcfda97..65c54fa 100644 --- a/ProgrammingForFaceDetection.py +++ b/ProgrammingForFaceDetection.py @@ -6,6 +6,8 @@ import numpy as np # Charger le classificateur Haar Cascade face_cascade = cv2.CascadeClassifier("Haar_Cascade.xml") +average_rgb = [] + # Charger l'image dans OpenCV # Convertir l'image en niveaux de gris img = cv2.imread("PhotoTest.jpg") @@ -25,3 +27,18 @@ for x, y, w, h in face: # Afficher l'image cv2.imshow("Faces", img) cv2.waitKey(0) + +b, g, r = cv2.split(img) +cv2.imshow("b", b) +cv2.imshow("g", g) +cv2.imshow("r", r) +cv2.waitKey(0) +# Calculate average on each channel +avg_b = np.mean(b) / 255 +avg_g = np.mean(g) / 255 +avg_r = np.mean(r) / 255 + +# Add to list +average_rgb.append([avg_b, avg_g, avg_r]) +# frame_matrices.append(face) +print(average_rgb)